From cc81a21523915a1d02feb70c587cf678f5b4cd86 Mon Sep 17 00:00:00 2001 From: swinston Date: Mon, 16 Mar 2026 15:36:23 -0700 Subject: [PATCH 1/5] Add Advanced Vulkan Compute tutorial sections on memory models, OpenCL, and conclusion Add comprehensive documentation covering Vulkan Memory Model (availability/visibility/domain operations), shared memory (LDS) with bank conflict details, memory consistency with GroupMemoryBarrierWithGroupSync, OpenCL C to SPIR-V pipeline (clspv), kernel portability guidelines, clvk layering, and tutorial conclusion. Include navigation entries for all new compute architecture sections. --- antora/modules/ROOT/nav.adoc | 57 ++++++++ .../01_introduction.adoc | 45 ++++++ .../02_workgroups_and_invocations.adoc | 83 ++++++++++++ .../03_occupancy_and_latency_hiding.adoc | 70 ++++++++++ .../04_vulkan_1_4_scalar_layouts.adoc | 120 ++++++++++++++++ .../03_Memory_Models/01_introduction.adoc | 34 +++++ .../02_vulkan_memory_model.adoc | 68 ++++++++++ .../03_shared_memory_lds.adoc | 102 ++++++++++++++ .../04_memory_consistency.adoc | 66 +++++++++ .../01_introduction.adoc | 33 +++++ .../02_cross_invocation_communication.adoc | 76 +++++++++++ .../03_subgroup_partitioning.adoc | 73 ++++++++++ .../04_non_uniform_indexing.adoc | 73 ++++++++++ .../05_OpenCL_on_Vulkan/01_introduction.adoc | 29 ++++ .../02_setup_and_installation.adoc | 76 +++++++++++ .../03_clspv_pipeline.adoc | 58 ++++++++ .../04_kernel_portability.adoc | 46 +++++++ .../05_clvk_and_layering.adoc | 40 ++++++ .../01_introduction.adoc | 39 ++++++ .../02_setup_and_installation.adoc | 69 ++++++++++ .../03_single_source_gpgpu.adoc | 62 +++++++++ .../04_vulkan_interoperability.adoc | 53 ++++++++ .../05_unified_shared_memory_usm.adoc | 53 ++++++++ .../01_introduction.adoc | 32 +++++ .../02_gpu_resident_trees.adoc | 104 ++++++++++++++ .../03_global_atomic_management.adoc | 128 ++++++++++++++++++ .../04_device_addressable_buffers.adoc | 101 ++++++++++++++ .../01_introduction.adoc | 37 +++++ .../02_indirect_dispatch.adoc | 97 +++++++++++++ .../03_gpu_side_command_generation.adoc | 41 ++++++ .../04_multi_draw_indirect_mdi.adoc | 47 +++++++ .../01_introduction.adoc | 20 +++ .../02_concurrent_execution.adoc | 64 +++++++++ .../03_timeline_semaphores.adoc | 50 +++++++ .../04_queue_priority.adoc | 39 ++++++ .../10_Specialized_Math/01_introduction.adoc | 12 ++ .../02_cooperative_matrices.adoc | 122 +++++++++++++++++ .../03_mixed_precision.adoc | 103 ++++++++++++++ .../01_introduction.adoc | 28 ++++ .../02_instruction_throughput.adoc | 49 +++++++ .../03_divergence_audit.adoc | 64 +++++++++ .../01_introduction.adoc | 28 ++++ .../02_compute_validation.adoc | 71 ++++++++++ .../03_assistant_led_optimization.adoc | 67 +++++++++ en/Advanced_Vulkan_Compute/conclusion.adoc | 50 +++++++ en/Advanced_Vulkan_Compute/introduction.adoc | 64 +++++++++ 46 files changed, 2843 insertions(+) create mode 100644 en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc create mode 100644 en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc create mode 100644 en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc create mode 100644 en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc create mode 100644 en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc create mode 100644 en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc create mode 100644 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100644 --- a/antora/modules/ROOT/nav.adoc +++ b/antora/modules/ROOT/nav.adoc @@ -149,3 +149,60 @@ *** xref:Building_a_Simple_Engine/Advanced_Topics/Robustness2.adoc[Robustness2] ** Appendix *** xref:Building_a_Simple_Engine/Appendix/appendix.adoc[Appendix] +* Advanced Vulkan Compute +** xref:Advanced_Vulkan_Compute/introduction.adoc[Introduction] +** The Compute Architecture and Execution Model +*** xref:Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc[Workgroups and Invocations] +*** xref:Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc[Occupancy and Latency Hiding] +*** xref:Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc[Vulkan 1.4 Scalar Layouts] +** Memory Models and Consistency +*** xref:Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc[The Vulkan Memory Model] +*** xref:Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc[Shared Memory (LDS)] +*** xref:Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc[Memory Consistency] +** Subgroup Operations: The Hidden Power +*** xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc[Cross-Invocation Communication] +*** xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc[Subgroup Partitioning] +*** xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc[Non-Uniform Indexing] +** Heterogeneous Ecosystem: OpenCL on Vulkan +*** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc[Setup and Installation] +*** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc[The clspv Pipeline] +*** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc[Kernel Portability] +*** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[clvk and Layering] +** High-Level Abstraction: SYCL and Single-Source C++ +*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc[Setup and Installation] +*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc[Single-Source GPGPU] +*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc[Vulkan Interoperability] +*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc[Unified Shared Memory (USM)] +** Advanced Data Structures on the GPU +*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/02_gpu_resident_trees.adoc[GPU-Resident Trees] +*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/03_global_atomic_management.adoc[Global Atomic Management] +*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Device-Addressable Buffers] +** Indirect Dispatch and GPU-Driven Pipelines +*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/02_indirect_dispatch.adoc[Indirect Dispatch] +*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc[GPU-Side Command Generation] +*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Multi-Draw Indirect (MDI)] +** Asynchronous Compute Orchestration +*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/02_concurrent_execution.adoc[Concurrent Execution] +*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/03_timeline_semaphores.adoc[Timeline Semaphores] +*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc[Queue Priority] +** Cooperative Matrices and Specialized Math +*** xref:Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/10_Specialized_Math/02_cooperative_matrices.adoc[Cooperative Matrices] +*** xref:Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc[Mixed Precision] +** Performance Auditing and Optimization +*** xref:Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/11_Performance_Optimization/02_instruction_throughput.adoc[Instruction Throughput Analysis] +*** xref:Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc[The "Divergence" Audit] +** Diagnostics and AI-Assisted Compute Refinement +*** xref:Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc[Compute Validation] +*** xref:Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Assistant-Led Optimization] +** xref:Advanced_Vulkan_Compute/conclusion.adoc[Conclusion] diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc new file mode 100644 index 00000000..81e70ddb --- /dev/null +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc @@ -0,0 +1,45 @@ +:pp: {plus}{plus} + += The Compute Architecture and Execution Model: Introduction + +== Overview + +To write efficient compute kernels, you must look beyond the abstract execution model of "workgroups" and "invocations" and understand how these concepts map to the physical hardware. While Vulkan provides a cross-vendor API, the silicon beneath it from AMD, NVIDIA, and Intel has specific ways of handling your data. + +In this chapter, we will bridge the gap between your shader code and the silicon. We'll explore how the 3D grid system you define in `vkCmdDispatch` is sliced, diced, and distributed across the GPU's **Compute Units (CU)** or **Streaming Multiprocessors (SM)**. + +=== The Language of Silicon + +Before we dive in, let's align our vocabulary. Different vendors use different names for the same concepts: + +* **Workgroups** (Vulkan/OpenCL) are often mapped to **Thread Blocks** (CUDA). +* **Invocations** (Vulkan) are simply **Threads**. +* **Subgroups** (Vulkan) are called **Wavefronts** (AMD) or **Warps** (NVIDIA). +* **Compute Units** (AMD) are equivalent to **Streaming Multiprocessors** (NVIDIA). + +Understanding these mappings allows you to read hardware-specific documentation and performance guides regardless of which GPU you are targeting. + +== Hardware Mapping + +When you dispatch a workload, the GPU's hardware command processor breaks the global grid into individual workgroups. These workgroups are the fundamental unit of scheduling. + +A critical rule of the GPU execution model is **workgroup atomicity**: once a workgroup is assigned to a physical compute unit, all its invocations will stay on that unit until the workgroup completes. They cannot be split across multiple units. This locality is what enables **Shared Memory (LDS - Local Data Store)**—since all threads in a workgroup are physically on the same hardware block, they can share a dedicated, ultra-fast cache. + +=== Invocations and SIMD + +While workgroups are the scheduling unit, the **invocation** is the smallest unit of execution. However, GPUs are **SIMD (Single Instruction, Multiple Data)** machines. They don't execute invocations one by one; instead, they group them into small bundles (Subgroups). + +In these bundles, every invocation executes the exact same instruction at the same time, but on different data. This is incredibly efficient for math, but it introduces a major pitfall: **Branch Divergence**. If your code contains an `if` statement where some threads go left and others go right, the hardware must execute *both* paths, masking out the inactive threads for each. + +== Performance Metrics + +Throughout this section, we will focus on two key metrics that determine how well you're utilizing the hardware: + +1. **Occupancy**: This is the "concurrency" metric. It represents how many active workgroups are residing on a compute unit compared to its theoretical maximum. High occupancy helps **hide latency**—if one bundle is waiting for a memory fetch from slow VRAM, the scheduler can instantly switch to another bundle that's ready to do math. +2. **Bandwidth Efficiency**: This is the "throughput" metric. Modern GPUs have massive memory bandwidth, but it's easily wasted by poor data alignment. We'll see how Vulkan 1.4's **Scalar Layouts** allow us to pack data tightly, ensuring that the shader actually uses every byte fetched from VRAM. + +== What's Next? + +We'll start by diving into the 3D grid system and seeing exactly how it maps to physical hardware. From there, we'll learn how to calculate theoretical occupancy and use engine tools to monitor real-world utilization. Finally, we'll master the scalar block layouts to maximize your data throughput. + +xref:../introduction.adoc[Previous: Introduction] | xref:02_workgroups_and_invocations.adoc[Next: Workgroups and Invocations] diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc new file mode 100644 index 00000000..269db9f5 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc @@ -0,0 +1,83 @@ +:pp: {plus}{plus} + += Workgroups and Invocations: The 3D Lattice + +== Introduction + +In the basic compute tutorial, we used a simple one-dimensional dispatch. While that works for simple tasks, it doesn't represent how the GPU actually schedules work. To write high-performance kernels, you need to understand how Vulkan's 3D grid system maps to the physical silicon of the GPU. + +The grid system is more than just a convenient way to index into textures; it defines how your workload is subdivided and scheduled across the hardware. + +== The Three-Tier Hierarchy + +When you define a compute dispatch, you are working with a hierarchy of units. Getting these dimensions right is the first step toward high performance. + +1. **Global Dispatch Grid**: This is the entire workload, defined in `vkCmdDispatch(x, y, z)`. +2. **Workgroups**: The global grid is subdivided into workgroups. The GPU's hardware scheduler assigns these workgroups to physical compute units. +3. **Invocations**: Each workgroup contains multiple individual threads, defined by the `local_size` in your shader. + +=== Workgroup Locality + +In the previous section, we mentioned that a workgroup cannot be split across multiple physical **Compute Units** (CU, on AMD/Intel) or **Streaming Multiprocessors** (SM, on NVIDIA). This means that all invocations within a workgroup are physically executed on the same hardware block. + +This locality is a key design constraint. It allows invocations in the same workgroup to share a fast, local memory known as **LDS** (Local Data Store) or **groupshared** memory, but it also means that the size of your workgroup is limited by the physical resources of a single CU/SM. If your workgroup size is too large, the GPU simply won't be able to schedule it. + +== The Math of Indexing + +Vulkan provides several built-in variables to help you find your place in the grid. In Slang, these are typically passed as parameters to the entry point using semantics like `SV_DispatchThreadID`, `SV_GroupThreadID`, and `SV_GroupID`. + +Let's look at how these relate in a typical shader: + +[source,slang] +---- +[numthreads(16, 16, 1)] +void main( + uint3 groupID : SV_GroupID, // gl_WorkGroupID + uint3 localID : SV_GroupThreadID, // gl_LocalInvocationID + uint3 globalID : SV_DispatchThreadID // gl_GlobalInvocationID +) { + // globalID: The unique index for this thread in the entire grid + // Formula: globalID = groupID * numthreads + localID + uint x = globalID.x; + uint y = globalID.y; + + // Process pixel (x, y) +} +---- + +Using a 2D or 3D grid makes spatial tasks (like image processing or physics simulations) much cleaner. Instead of manually calculating a 1D index, you can use `.xy` or `.xyz` coordinates that match your data structure. + +== Choosing Optimal Sizes + +A common mistake is choosing workgroup sizes based solely on what "fits" your data. For example, if you're processing a 10x10 image, you might choose a workgroup size of (10, 10, 1). + +However, GPUs execute invocations in bundles of 32 or 64—known as **Subgroups**, **Warps** (NVIDIA), or **Wavefronts** (AMD). If your workgroup size is not a multiple of the hardware's native bundle size, you are leaving silicon idle. This is called **internal fragmentation**. + +=== The Rule of 32/64 + +* **NVIDIA** GPUs typically prefer multiples of **32** (Warps). +* **AMD** GPUs typically prefer multiples of **64** (Wavefronts), though modern RDNA architectures can also handle 32. +* **Intel** GPUs have variable sizes (8, 16, 32). + +A safe, portable choice for many workloads is a workgroup size of **64** or **256** (e.g., `16x16` or `8x8x4`). This ensures that most hardware can keep its **SIMD** (Single Instruction, Multiple Data) lanes full. + +== Dispatching the Work + +When you call `vkCmdDispatch(groupCountX, groupCountY, groupCountZ)`, you are defining how many times the `local_size` block is repeated. + +If you have an image of size `width` x `height` and a workgroup size of `16x16`, your dispatch would look like this: + +[source,cpp] +---- +uint32_t groupCountX = (width + 15) / 16; +uint32_t groupCountY = (height + 15) / 16; +commandBuffer.dispatch(groupCountX, groupCountY, 1); +---- + +Note the use of "rounding up" (`(width + 15) / 16`). This ensures that if your image size isn't a perfect multiple of 16, you don't miss the last few pixels. Inside the shader, you would then use a bounds check: `if (x < width && y < height)`. + +== What's Next? + +Understanding how workgroups map to hardware is the foundation of GPU compute. But mapping work to hardware is only part of the story; we also need to keep that hardware busy. In the next section, we'll talk about **Occupancy** and how to hide the massive latency of VRAM. + +xref:01_introduction.adoc[Previous: Introduction] | xref:03_occupancy_and_latency_hiding.adoc[Next: Occupancy and Latency Hiding] diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc new file mode 100644 index 00000000..d3844d8b --- /dev/null +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc @@ -0,0 +1,70 @@ +:pp: {plus}{plus} + += Occupancy and Latency Hiding: Keeping the GPU Busy + +== Introduction + +In the previous section, we learned how workgroups are mapped to the GPU's factory floor (the Compute Units or SMs). But simply getting a workgroup onto a CU is only half the battle. If that workgroup is poorly designed, it might only use a fraction of the hardware's potential, leaving expensive silicon sitting idle. + +To understand why this happens, we must talk about **Latency** and **Occupancy**. + +== The Latency Gap + +GPUs are memory-bound. While a modern GPU can perform trillions of floating-point operations per second (**TFLOPS**), fetching a single piece of data from **VRAM** (Video Random Access Memory) can take hundreds or even thousands of clock cycles. + +If a bundle of invocations (a warp or wavefront) needs to read from memory, it has to wait. If that CU only has one bundle to run, the entire CU goes silent until the data arrives. This is a disaster for performance, and is known as **memory latency**. + +The GPU's solution is **Concurrency**. Instead of waiting for one bundle, the CU switches to another bundle that is ready to execute. The more bundles you have "in flight" on a single CU, the better you can hide the latency of memory fetches. + +== Defining Occupancy + +**Occupancy** is a measure of how many bundles are active on a CU compared to the theoretical maximum. It's often expressed as a percentage. + +* **100% Occupancy**: The CU is completely packed with bundles. Whenever one waits for memory, there's almost certainly another one ready to go. +* **Low Occupancy**: Only a few bundles are active. If they all hit a memory fetch at the same time, the CU will stall. + +=== The Resource Tug-of-War + +You might wonder: "Why not just always dispatch thousands of threads?" The problem is that each Compute Unit has a fixed pool of physical resources. Every thread you add consumes a portion of that pool. + +The three primary limiters of occupancy are: + +1. **Registers**: Each thread needs a set of registers to store its variables. If your shader uses 128 registers, you can fit fewer threads than if it used 32. +2. **Shared Memory (LDS)**: This memory is shared by the whole workgroup. If your workgroup uses 32KB of LDS and the CU only has 64KB, you can only fit two workgroups on that CU, regardless of how many threads they have. +3. **Thread/Warp Slots**: There is a hard limit on how many threads the hardware scheduler can track at once (e.g., 2048 threads per CU). + +|=== +| Resource Usage | Impact on Occupancy | Result + +| High Register Count +| **Negative** +| Fewer bundles per CU; harder to hide latency. + +| High LDS Usage +| **Negative** +| Fewer workgroups per CU; limited concurrency. + +| Small Workgroup Size +| **Neutral/Negative** +| May not fill all warp slots; scheduling overhead. +|=== + +== Calculating Theoretical Occupancy + +Most GPU vendors provide tools (like NVIDIA's Nsight or AMD's RGP) that calculate occupancy for you. However, you can estimate it yourself by looking at your shader's resource usage. + +If a CU has 64KB of shared memory and your workgroup uses 32KB, your CU can only ever host two workgroups at a time. If your workgroup size is small (say, 64 threads), you'll have 128 threads per CU. If that hardware is capable of tracking 2048 threads, your occupancy is only around 6%. + +This is why "fat" shaders (those that use lots of registers or shared memory) often perform poorly unless they are carefully tuned. + +== Monitoring Utilization + +In a real engine, you don't just want to guess. Modern Vulkan engines use performance counters (via the `VK_KHR_performance_query` extension) to monitor hardware utilization in real-time. + +By tracking metrics like **ValuUtilization** (AMD) or **SM Active** (NVIDIA), you can see if your kernels are actually keeping the hardware busy. If you see high memory latency but low occupancy, you know you need to optimize your register usage or shared memory footprint. + +== What's Next? + +Now that we know how to keep the GPU busy, we need to make sure that when it *is* busy, it's being efficient. In the final section of this chapter, we'll look at **Scalar Layouts**—a Vulkan 1.4 feature that allows us to pack our data tightly and maximize the bandwidth we've worked so hard to hide. + +xref:02_workgroups_and_invocations.adoc[Previous: Workgroups and Invocations] | xref:04_vulkan_1_4_scalar_layouts.adoc[Next: Vulkan 1.4 Scalar Layouts] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc new file mode 100644 index 00000000..d8cc88b2 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc @@ -0,0 +1,120 @@ +:pp: {plus}{plus} + += Vulkan 1.4 Scalar Layouts: Tight Packing + +== Introduction + +In the previous sections, we've focused on keeping the GPU's Compute Units busy through high occupancy. But even if you have thousands of threads active, you can still be held back by **Bandwidth**. + +Every byte you fetch from VRAM is precious. If your data is poorly laid out, you might be fetching bytes you never use. In this final section of the Compute Architecture chapter, we'll look at how Vulkan 1.4's **Scalar Layouts** solve one of the oldest and most frustrating problems in GPU programming: the alignment tax. + +== The Alignment Tax: std140 and std430 + +Historically, OpenGL and Vulkan required you to lay out your buffers using strict alignment rules known as **std140** and **std430** (standard 140/430 layouts). These rules were designed for older hardware that had difficulty reading data that wasn't perfectly aligned to 4-byte or 16-byte boundaries. + +For example, under `std140`, a simple `vec3` (which is three floats) would often be padded to the size of a `vec4`. This means that if you had an array of `vec3`, 25% of your memory bandwidth was being wasted on empty padding! + +[source,slang] +---- +// Under std140: +struct MyData { + float3 position; // 12 bytes + 4 bytes padding + float radius; // 4 bytes +}; +// Total size: 20 bytes (but logically 16) +---- + +`std430` improved this by allowing tighter packing for arrays of scalars and vectors, but it still had strict rules about how nested structures were aligned. + +== Enter GL_EXT_scalar_block_layout + +To solve this, a new extension called **GL_EXT_scalar_block_layout** was introduced. This extension allows you to use a **scalar layout**, which essentially removes all padding between members of a structure or elements of an array. + +In Vulkan 1.4, this functionality is now a core requirement. By using the `scalar` layout, you can ensure that your data structures on the GPU match your C{pp} structures perfectly, byte-for-byte. + +=== Why does this matter? + +It's not just about saving a few bytes of VRAM. It's about **Cache Efficiency**. + +When the GPU fetches data from VRAM, it fetches it in large "cache lines" (often 64 or 128 bytes). If your data is full of padding, each cache line will contain less "real" data. This means you have to perform more memory fetches to get the same amount of information, which directly leads to lower performance. + +=== Slang: Automatic Packing + +If you are using Slang, you don't even need to worry about manual layout qualifiers for most cases. Slang's layout engine handles the `scalar` rules for you when targeting Vulkan 1.4: + +[source,slang] +---- +struct MyData { + float3 position; + float radius; +}; + +[[vk::binding(0, 0)]] +RWStructuredBuffer MyBuffer; +---- + +The `RWStructuredBuffer` in Slang maps to a `Storage Buffer` in Vulkan, and because Slang defaults to natural alignment, it produces the same result as the `scalar` layout in GLSL without the boilerplate. + +=== GLSL: The Manual Struggle + +To truly appreciate the "win" in Vulkan 1.4, let's look at how this same structure would be handled in GLSL under the older `std430` rules vs. the modern `scalar` layout. + +[source,glsl] +---- +// The "Old" Way (std430) +struct MyData { + vec3 position; // 12 bytes + 4 bytes padding (arrays of vec3 are even worse!) + float radius; // 4 bytes +}; + +layout(std430, binding = 0) buffer MyBuffer { + MyData data[]; +}; +---- + +Under `std430`, if you had an array of `MyData`, each `vec3` would be padded to 16 bytes. If you tried to match this with a simple `struct { glm::vec3 p; float r; }` on the CPU, you would likely experience memory corruption because the GPU expects that 4-byte gap between `position` and `radius`. + +Now, look at the Vulkan 1.4 way using the **scalar** layout: + +[source,glsl] +---- +// The "Modern" Way (Vulkan 1.4 / GL_EXT_scalar_block_layout) +#extension GL_EXT_scalar_block_layout : enable + +struct MyData { + vec3 position; // 12 bytes + float radius; // 4 bytes +}; + +layout(scalar, binding = 0) buffer MyBuffer { + MyData data[]; +}; +// Total size of MyData: 16 bytes. No padding! +---- + +By explicitly using `layout(scalar)`, you tell the driver that you want the tighter packing rules. This allows your GLSL code to perfectly match a standard C{pp} struct without any manual `float padding` members. + +=== C{pp} Side Comparison + +To match this on the CPU, you no longer need to manually add `float padding[1]` or use `alignas(16)`. You can simply define your structure naturally: + +[source,cpp] +---- +struct MyData { + glm::vec3 position; + float radius; +}; +// Total size: 16 bytes. No padding! +---- + +If you are using modern languages like Slang, this becomes even easier. Slang defaults to a more natural, C{pp}-like layout, and its Vulkan backend handles the scalar layout details for you automatically when targeting Vulkan 1.4. + +== Conclusion + +We've covered a lot of ground in this chapter. We've seen how workgroups map to silicon, how occupancy helps us hide the massive latency of memory fetches, and how scalar layouts ensure we aren't wasting the bandwidth we've worked so hard to use. + +By understanding these low-level architectural details, you've moved beyond "writing shaders" and started "programming the hardware." + +In the next chapter, we'll take these concepts even further by looking at the **Vulkan Memory Model** and how to safely synchronize data between thousands of threads. + +xref:03_occupancy_and_latency_hiding.adoc[Previous: Occupancy and Latency Hiding] | xref:../03_Memory_Models/01_introduction.adoc[Next: Memory Models and Consistency] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc new file mode 100644 index 00000000..dbab97ea --- /dev/null +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc @@ -0,0 +1,34 @@ +:pp: {plus}{plus} + += Memory Models and Consistency: Introduction + +== Overview + +In the previous chapter, we looked at how to keep the GPU busy through high occupancy and tight data layouts. But as you scale your compute dispatches from simple, independent tasks to complex, cooperative algorithms, you'll quickly encounter a much more challenging problem: **Memory Consistency** (ensuring all parts of the GPU see the same data at the same time). + +How do you know that a value written by one invocation is visible to another? What happens when two invocations try to write to the same location at once? How do you share data efficiently between thousands of threads without crashing into a race condition? + +=== The Explicit Nature of Vulkan + +On the CPU, you're used to a world where memory is generally **coherent**. If Thread A writes a value to a variable, Thread B can usually read it shortly after without any special ceremony because the hardware keeps the caches in sync automatically. + +On the GPU, this is **not** the case. With thousands of threads executing concurrently across multiple compute units, each with its own hierarchical caches (**L1** - Level 1 and **L2** - Level 2, etc.), keeping everyone's view of memory in sync is an incredibly expensive task. Vulkan's philosophy is simple: **synchronization is never automatic**. If you want a write to be visible to a read, you must explicitly say so. + +== The Three Pillars of Memory Management + +In this chapter, we'll dive deep into the mechanisms Vulkan provides to manage this complexity: + +1. **The Vulkan Memory Model**: Mastering Availability, Visibility, and Domain operations to create a formal **"Happens-Before"** relationship (a strict ordering of operations) between threads. +2. **Shared Memory (LDS)**: Utilizing a small, ultra-fast, workgroup-local memory for high-speed data exchange and manual caching. +3. **Memory Consistency**: Using Slang's `GroupMemoryBarrierWithGroupSync` vs. fine-grained Vulkan 1.4 barriers to minimize pipeline stalls and maximize throughput. + +== Why This Matters + +Efficient memory synchronization is the difference between a high-performance simulation and a broken, non-deterministic mess. + +* **Over-synchronization**: Your kernels will be slow because every thread is constantly waiting for every other thread. +* **Under-synchronization**: You'll get flickering results, "ghost" data, and hard-to-debug crashes that only appear on certain hardware. + +We'll start by looking at the theoretical foundation: the **Vulkan Memory Model**. While it might seem abstract at first, it is the key to writing portable, robust compute code that works on every GPU from a smartphone to a high-end workstation. + +xref:../02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc[Previous: Scalar Layouts] | xref:02_vulkan_memory_model.adoc[Next: The Vulkan Memory Model] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc new file mode 100644 index 00000000..c41d85a8 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc @@ -0,0 +1,68 @@ +:pp: {plus}{plus} + += The Vulkan Memory Model: Availability, Visibility, and Domain Operations + +In a GPU, you have thousands of threads running concurrently across multiple compute units, each with its own hierarchical caches (L1 - Level 1, L2 - Level 2, etc.) Because of this, it's not enough to simply write a value to a buffer and expect another thread to see it immediately. + +Instead, you need to follow a formal protocol to ensure that data written by one part of the device is available and visible to another. This protocol is defined by the **Vulkan Memory Model**. + +== The Three Pillars of Synchronization + +When you want to share data between two different operations, (e.g., a write in one thread and a read in another), you need to establish a **Happens-Before** relationship. This is done through three distinct operations: + +1. **Availability Operation**: This ensures that data written to a local cache is "pushed" out to a domain that is accessible to other operations. Think of this as flushing a cache. +2. **Visibility Operation**: This ensures that data that is available in a shared domain is "pulled" into the local cache of the thread that needs to read it. Think of this as invalidating a local cache so it's forced to read fresh data. +3. **Memory Domain**: This is the common "meeting ground" where availability and visibility operations meet (usually the L2 cache or VRAM). + +=== The Flow of Data + +[source,text] +---- +Thread A (Write) -> Availability Operation (Make Available) + | + [Memory Domain] + | +Thread B (Read) <- Visibility Operation (Make Visible) +---- + +== Happens-Before and Execution Barriers + +A "Happens-Before" relationship is established when an execution barrier (like `vkCmdPipelineBarrier2`) is used to synchronize two operations. This barrier specifies: + +* **srcStageMask/dstStageMask**: Which stages of the pipeline must complete before the next stages can begin. +* **srcAccessMask/dstAccessMask**: Which memory operations are being performed (writes vs. reads). + +In Vulkan 1.4, these masks have been simplified and unified with **Synchronization 2**, which we'll use throughout this tutorial. For example, a barrier between two compute dispatches might look like this: + +[source,cpp] +---- +vk::BufferMemoryBarrier2 bufferBarrier { + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderWrite, // Availability + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderRead // Visibility +}; + +vk::DependencyInfo dependencyInfo { + .bufferMemoryBarrierCount = 1, + .pBufferMemoryBarriers = &bufferBarrier +}; +// ... +commandBuffer.pipelineBarrier2(dependencyInfo); +---- + +== Why You Need to Care + +If you skip these steps, your kernel might appear to work on one GPU but fail on another. This is because different architectures have different cache coherency strategies. NVIDIA's caches might behave differently than AMD's or Intel's. + +The Vulkan Memory Model is your way of telling the driver exactly what you need, so it can emit the minimal set of hardware instructions to keep your data safe without sacrificing performance. + +== Data Races and Undefined Behavior + +When two threads access the same memory location and at least one of them is a write, and they aren't synchronized by a "Happens-Before" relationship, you have a **Data Race**. + +In Vulkan, data races result in **Undefined Behavior**. This doesn't just mean you get the wrong value; it could mean you read old data, partially updated data, or even crash the GPU if the race condition leads to an out-of-bounds access or a malformed pointer. + +Next, we'll see how to apply these concepts to **Shared Memory (LDS)**, which is much faster than global VRAM. + +xref:01_introduction.adoc[Previous: Introduction] | xref:03_shared_memory_lds.adoc[Next: Shared Memory (LDS)] diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc new file mode 100644 index 00000000..4c8ad667 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc @@ -0,0 +1,102 @@ +:pp: {plus}{plus} + += Shared Memory (LDS): High-Speed Data Exchange + +The GPU's main memory (VRAM) is large but relatively slow. For many compute tasks, fetching data from VRAM is the primary bottleneck. To solve this, GPUs provide a small, ultra-fast memory that is local to each workgroup. + +In Vulkan, this is called **Shared Memory**. On physical hardware, it is often referred to as **LDS (Local Data Store)** or **Scratchpad Memory** (a fast, temporary memory for local data). + +== Why Shared Memory? + +Shared memory is your most powerful tool for optimizing memory-bound kernels. It is typically used for: + +* **Manual Caching**: Reading a block of data from VRAM once, storing it in shared memory, and then having all threads in the workgroup read from that fast local copy multiple times. +* **Data Exchange**: Passing data between threads in the same workgroup (e.g., for calculating a **prefix sum**—where each element is the sum of all previous elements—or a **reduction**). +* **Workgroup-Level Reductions**: Finding the maximum or minimum value in a large dataset by first reducing it (combining multiple values into one) within each workgroup. + +== Using Shared Memory in Slang + +In Slang (and HLSL), you declare shared memory using the `groupshared` keyword. Because it is physically local to a Compute Unit, it is shared by all threads in a workgroup but is invisible to other workgroups. + +[source,slang] +---- +groupshared float sharedData[256]; + +[numthreads(256, 1, 1)] +void main(uint3 tid : SV_GroupThreadID) { + // Each thread initializes its own slot in shared memory + sharedData[tid.x] = someBuffer[tid.x]; + + // CRITICAL: We must wait for all threads to finish writing AND make those writes visible! + // GroupMemoryBarrier: Ensures all previous memory writes are complete and visible. + // WithGroupSync: Acts as an execution barrier, waiting for all threads in the group to arrive. + GroupMemoryBarrierWithGroupSync(); + + // Now it is safe to read data written by our neighbors + float neighborValue = sharedData[(tid.x + 1) % 256]; +} +---- + +=== Breaking Down the Cryptic Name + +The function `GroupMemoryBarrierWithGroupSync()` might seem like a mouthful, but its name tells you exactly what it's doing across two different types of synchronization: + +1. **GroupMemoryBarrier**: This is a **Memory Barrier**. It ensures that any writes a thread has made to `groupshared` memory are "pushed" out and made visible to all other threads in the workgroup. Without this, a neighbor might read an old or uninitialized value from your slot in shared memory. +2. **WithGroupSync**: This is an **Execution Barrier**. It forces every thread in the workgroup to stop and wait at this exact line. No thread can proceed to the next instruction until *every* thread in the group has reached this point. + +By combining them, you guarantee that when a thread moves past this line, all its neighbors have finished their work and their data is ready to be read. + +=== GLSL: shared and barrier() + +In GLSL, you use the `shared` keyword to declare your workgroup-local memory. The synchronization is handled by the `barrier()` function, which acts as both an execution barrier and a memory barrier for `shared` memory. + +[source,glsl] +---- +shared float sharedData[256]; + +layout(local_size_x = 256) in; +void main() { + uint tid = gl_LocalInvocationID.x; + + // Each thread initializes its own slot in shared memory + sharedData[tid] = someBuffer[tid]; + + // Wait for all threads to reach this point and make memory visible + barrier(); + + // Now it is safe to read + float neighborValue = sharedData[(tid + 1) % 256]; +} +---- + +The main difference here is Slang's `GroupMemoryBarrierWithGroupSync()`, which is a more descriptive name for the common pattern of combining a memory barrier with an execution sync. + +== Bank Conflicts: The Speed Trap + +Shared memory is organized into **Banks** (parallel memory modules, typically 32 banks). Each bank can handle one request per clock cycle. If your threads access memory in a way that maps to different banks, the operation is performed in parallel at full speed. + +However, if two or more threads in a bundle (subgroup) try to access different addresses that fall within the **same bank**, you get a **Bank Conflict**. The hardware must then serialize these requests, which can double or triple the execution time of that instruction. + +[source,text] +---- +// NO CONFLICT (Fast) +Thread 0 -> Bank 0 +Thread 1 -> Bank 1 +Thread 2 -> Bank 2 + +// BANK CONFLICT (Slow) +Thread 0 -> Bank 0 (Address 0) +Thread 1 -> Bank 0 (Address 32) +---- + +To avoid bank conflicts, aim for linear access patterns where `thread_id` matches `index`. Using a **stride** of 1 (accessing elements one after another) is usually the safest way to ensure full speed. + +== Lifecycle and Scope + +Shared memory is only valid for the lifetime of a single workgroup. When the workgroup completes, its shared memory is discarded. + +Crucially, **shared memory is not coherent between workgroups**. If you need to send data from Workgroup A to Workgroup B, you must write it back to global VRAM and use a proper Vulkan memory barrier as described in the previous section. + +In the next section, we'll see how to balance these barriers to keep your pipeline as full as possible. + +xref:02_vulkan_memory_model.adoc[Previous: The Vulkan Memory Model] | xref:04_memory_consistency.adoc[Next: Memory Consistency] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc new file mode 100644 index 00000000..97054fa1 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc @@ -0,0 +1,66 @@ +:pp: {plus}{plus} + += Memory Consistency: Slang Barriers and Pipeline Stalls + +In the previous sections, we've explored the "what" and "where" of synchronization. Now, we'll focus on the "how"—specifically, how to balance safety with performance to keep your GPU's pipeline full. + +== The All-In-One Barrier: GroupMemoryBarrierWithGroupSync + +Most developers start with Slang's `GroupMemoryBarrierWithGroupSync()`. This is a high-level function that combines two critical operations: + +1. **Execution Sync**: It forces every thread in the current workgroup to wait at this line. No thread can proceed until its neighbors have also reached the barrier. +2. **Memory Barrier**: It ensures that all memory writes performed by the workgroup (to both shared and global memory) are made available and visible. + +This function is essentially the "Safe Mode" of synchronization. Use it when you need to be 100% sure that all data is ready for the next step of an algorithm. + +=== GLSL: The Explicit Barriers + +In GLSL, you don't have a single "magic" function that does everything. Instead, you have to be explicit about what you are synchronizing. This is where many bugs creep in, but it's also where you can find performance wins. + +[source,glsl] +---- +// The GLSL equivalent of Slang's GroupMemoryBarrierWithGroupSync() +memoryBarrierShared(); // Make shared memory writes available/visible +barrier(); // Wait for all threads to reach this point +---- + +If you are working with **Global Memory** (SSBOs), `barrier()` alone is not enough! You must also call `memoryBarrierBuffer()` to ensure that your writes to the buffer are actually visible to other threads before they proceed past the barrier. + +[source,glsl] +---- +// Ensuring global memory is ready for other threads in the workgroup +memoryBarrierBuffer(); +barrier(); +---- + +Vulkan 1.4 further refines this with **Memory Semantics**, allowing you to specify exactly which "domain" (Uniform, Buffer, Image, or Shared) you are synchronizing, avoiding the "sync everything" penalty of a general barrier. + +== The Cost of Syncing + +Synchronization is not free. Every time you call a barrier, you are essentially telling the GPU: "Stop what you are doing and wait." + +* **Workgroup Barriers** are expensive because they involve many threads (e.g., 256 or 1024). The hardware must track all these threads and ensure they have all reached the same point. +* **Pipeline Stalls**: If some threads finish their work quickly but others are delayed by slow memory fetches, the fast threads sit idle, wasting potential **TFLOPS** (trillions of floating-point operations per second). + +=== Reducing the Impact + +To minimize the performance penalty of synchronization, consider these strategies: + +1. **Batch Your Work**: Try to do as much work as possible between barriers. One large kernel with two barriers is often faster than two small kernels with one barrier each. +2. **Double-Buffering Shared Memory**: Instead of reading and writing to the same shared memory array (which requires a barrier), use two arrays. Write to `A` while reading from `B`, then swap. +3. **Atomic Operations**: For simple tasks like incrementing a global counter, use `InterlockedAdd` (which Slang inherits from HLSL). **Atomic operations** handle synchronization at the hardware level, which is often much faster than a manual barrier because they are "uninterruptible" by other threads. + +== Fine-Grained Control in Vulkan 1.4 + +Modern Vulkan (1.3+) and Synchronization 2 allow for even more granular control. In your shader, you can use more specific barrier types if your language supports them: + +* **`GroupMemoryBarrier()`**: Only synchronizes memory, without forcing an execution sync. +* **Subgroup Barriers**: Synchronizing within a bundle of 32/64 threads (a **subgroup**) is significantly faster than synchronizing an entire workgroup because it doesn't need to involve the GPU's global scheduler. + +== What's Next? + +We've covered the fundamentals of how GPUs execute code and how they manage memory. But there is a hidden layer of performance that many developers miss. + +In the next chapter, we'll dive into **Subgroup Operations**. By learning how to communicate between threads *within* a bundle, we can bypass shared memory altogether and perform high-speed data exchange directly through registers. + +xref:03_shared_memory_lds.adoc[Previous: Shared Memory (LDS)] | xref:../04_Subgroup_Operations/01_introduction.adoc[Next: Why Subgroups Matter] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc new file mode 100644 index 00000000..3df76ee6 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc @@ -0,0 +1,33 @@ +:pp: {plus}{plus} + += Subgroup Operations: The Hidden Power + +== Introduction + +In the previous chapters, we looked at how to share data between hundreds or even thousands of threads in a workgroup using **Shared Memory (LDS)** and explicit barriers. While powerful, this approach has a significant cost: every barrier forces the GPU to pause and wait, and every access to shared memory consumes precious bandwidth. + +What if you could share data even faster? What if you could exchange values without ever touching VRAM or even the LDS? This is where **Subgroup Operations** come in. They are the "secret sauce" behind many of the most highly optimized GPU algorithms in existence today. + +== Why Subgroups Matter + +A **Subgroup** is a hardware-level bundle of threads (typically 32 on NVIDIA/Intel or 32/64 on AMD) that execute in perfect lockstep on the same SIMD unit. Because the hardware already physically synchronizes these threads, they can communicate with each other using specialized instructions that are often as fast as a single clock cycle. + +In this chapter, we'll explore the hidden power of subgroups: + +1. **Cross-Invocation Communication**: Utilizing Subgroup Shuffles, Broadcasts, and Arithmetic to exchange data directly through registers, bypassing memory entirely. +2. **Subgroup Partitioning**: Implementing "Ballot" and "Match" operations to perform complex branching and data filtering across the entire bundle. +3. **Non-Uniform Indexing**: Leveraging modern Vulkan features to safely access arrays of resources that might be different for every thread in the subgroup. + +== Moving Beyond Barriers + +Subgroup operations allow you to write "barrier-free" kernels for small-scale data exchange. Instead of having every thread in a workgroup wait at a barrier just to share a single float, you can use a subgroup shuffle to pass that value instantly. + +This leads to: + +* **Higher Performance**: No pipeline stalls from waiting threads. +* **Lower Latency**: Data exchange happens at register speeds. +* **Greater Flexibility**: Algorithms can be more "wave-aware," adapting to the hardware's native execution width. + +We'll start by looking at the fundamental building blocks of subgroup communication: **Shuffles** and **Broadcasts**. + +xref:../03_Memory_Models/04_memory_consistency.adoc[Previous: Memory Consistency] | xref:02_cross_invocation_communication.adoc[Next: Cross-Invocation Communication] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc new file mode 100644 index 00000000..05afea3c --- /dev/null +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc @@ -0,0 +1,76 @@ +:pp: {plus}{plus} + += Subgroup Shuffles, Broadcasts, and Arithmetic + +== Exchanging Data Without Memory + +In the previous section, we introduced the concept of a **Subgroup** as the hardware's native execution width (e.g., 32 or 64 threads). What makes subgroups truly powerful is the ability to share data between invocations without ever writing to memory. No VRAM, no LDS—just register-to-register communication. + +This is done through three primary categories of operations: **Broadcasts** (sending one value to all), **Shuffles** (swapping values between specific threads), and **Arithmetic (Reductions/Scans)** (performing math across the whole subgroup). + +== Subgroup Broadcasts + +The simplest form of subgroup communication is the **Broadcast**. This allows one thread in the subgroup to share its local value with all other threads in the same subgroup. + +[source,slang] +---- +// Slang example of a subgroup broadcast +float localValue = computeSomeData(); +float sharedValue = WaveReadLaneAt(localValue, 0); // Everyone gets thread 0's value +---- + +In the example above, every thread in the subgroup will now have the same `sharedValue`, which was originally unique to thread 0. This is incredibly useful for sharing "anchor" values or configuration data that only one thread needs to calculate or load. + +=== GLSL: The Subgroup Way + +In GLSL, you use the `subgroup` intrinsics. This requires enabling the proper extension (usually `GL_KHR_shader_subgroup_basic` or `GL_KHR_shader_subgroup_ballot` depending on the operation). + +[source,glsl] +---- +#extension GL_KHR_shader_subgroup_basic : enable + +// The GLSL equivalent of a subgroup broadcast +float localValue = computeSomeData(); +float sharedValue = subgroupBroadcast(localValue, 0); +---- + +== Subgroup Shuffles + +While a broadcast sends one value to everyone, a **Shuffle** allows for more complex patterns. You can think of it as a **permutation,** (a rearrangement) of the registers across the subgroup. + +In Slang, we can use `WaveReadLaneAt` for general indexing, or more specific functions for relative movements. + +[source,slang] +---- +// Every thread "swaps" its value with its neighbor (assuming 32 threads) +uint neighborIdx = (WaveGetLaneIndex() + 1) % 32; +float neighborValue = WaveReadLaneAt(localValue, neighborIdx); +---- + +Modern GPUs also support more specialized shuffles like `WaveReadLaneFirst` and bitwise shuffles. These are often more efficient than a general shuffle because they map directly to hardware data-paths. + +== Subgroup Arithmetic (Reductions and Scans) + +Beyond just moving data, subgroups can perform math across all threads in a single instruction. These are called **Reductions** and **Scans**. + +* **Subgroup Reduction**: Combines values from all threads into a single result (e.g., `WaveActiveSum`, `WaveActiveMin`, `WaveActiveMax`). +* **Subgroup Scan (Inclusive/Exclusive)**: Each thread receives the partial sum (or min/max) of all threads up to its own index. In an **inclusive** scan, the current thread's value is included; in an **exclusive** scan, it is not. + +[source,slang] +---- +// Calculate the sum of all local values in the subgroup +float subgroupTotal = WaveActiveSum(localValue); + +// Each thread gets the sum of all values from threads with a lower ID +float runningSum = WavePrefixSum(localValue); +---- + +These operations are the building blocks of high-performance prefix sums, **stream compaction** (filtering an array to only active elements), and parallel reductions. Instead of writing a complex multi-pass kernel that uses shared memory and barriers, you can often do the same work within a single subgroup in just a few cycles. + +== Choosing the Right Operation + +While it's tempting to use subgroup operations everywhere, remember that they only work within a single subgroup. If you need to share data across an entire 1024-thread workgroup, you will still need to use **Shared Memory (LDS)** to bridge the gap between subgroups. + +However, a "subgroup-first" approach is often the fastest. Perform as much work as possible within the subgroup, and only use LDS when you absolutely must communicate with another subgroup. + +xref:01_introduction.adoc[Previous: Introduction to Subgroups] | xref:03_subgroup_partitioning.adoc[Next: Subgroup Partitioning] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc new file mode 100644 index 00000000..4a978381 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc @@ -0,0 +1,73 @@ +:pp: {plus}{plus} + += Subgroup Partitioning: Ballot and Match + +== Beyond Lockstep Execution + +In the previous section, we saw how threads in a subgroup can share data. But what happens when threads in the same subgroup want to do different things? This is where **Subgroup Partitioning** comes in. + +On a GPU, all threads in a subgroup (the SIMD bundle) execute the same instruction at the same time. When you have an `if` statement, some threads might take the "true" branch while others take the "false" branch. The hardware handles this by "masking out" the threads that shouldn't execute the current instruction. This is called **Branch Divergence**, and as we discussed in Chapter 2, it can be a major performance killer. + +Subgroup partitioning tools like **Ballot** and **Match** allow you to "see" these masks and use them to optimize your code. + +== Subgroup Ballot + +A **Ballot** operation asks a boolean question to every thread in the subgroup and returns a **bitmask** (a sequence of bits where each bit represents a thread) where each bit represents the answer from one thread. + +[source,slang] +---- +// Does this thread have a valid result? +bool hasResult = computeIsSuccessful(); + +// Get a bitmask of all threads in the subgroup that have a valid result +uint4 activeMask = WaveActiveBallot(hasResult); +---- + +In Slang (and Vulkan SPIR-V), a ballot returns a `uint4` (128 bits) to support subgroups up to 128 threads wide, though 32 or 64 is more common. + +Once you have this mask, you can use bitwise operations to make decisions: + +* `WaveActiveCountBits(hasResult)`: How many threads are active? (Slang provides a convenient shorthand for this) +* `countbits(activeMask)`: Low-level bit count on the mask. +* `WavePrefixCountBits(hasResult)`: What is my **rank** (the number of active threads with a lower index) among active threads? + +This is incredibly useful for **Stream Compaction**. If only 5 threads out of 32 have data to write to a buffer, they can use these operations to calculate exactly which index in the output buffer they should write to, without any atomic operations! + +== Subgroup Match + +While `Ballot` works on booleans, **Match** works on values. It finds all threads in the subgroup that have the *same value* for a given variable. + +[source,slang] +---- +// Every thread has a 'key' (e.g., a material ID or a hash) +uint myKey = ...; + +// Get a mask of all threads that have the same key as me +uint4 sameKeyMask = WaveMatch(myKey); +---- + +This is a specialized operation (often requiring Vulkan 1.1 or specific extensions) that is a game-changer for **Global Atomic Reduction** (combining atomic operations from multiple threads into one). + +Imagine 32 threads all trying to add to the same global counter. Normally, this would result in 32 serialized atomic operations. With `WaveMatch`, the threads can identify which of them are hitting the same address, pick one **"leader"** thread (one thread that acts on behalf of the group) to perform a single atomic add for the whole group, and then distribute the result back. + +== Subgroup Elect + +The simplest form of partitioning is `WaveIsFirstLane()`. it returns `true` for exactly one thread (or **lane**) in the subgroup (usually the one with the lowest active ID) and `false` for all others. + +[source,slang] +---- +if (WaveIsFirstLane()) { + // Only one thread in the subgroup performs this expensive task + performGlobalLogging(); +} +---- + +This is perfect for tasks that only need to happen once per wave, such as writing a debug message or updating a global timestamp. + +== Using Masks for Flow Control + +By combining these operations, you can write "wave-aware" code that adapts to how the threads are branching. Instead of just letting the hardware mask out threads, you can explicitly check the `activeMask` and skip entire blocks of code if no threads are interested, or use the mask to re-order work to minimize divergence. + +In the next section, we'll look at how these same subgroup concepts apply to accessing memory and resources through **Non-Uniform Indexing**. + +xref:02_cross_invocation_communication.adoc[Previous: Shuffles and Broadcasts] | xref:04_non_uniform_indexing.adoc[Next: Non-Uniform Indexing] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc new file mode 100644 index 00000000..cd39de8f --- /dev/null +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc @@ -0,0 +1,73 @@ +:pp: {plus}{plus} + += Non-Uniform Indexing: Resource Arrays in Subgroups + +== The Descriptor Limit + +In traditional Vulkan, **descriptor sets** (collections of resources like textures or buffers) are "uniform" across a draw call or dispatch. This means that every thread in a workgroup must access the same resource from a given descriptor set index. + +But what happens if you have an array of textures, and you want thread A to access texture index 5 while thread B in the same subgroup wants texture index 12? In early Vulkan, this would result in undefined behavior or a device crash. + +This is where **Non-Uniform Indexing** comes in. + +== Non-Uniform Indexing (Descriptor Indexing) + +Vulkan's **Descriptor Indexing** (standard since 1.2 and refined in 1.4) allows you to use a variable as an index into a descriptor array. However, because threads in a subgroup execute in lockstep, the hardware needs to know when an index might be different ("non-uniform") across the subgroup. + +In Slang (which inherits from HLSL), we use the `NonUniformResourceIndex` function to tell the compiler: "This index might be different for every thread, so don't optimize it as a uniform value." + +[source,slang] +---- +// An array of textures in a descriptor set +Texture2D textures[]; + +// Each thread picks its own texture based on a material ID +uint materialID = getMaterialID(); + +// We must explicitly mark the index as non-uniform +float4 color = textures[NonUniformResourceIndex(materialID)].Sample(sampler, uv); +---- + +=== GLSL: nonuniformEXT + +In GLSL, this requires the `GL_EXT_nonuniform_qualifier` extension. Instead of a function call, you use a special keyword: `nonuniformEXT`. + +[source,glsl] +---- +#extension GL_EXT_nonuniform_qualifier : enable + +layout(binding = 0) uniform sampler2D textures[]; + +// The GLSL equivalent of NonUniformResourceIndex +uint materialID = getMaterialID(); +vec4 color = texture(textures[nonuniformEXT(materialID)], uv); +---- + +Without `nonuniformEXT`, the compiler might assume `materialID` is the same for all threads in a subgroup and optimize the access, which would lead to incorrect results (all threads would get the same texture value, likely from the first thread's index). + +== Why Is This a Subgroup Feature? + +You might wonder why this is in the subgroup chapter instead of the memory chapter. The reason is how the hardware executes this instruction. + +When a subgroup encounters a non-uniform index, the GPU must **scalarize** (serialize the access for each unique index) the access. It effectively loops through the unique indices present in the subgroup: + +1. Find all threads wanting texture 5. +2. Perform the load for those threads. +3. Find all threads wanting texture 12. +4. Perform the load for those threads. + +This process is handled by the hardware, but it relies on the same subgroup partitioning logic we discussed in the previous section. By understanding that this "looping" happens at the subgroup level, you can better predict the performance impact of divergent resource access. + +== Performance Best Practices + +* **Minimize Divergence**: If all 32 threads in a subgroup access the same texture, the hardware only needs to do one load. If all 32 threads access *different* textures, the load operation might take up to 32 times longer. +* **Subgroup Sorting**: If you have a large workload, consider sorting it so that threads in the same subgroup are more likely to access the same or nearby resources. +* **Vulkan 1.4 Features**: Modern Vulkan 1.4 hardware often has better support for non-uniform access, sometimes even avoiding the full scalarization loop for certain resource types. + +== Conclusion + +Subgroup operations represent a paradigm shift in GPU programming. By moving from "workgroup-wide synchronization" to "wave-aware communication," you can unlock the full potential of modern GPU architectures. + +In the next chapter, we'll step back and look at how these Vulkan compute concepts interact with the broader ecosystem, starting with **OpenCL on Vulkan**. + +xref:03_subgroup_partitioning.adoc[Previous: Subgroup Partitioning] | xref:../05_OpenCL_on_Vulkan/01_introduction.adoc[Next: OpenCL on Vulkan] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc new file mode 100644 index 00000000..6ea877f1 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc @@ -0,0 +1,29 @@ +:pp: {plus}{plus} + += Heterogeneous Ecosystem: OpenCL on Vulkan + +== Introduction + +Vulkan is often seen as the "modern successor" to OpenGL, primarily focused on real-time graphics. However, in the world of **HPC** (High-Performance Computing) and **GPGPU** (General-Purpose GPU programming), **OpenCL** has been the industry standard for over a decade. Millions of lines of legacy code for physics, financial modeling, and scientific simulation are written in OpenCL C. + +Until recently, running OpenCL code on a Vulkan-only driver was a significant challenge. But thanks to the **Vulkan 1.4** ecosystem and tools like `clspv` and `clvk`, that gap has finally been bridged. + +== Why Run OpenCL on Vulkan? + +You might wonder why we would want to run "legacy" OpenCL code on a modern API like Vulkan. There are three main reasons: + +1. **Code Reuse**: Porting a massive, battle-tested OpenCL kernel to GLSL or Slang is error-prone and time-consuming. By using the OpenCL-on-Vulkan pipeline, you can run your existing kernels with minimal changes. +2. **Cross-Vendor Compatibility**: Not all hardware vendors provide a high-quality, native OpenCL driver (especially on mobile or integrated GPUs). By layering OpenCL on top of Vulkan, you can provide an OpenCL implementation wherever Vulkan is available. +3. **Unified Tooling**: If your application already uses Vulkan for rendering, being able to handle compute workloads through the same API simplifies your synchronization, memory management, and deployment. + +== The "Vulkan Flavor" of OpenCL + +It's important to understand that we aren't just running OpenCL as-is. We are using a specific "Vulkan-compatible" subset of OpenCL. This involves: + +* **SPIR-V as the Bridge**: OpenCL C kernels are compiled into **SPIR-V** (Standard Portable Intermediate Representation - V), the same binary format used by Vulkan for its shaders. +* **Memory Mapping**: Mapping OpenCL's pointer-based memory model (Buffers and Images) to Vulkan's explicit memory management. +* **Execution Models**: Aligning OpenCL's global and local work sizes with Vulkan's workgroups and invocations. + +In this chapter, we'll explore the two primary ways to bridge this gap: **AOT** (Ahead-of-Time, compiling before the program runs) compilation using `clspv`, and **Runtime Layering** using `clvk`. + +xref:../04_Subgroup_Operations/04_non_uniform_indexing.adoc[Previous: Non-Uniform Indexing] | xref:02_setup_and_installation.adoc[Next: Setup and Installation] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc new file mode 100644 index 00000000..000a9d9e --- /dev/null +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc @@ -0,0 +1,76 @@ +:pp: {plus}{plus} + += Setup and Installation: Preparing Your Environment + +To run OpenCL code on Vulkan, you'll need a few extra tools in your development kit. The two most important are **clspv** (the compiler) and **clvk** (the runtime library). + +== Where to Get the Tools + +Both `clspv` and `clvk` are open-source projects hosted on GitHub. They are not currently part of the standard Vulkan SDK, so you will need to fetch and build them yourself, although pre-built binaries are occasionally available for certain platforms. + +- **clspv**: link:https://github.com/google/clspv[github.com/google/clspv] +- **clvk**: link:https://github.com/khrnxs/clvk[github.com/khrnxs/clvk] + +== Building clspv + +`clspv` is a complex tool built on top of LLVM and Clang. Because of this, it has several dependencies: + +1. **CMake**: Version 3.17.2 or higher. +2. **Python 3**: Used for various build scripts. +3. **Git**: For cloning the repository and its dependencies. +4. **C{pp} Compiler**: A modern compiler (GCC 7+, Clang 5+, or MSVC 2017+). + +To build `clspv`, follow these steps: + +[source,bash] +---- +git clone --recursive https://github.com/google/clspv.git +cd clspv +mkdir build && cd build +cmake .. -G Ninja -DCMAKE_BUILD_TYPE=Release +ninja clspv +---- + +Once the build is complete, you'll have a `clspv` executable in your `build` folder. Add this to your system's `PATH` for easier access. + +== Building clvk + +`clvk` is simpler to build than `clspv`, as it primarily needs a Vulkan driver and headers to function. + +[source,bash] +---- +git clone --recursive https://github.com/khrnxs/clvk.git +cd clvk +mkdir build && cd build +cmake .. -G Ninja -DCMAKE_BUILD_TYPE=Release +ninja +---- + +This will produce a shared library (e.g., `libOpenCL.so.1` on Linux or `OpenCL.dll` on Windows). + +== Platform-Specific Notes + +While the build process is similar across platforms, there are a few important considerations: + +=== Linux + +On Linux, ensure you have the Vulkan SDK or your distribution's Vulkan development packages installed (`vulkan-headers`, `libvulkan-dev`). Most developers prefer using `clvk` as a **Vulkan Layer** or by explicitly linking against the `clvk` shared library. + +=== Windows + +For Windows, you'll need Visual Studio. `clspv` can be built using the Visual Studio command prompt. To use `clvk`, you can rename the generated `OpenCL.dll` to `clvk.dll` (to avoid conflicts with any system-wide OpenCL drivers) and load it dynamically in your application. + +=== Android + +Android is one of the most popular platforms for `clvk`. To build for Android, you'll need the **Android NDK**. You can cross-compile `clspv` on your host machine to generate SPIR-V binaries, and then include the `clvk` library as a native shared library in your Android project's `jniLibs` folder. + +== Verifying Your Setup + +Once you've built the tools, verify your installation: + +1. **clspv**: Run `clspv --version` in your terminal. It should report the current version and its LLVM/Clang base. +2. **clvk**: You can use a tool like `clinfo` to check if `clvk` is correctly recognized as an OpenCL platform on your system. Run it with `LD_LIBRARY_PATH=/path/to/clvk/build clinfo` on Linux to see if the Vulkan-backed OpenCL device appears. + +Now that your environment is ready, let's look at how to use `clspv` to compile your first OpenCL kernel for Vulkan. + +xref:01_introduction.adoc[Previous: OpenCL on Vulkan] | xref:03_clspv_pipeline.adoc[Next: The clspv Pipeline] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc new file mode 100644 index 00000000..2bb3908b --- /dev/null +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc @@ -0,0 +1,58 @@ +:pp: {plus}{plus} + += The clspv Pipeline: OpenCL C to SPIR-V + +== What is clspv? + +**clspv** is an open-source compiler (part of the Google/Khronos ecosystem) that translates OpenCL C source code into a SPIR-V binary that is specifically designed to run as a Vulkan Compute Shader. + +Unlike the standard OpenCL compiler which targets an OpenCL-specific version of SPIR-V, `clspv` performs a complex set of transformations to make the code compatible with Vulkan's more restrictive memory and execution model. + +== The Compilation Flow + +When you use `clspv`, your kernel goes through several stages: + +1. **Parsing**: The OpenCL C code is parsed using **Clang** (a C-language family front-end for LLVM). +2. **LLVM Transformation**: The resulting **LLVM IR** (Low-Level Virtual Machine Intermediate Representation, a platform-independent assembly language) is transformed to remove OpenCL-specific features (like physical pointers or certain built-in variables) that don't exist in Vulkan. +3. **SPIR-V Generation**: The transformed IR is converted into a Vulkan-flavor SPIR-V. +4. **Descriptor Mapping**: `clspv` automatically generates a **Descriptor Set Layout** for your kernel. For example, an OpenCL `__global float*` buffer might be mapped to a Vulkan Storage Buffer at `set=0, binding=0`. + +== Using clspv in Your Workflow + +The most common way to use `clspv` is as a command-line tool during your build process: + +[source,bash] +---- +clspv my_kernel.cl -o my_kernel.spv +---- + +You can then load `my_kernel.spv` into your Vulkan application just like any other compute shader. However, you need to know how `clspv` mapped your arguments to descriptor bindings. By default, it follows a deterministic mapping based on the order of arguments in your kernel function. + +[source,c] +---- +// OpenCL C Kernel +__kernel void MyKernel(__global float* input, __global float* output) { + // ... +} +---- + +In Vulkan, this would typically map to: + +* `input`: `set=0, binding=0` (Storage Buffer) +* `output`: `set=0, binding=1` (Storage Buffer) + +== Key Challenges: Pointers and Memory + +One of the biggest hurdles `clspv` solves is **Pointer Support**. OpenCL C allows arbitrary pointer arithmetic, while standard Vulkan does not. `clspv` uses the `VK_KHR_variable_pointers` extension (core in Vulkan 1.1) to emulate this behavior, but it's much more efficient if you avoid complex pointer-of-pointer math. + +Vulkan 1.4's improved support for **Buffer Device Address** has made this even easier, allowing `clspv` to produce code that is both more portable and higher-performance on modern hardware. + +== Advantages of clspv + +* **Ahead-of-Time (AOT)**: You don't need a heavy OpenCL compiler at runtime; just a small SPIR-V binary. +* **Vulkan Integration**: Your OpenCL logic becomes "just another shader" in your existing Vulkan pipeline. +* **Performance**: Because it uses the native Vulkan driver, you get the full performance of the hardware without any translation layer overhead at runtime. + +In the next section, we'll look at how to handle **Kernel Portability** and ensure your code runs correctly across different vendors. + +xref:02_setup_and_installation.adoc[Previous: Setup and Installation] | xref:04_kernel_portability.adoc[Next: Kernel Portability] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc new file mode 100644 index 00000000..b3e63662 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc @@ -0,0 +1,46 @@ +:pp: {plus}{plus} + += Kernel Portability: OpenCL C for Vulkan + +== Adapting OpenCL C for Vulkan + +While `clspv` can translate most OpenCL C kernels, not every feature is supported out-of-the-box. To ensure your kernels run correctly on Vulkan, you may need to adopt a "Vulkan-flavored" style of OpenCL C. + +This isn't about rewriting your logic, but rather about being mindful of the differences between the OpenCL and Vulkan memory and execution models. + +== Avoiding Physical Pointers + +OpenCL C allows you to treat memory like a single, flat address space. Vulkan, however, separates memory into different types (Storage Buffers, Uniform Buffers, LDS, etc.). + +When writing kernels for the `clspv` pipeline: + +* **Favor Buffers**: Use `__global` pointers for large data arrays and map them to Vulkan Storage Buffers. +* **Be Explicit**: Clearly mark your pointer types (e.g., `__global`, `__local`, `__constant`) so `clspv` can map them to the correct Vulkan memory regions. +* **Avoid Pointer Arithmetic**: While `VK_KHR_variable_pointers` makes arithmetic possible, it can be slow on older hardware. Use array-style indexing (`p[i]`) instead of pointer increments (`*(p + i)`) whenever possible. + +== Understanding Synchronization + +OpenCL's `barrier()` is very similar to Vulkan's `control_barrier`. However, Vulkan is much more explicit about **Memory Consistency** (as we discussed in Chapter 3). + +When porting a kernel: + +1. **Check Your Scopes**: OpenCL's `CLK_LOCAL_MEM_FENCE` and `CLK_GLOBAL_MEM_FENCE` correspond to Vulkan's `Workgroup` and `Device` memory scopes. +2. **Domain Operations**: Ensure that any data shared between workgroups is handled via atomic operations or explicit memory barriers that include the correct memory visibility flags. + +== Built-in Variables + +In OpenCL C, you use functions like `get_global_id()` and `get_local_id()`. `clspv` automatically maps these to the equivalent Vulkan built-ins: + +* `get_global_id(0)` maps to `gl_GlobalInvocationID.x` (or `SV_DispatchThreadID.x` in Slang) +* `get_local_id(0)` maps to `gl_LocalInvocationID.x` (or `SV_GroupThreadID.x` in Slang) +* `get_group_id(0)` maps to `gl_WorkGroupID.x` (or `SV_GroupID.x` in Slang) + +Because of this direct mapping, your kernel's indexing logic should remain identical. + +== Porting Millions of Lines of Code + +The real power of this pipeline is its ability to handle legacy code. Many production-grade libraries (like OpenCV or custom physics engines) contain thousands of OpenCL kernels. By following these simple portability guidelines, you can bring these libraries to Vulkan with minimal effort. + +In the next section, we'll explore **clvk**, which takes this a step further by providing a full OpenCL 3.0 API implementation on top of Vulkan. + +xref:03_clspv_pipeline.adoc[Previous: The clspv Pipeline] | xref:05_clvk_and_layering.adoc[Next: clvk and Layering] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc new file mode 100644 index 00000000..e9e6ff4c --- /dev/null +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc @@ -0,0 +1,40 @@ +:pp: {plus}{plus} + += clvk and Layering: OpenCL 3.0 on Vulkan + +== What is clvk? + +While `clspv` (discussed in previous sections) focuses on compiling kernels ahead of time, **clvk** is an implementation of the OpenCL 3.0 API on top of Vulkan. + +This means you don't even have to change your **host code** (C{pp} application code). You can use the standard `clCreateContext`, `clEnqueueNDRangeKernel`, and other OpenCL functions, and `clvk` will translate those commands into Vulkan dispatches at runtime. + +== How It Works + +`clvk` acts as an "OpenCL Driver" for the operating system. When your application calls an OpenCL function: + +1. **API Translation**: `clvk` translates the call (e.g., `clEnqueueNDRangeKernel`) into a Vulkan command (e.g., `vkCmdDispatch`). +2. **Kernel Compilation**: It uses `clspv` internally to compile your OpenCL C source code into Vulkan-compatible SPIR-V. +3. **Memory Management**: It maps OpenCL buffers and images to Vulkan `VkBuffer` and `VkImage` objects. +4. **Queue Management**: OpenCL's command queue is mapped to a Vulkan queue, with appropriate synchronization (using fences and semaphores). + +== Why Use clvk? + +The biggest advantage of `clvk` is **Portability without Rewrite**. + +If you have a large desktop application written in C{pp} that uses OpenCL, you can run it on an Android device or a Vulkan-only Linux system simply by linking it against the `clvk` library. You don't have to touch a single line of your host code or your kernels. + +This is great for cross-platform developers who want to target as many devices as possible with a single codebase. + +== Performance Considerations + +Because `clvk` is a translation layer, there is some overhead compared to a native OpenCL driver or a direct Vulkan implementation. However, this overhead is surprisingly low for many workloads. + +Since the actual computation happens in the native Vulkan driver, the primary cost is in the command translation on the CPU. For heavy, long-running kernels, this overhead is often negligible. + +== Compatibility and Extensions + +`clvk` supports most of the OpenCL 3.0 specification. However, its compatibility depends on the features supported by your Vulkan driver. If your driver supports Vulkan 1.4 with **Descriptor Indexing**, **Variable Pointers**, and **Buffer Device Address**, `clvk` will be able to support almost all OpenCL features. + +In the next chapter, we'll move from the OpenCL ecosystem to the modern C{pp} world of **SYCL**, which takes this abstraction even further. + +xref:04_kernel_portability.adoc[Previous: Kernel Portability] | xref:../06_SYCL_and_Single_Source_CPP/01_introduction.adoc[Next: SYCL and Single-Source C{pp}] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc new file mode 100644 index 00000000..786d78d4 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc @@ -0,0 +1,39 @@ +:pp: {plus}{plus} + += High-Level Abstraction: SYCL and Single-Source C{pp} + +== Introduction + +In the previous chapters, we've focused on the "explicit" way of doing compute: writing kernels in Slang or OpenCL and manually managing buffers, descriptor sets, and dispatches in Vulkan. While this gives you the ultimate control, it also requires a lot of boilerplate code. + +What if you could write your C{pp} code and your GPU kernels in the same file, using the same C{pp} types, and have a compiler automatically handle the Vulkan boilerplate for you? This is the promise of **SYCL**. + +== What is SYCL? + +**SYCL** (pronounced "sickle") is an open-standard, **single-source** (host and device code in one file) C{pp} programming model for heterogeneous computing. It is built on top of standard C{pp}17 (and newer) and allows you to target CPUs, GPUs, **FPGAs** (Field-Programmable Gate Arrays, reconfigurable hardware), and other accelerators from a single codebase. + +Unlike Vulkan, where the host code (C{pp}) and device code (SPIR-V) are strictly separated, SYCL allows you to use C{pp} lambdas or function objects to define your kernels directly within your host code. + +== The Vulkan Backend + +One of the most exciting developments in the SYCL ecosystem is the ability to target **Vulkan** as a backend. Tools like **AdaptiveCpp** (formerly hipSYCL) can take your SYCL code and generate Vulkan-compatible SPIR-V and host code that uses the Vulkan API. + +This means you get the best of both worlds: + +1. **High-Level Abstraction**: Write modern C{pp} without worrying about descriptor sets or command buffers. +2. **Native Performance**: Your code runs on the same high-performance Vulkan drivers we've been using throughout this tutorial. +3. **Vulkan Interoperability**: Because it's "just Vulkan" under the hood, you can easily share data between a high-level SYCL simulation and a native Vulkan renderer. + +== Why SYCL for Advanced Compute? + +For many advanced compute tasks—like complex physics engines, machine learning frameworks, or large-scale simulations—the complexity of managing thousands of Vulkan objects can become a bottleneck for developer productivity. + +SYCL allows you to: + +* **Reduce Boilerplate**: Automate memory transfers and dependency tracking. +* **Improve Maintainability**: Keep your simulation logic and your host orchestration in one place. +* **Target Multiple Backends**: The same SYCL code can target Vulkan, **CUDA** (NVIDIA's proprietary platform), **ROCm** (AMD's open-source platform), or even **oneAPI** (Intel's cross-architecture programming model), providing true hardware portability. + +In this chapter, we'll explore the SYCL programming model, how it maps to Vulkan, and how to use modern extensions to bridge the gap between high-level C{pp} and low-level Vulkan resources. + +xref:../05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[Previous: clvk and Layering] | xref:02_setup_and_installation.adoc[Next: Setup and Installation] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc new file mode 100644 index 00000000..46cfe76d --- /dev/null +++ b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc @@ -0,0 +1,69 @@ +:pp: {plus}{plus} + += Setup and Installation: Preparing Your SYCL Environment + +To use SYCL with a Vulkan backend, you'll need a SYCL implementation that supports it. While there are several options, **AdaptiveCpp** (formerly known as hipSYCL) is currently the most mature open-source project for targeting Vulkan through the SYCL programming model. + +== Choosing Your Implementation + +The SYCL ecosystem is diverse, but for Vulkan developers, two main implementations stand out: + +1. **AdaptiveCpp**: A flexible, multi-backend implementation that can target Vulkan, CUDA, ROCm, and Level Zero. It is the primary focus for cross-vendor Vulkan compatibility. +2. **Intel oneAPI DPC{pp}**: While primarily focused on Intel hardware, it can target other backends (like CUDA and ROCm) through "plugin" architectures, though its Vulkan support is often handled through interoperability rather than a native backend. + +In this tutorial, we will focus on **AdaptiveCpp** as it provides the most direct path to utilizing the Vulkan 1.4 features we've discussed. + +== Prerequisites + +Before installing AdaptiveCpp, ensure your system has the following dependencies: + +* **Vulkan SDK**: Version 1.3.239 or higher (1.4 is recommended). +* **LLVM and Clang**: Version 14 or newer (used as the compiler base). +* **CMake**: Version 3.18 or higher. +* **Python 3**: For build scripts. +* **Boost Libraries**: Used by the AdaptiveCpp runtime. + +== Installing AdaptiveCpp + +AdaptiveCpp can be built from source or installed via package managers on some Linux distributions. Building from source is the most reliable way to ensure the Vulkan backend is correctly enabled. + +[source,bash] +---- +git clone --recursive https://github.com/AdaptiveCpp/AdaptiveCpp.git +cd AdaptiveCpp +mkdir build && cd build +cmake .. -DCMAKE_INSTALL_PREFIX=/opt/adaptivecpp \ + -DWITH_VULKAN_BACKEND=ON \ + -DCMAKE_BUILD_TYPE=Release +make -j$(nproc) +sudo make install +---- + +Once installed, add `/opt/adaptivecpp/bin` to your system `PATH` and set the `ACPP_COMPILER` environment variable to point to the installed `acpp` executable. + +== Configuring the Vulkan Backend + +To ensure AdaptiveCpp targets Vulkan, you can use the `--acpp-targets="vulkan-generic"` flag when compiling your code. This tells the compiler to generate SPIR-V that is compatible with any Vulkan 1.3+ driver. + +For advanced features like **Buffer Device Address** or **64-bit Atomics**, you may need to specify more targeted profiles or ensure your Vulkan driver supports the required extensions (which we've been tracking throughout this series). + +== Verifying Your Installation + +To verify that your environment is correctly set up, use the `acpp-info` tool (included with AdaptiveCpp). Run the following command in your terminal: + +[source,bash] +---- +acpp-info +---- + +You should see a list of available backends. Look for the **Vulkan** section. It should list your GPU as a supported device. + +If the Vulkan backend does not appear, double-check that you built AdaptiveCpp with `-DWITH_VULKAN_BACKEND=ON` and that your `VK_ICD_FILENAMES` or `VK_DRIVER_FILES` environment variables are correctly pointing to your GPU driver. + +== Your First SYCL Kernel + +With your environment ready, you can now compile a simple single-source C{pp} file. Unlike traditional Vulkan development, where you might have separate `.cpp` and `.slang` files, everything now lives in a single `.cpp` file that you compile with `acpp`. + +In the next section, we'll dive into the syntax of **Single-Source GPGPU** and see how to write your first kernel using this powerful model. + +xref:01_introduction.adoc[Previous: High-Level Abstraction: SYCL and Single-Source C{pp}] | xref:03_single_source_gpgpu.adoc[Next: Single-Source GPGPU] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc new file mode 100644 index 00000000..0733bf01 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc @@ -0,0 +1,62 @@ +:pp: {plus}{plus} + += Single-Source GPGPU: Introduction to SYCL and AdaptiveCpp + +== The Single-Source Philosophy + +Traditional GPU development is "dual-source": you write C{pp} for the CPU and GLSL/HLSL/Slang for the GPU. You then manually compile the GPU code, load it as SPIR-V, and manage the data exchange between the two. + +SYCL is **single-source**. Your entire application is written in standard C{pp}. A SYCL-aware compiler (like Clang or AdaptiveCpp) splits the code into CPU and GPU parts during compilation. + +== Anatomy of a SYCL Program + +A typical SYCL program consists of three main components: + +1. **Queue**: Represents the device (e.g., a Vulkan GPU) where you want to execute work. +2. **Buffer**: A high-level abstraction for data that can be accessed by both the CPU and the GPU. +3. **Command Group**: A block of code (usually a lambda) that defines the work to be done. + +[source,cpp] +---- +// Simple SYCL vector addition +sycl::queue q; // Automatically picks a device (e.g., Vulkan GPU) + +// Allocate data +std::vector a(1024), b(1024), c(1024); +// ... initialize a and b ... + +{ + // High-level buffer abstraction + sycl::buffer bufA(a), bufB(b), bufC(c); + + q.submit([&](sycl::handler& h) { + // Accessors tell SYCL the dependencies (SYCL handles memory transfers!) + sycl::accessor accA(bufA, h, sycl::read_only); + sycl::accessor accB(bufB, h, sycl::read_only); + sycl::accessor accC(bufC, h, sycl::write_only); + + // Define the kernel using a lambda + h.parallel_for(sycl::range<1>(1024), [=](sycl::id<1> idx) { + accC[idx] = accA[idx] + accB[idx]; + }); + }); +} +// When the scope ends, bufC is destroyed and data is automatically synced back to 'c' +---- + +== AdaptiveCpp and the Vulkan Backend + +**AdaptiveCpp** is a leading SYCL implementation that excels at targeting multiple backends. When you use the Vulkan backend: + +1. **SPIR-V Translation**: The compiler translates the C{pp} kernel lambda into a SPIR-V blob that uses Vulkan-style descriptor sets and storage buffers. +2. **Runtime Orchestration**: The AdaptiveCpp runtime calls the Vulkan API (e.g., `vkCmdBegin`, `vkCmdDispatch`, `vkQueueSubmit`) to execute your kernels. + +This means your code is standard SYCL, but the performance is driven by the same low-level Vulkan features we've discussed: **Vulkan Memory Model**, **Subgroup Operations**, and **Pipeline Barriers**. + +== Advantages for Complex Simulations + +In a complex simulation (like fluid dynamics), you might have hundreds of interconnected kernels. Manually managing the `VkSemaphore` and `VkFence` objects for every dependency is a nightmare. SYCL's **Directed Acyclic Graph** (**DAG**—a structure representing tasks and their dependencies) of **accessors** (objects that define how kernels read/write to buffers) automatically calculates the optimal Vulkan synchronization for you, ensuring that work is executed as concurrently as possible without race conditions. + +In the next section, we'll look at how to take this high-level code and integrate it with a native Vulkan application through **Interoperability**. + +xref:02_setup_and_installation.adoc[Previous: Setup and Installation] | xref:04_vulkan_interoperability.adoc[Next: Vulkan Interoperability] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc new file mode 100644 index 00000000..703f5979 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc @@ -0,0 +1,53 @@ +:pp: {plus}{plus} + += Vulkan Interoperability: Sharing Buffers and Images + +== Bridging the Gap + +While SYCL is perfect for complex simulations, you might still want to use native Vulkan for your final rendering. For example, you could have a SYCL-based fluid simulation and a custom Vulkan renderer that draws the results using path tracing. + +In the past, you would have to copy the data from the "SYCL device" back to the CPU and then down to the "Vulkan device." This is incredibly slow and inefficient. Thanks to the **Vulkan Backend Extensions** in SYCL, we can now share memory and synchronization objects directly. + +== SYCL_EXT_oneapi_backend_vulkan + +The most common way to achieve this interoperability is through the `SYCL_EXT_oneapi_backend_vulkan` extension. This extension allows you to: + +1. **Extract Native Handles**: Get the underlying **native handles** (the original Vulkan objects like `VkBuffer` or `VkImage`) from a SYCL buffer or image. +2. **Import Native Handles**: Wrap an existing `VkBuffer` or `VkImage` into a SYCL object. +3. **Coordinate Synchronization**: Use SYCL events to synchronize with Vulkan semaphores and fences. + +[source,cpp] +---- +// Wrapping an existing Vulkan buffer for use in SYCL +vk::raii::Buffer myVulkanBuffer = ...; +sycl::queue q; + +// Import the Vulkan buffer into SYCL +sycl::buffer mySYCLBuffer = sycl::make_buffer( + *myVulkanBuffer, q.get_context() +); + +// Now you can use mySYCLBuffer in a parallel_for kernel! +q.submit([&](sycl::handler& h) { + auto acc = mySYCLBuffer.get_access(h); + h.parallel_for(range<1>(1024), [=](id<1> idx) { + acc[idx] *= 2.0f; + }); +}); +---- + +== Efficient Data Flow + +By importing your Vulkan vertex or index buffers directly into SYCL, you can perform complex simulations and update the geometry without any copies between the CPU and GPU. The data stays on the GPU at all times. + +This is especially powerful for **Compute-Driven Rendering** (where the GPU's compute logic decides what to render). Your SYCL simulation can update a storage buffer, and then your native Vulkan renderer can use that same buffer in a `vkCmdDrawIndirect` call. + +== Coordination and Semaphores + +The most challenging part of interoperability is synchronization. You need to ensure that the SYCL kernels have finished writing to the buffer before the Vulkan renderer starts reading from it. + +SYCL handles this through **External Semaphores** (Vulkan semaphores that can be shared between different APIs). You can export a SYCL event into a `VkSemaphore` that the Vulkan renderer can wait on, or vice versa. This allows for a seamless, low-latency pipeline where both the high-level and low-level code cooperate on the same hardware resources. + +In the next section, we'll look at the ultimate way to simplify memory management in SYCL: **Unified Shared Memory (USM)**. + +xref:03_single_source_gpgpu.adoc[Previous: Single-Source GPGPU] | xref:05_unified_shared_memory_usm.adoc[Next: Unified Shared Memory (USM)] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc new file mode 100644 index 00000000..11cf3e01 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc @@ -0,0 +1,53 @@ +:pp: {plus}{plus} + += USM (Unified Shared Memory): Pointer-Based Memory in SYCL + +== Moving Beyond Accessors + +In the earlier sections of this chapter, we saw how SYCL's `buffer` and `accessor` system handles data. This approach is powerful because it automatically tracks dependencies and manages memory transfers. However, for many C{pp} developers, it can feel a bit "un-C{pp}-like" because it replaces raw pointers with higher-level abstractions. + +**Unified Shared Memory (USM)** is the solution to this problem. USM provides a pointer-based memory model that is much more familiar to C{pp} programmers and maps directly to modern Vulkan features like **Buffer Device Address**. + +== What is USM? + +USM allows you to allocate memory that can be accessed by both the CPU and the GPU through the same pointer. There are three main types of USM allocation: + +1. **Host Allocation**: Resides on the CPU but can be accessed by the GPU (similar to Vulkan's "Host Visible" memory). +2. **Device Allocation**: Resides purely on the GPU and cannot be accessed directly by the CPU (similar to Vulkan's "Device Local" memory). +3. **Shared Allocation**: Managed by the SYCL runtime. It can migrate between the CPU and GPU automatically, allowing the same pointer to be used everywhere (similar to **Managed Memory**—memory that automatically moves between host and device—in CUDA). + +== USM and Vulkan's Buffer Device Address + +The secret behind USM's efficiency is its direct mapping to **Vulkan 1.4's Buffer Device Address** feature. + +When you allocate USM memory on the device, the SYCL runtime (through a backend like AdaptiveCpp) creates a Vulkan buffer and obtains its raw **64-bit device address** (a pointer-like address that the GPU can use directly). This address is then passed to the GPU kernels, which can treat it as a standard C{pp} pointer. + +[source,cpp] +---- +// Simple USM example in SYCL +sycl::queue q; + +// Allocate device memory (returns a raw pointer) +float* data = sycl::malloc_device(1024, q); + +q.submit([&](sycl::handler& h) { + h.parallel_for(sycl::range<1>(1024), [=](sycl::id<1> idx) { + // We can use the raw pointer directly in the kernel! + data[idx] *= 2.0f; + }); +}); +---- + +== Why Use USM? + +USM is the "gold standard" for complex data structures like linked lists, trees, and graphs on the GPU. These structures rely on pointers, which are difficult to implement using the traditional accessor-based model. + +By using USM, you can build **GPU-Resident Trees** (tree structures stored entirely in GPU memory) or **BVHs** (**Bounding Volume Hierarchies**—a tree structure used for fast spatial searches) that look and feel like standard C{pp} data structures. You can share pointers between the CPU and GPU without any manual "mapping" or "unmapping" of memory. + +== Conclusion: The Power of C{pp} and Vulkan + +Throughout this chapter, we've seen how SYCL and Single-Source C{pp} take the complex world of Vulkan and make it accessible to modern developers. By combining the low-level power of the Vulkan 1.4 API with the high-level abstractions of SYCL, you can build massive, high-performance compute applications with a fraction of the code. + +In the next chapter, we'll dive deeper into how to implement those complex data structures we just mentioned: **Advanced Data Structures on the GPU**. + +xref:04_vulkan_interoperability.adoc[Previous: Vulkan Interoperability] | xref:../07_Advanced_Data_Structures/01_introduction.adoc[Next: Advanced Data Structures] diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc new file mode 100644 index 00000000..a1ef9a7a --- /dev/null +++ b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc @@ -0,0 +1,32 @@ +:pp: {plus}{plus} + += Advanced Data Structures on the GPU + +== Introduction + +In the first half of this tutorial, we focused on how to execute compute dispatches and how to manage memory. We worked mostly with simple data structures like linear arrays (buffers) and 2D/3D grids (textures). While these are the bread and butter of GPU programming, many real-world problems require more complex organization. + +In this chapter, we're moving from "data-parallel" arrays to "GPU-resident" data structures. We'll explore how to build and traverse complex structures like **Trees (BVH/Octrees)** (BVH for bounding boxes, Octrees for 3D space partitioning), **Linked Lists**, and **Work Queues** entirely on the device. + +== Moving Data Structures to the GPU + +Traditionally, complex data structures were built on the CPU and then "flattened" into arrays for the GPU to read. While this works, it creates a massive bottleneck: any update to the structure requires a CPU-GPU round-trip. + +Modern Vulkan compute allows us to eliminate this bottleneck by moving the *construction* and *management* of these structures to the GPU. This is made possible by three key technologies: + +1. **64-bit Atomics**: Allowing for thread-safe updates to global counters and pointers across the entire GPU. This is critical for **lock-free** data structures, which we'll explore in detail. +2. **Buffer Device Address**: Moving away from complex descriptor sets to raw, pointer-like flexibility for building graph-like structures. +3. **Subgroup Operations**: Using the wave-aware logic we learned in Chapter 4 to build these structures much faster by **coalescing** (combining) multiple operations into a single atomic update. + +== Why This Matters + +GPU-resident data structures are the foundation of modern high-performance rendering and simulation: + +* **Ray Tracing**: Bounding Volume Hierarchies (BVH) are used to quickly find which triangles a ray might hit. +* **Physics, and Robotics**: Spatial partitioning structures like Octrees or Grid-based hashes are used for collision detection. +* **Order-Independent Transparency (OIT)**: A technique for rendering transparent objects without pre-sorting them on the CPU; per-pixel linked lists are used to store and sort transparent fragments on the GPU. +* **GPU-Driven Pipelines**: Work queues allow the GPU to generate its own work, which we'll explore in the next chapter. + +By the end of this chapter, you'll understand how to stop treating the GPU as a "dumb array processor" and start treating it as a platform for autonomous, complex data management. + +xref:../06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc[Previous: Unified Shared Memory (USM)] | xref:02_gpu_resident_trees.adoc[Next: GPU-Resident Trees] diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/02_gpu_resident_trees.adoc b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/02_gpu_resident_trees.adoc new file mode 100644 index 00000000..8ef13156 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/02_gpu_resident_trees.adoc @@ -0,0 +1,104 @@ +:pp: {plus}{plus} + += GPU-Resident Trees: BVH and Octrees + +== Why Trees? + +Trees are the fundamental structure for spatial partitioning. Whether you're searching for which triangles are hit by a ray or which objects are near a particle, a linear search through every object is too slow. + +While trees are easy to build recursively on the CPU, they are notoriously difficult to build on the GPU because of the SIMD execution model and lack of a shared heap. However, with the right approach, a GPU can build a tree much faster than a CPU ever could. + +== Bounding Volume Hierarchies (BVH) + +A BVH is a tree where each node represents a bounding box that contains all its children. This is the heart of every ray tracing engine. + +Traditionally, a BVH is "flattened" into a linear array where child links are represented as array indices. On modern hardware, we can build these trees using **Radix Trees** (a space-optimized tree) or **Morton Codes**. + +=== The Anatomy of a BVH Node + +A typical **Inner Node** in a BVH must store its spatial boundaries and pointers to its children. A **Leaf Node** stores its boundaries and a list of primitives (like triangles) it contains. + +To save space and improve cache locality, these are often packed into a single structure: + +[source,slang] +---- +struct BVHNode { + float3 min; // AABB Min: The minimum corner of the bounding box + uint childOrLeaf; // Index to children OR first triangle in leaf + float3 max; // AABB Max: The maximum corner of the bounding box + uint count; // Number of children (if inner) OR triangles (if leaf) +}; +---- + +In this layout: + +* **AABB (Axis-Aligned Bounding Box)**: Represented by two points (`min` and `max`). This is the most common volume because checking if a ray hits a box is extremely fast on the GPU. +* **childOrLeaf**: A single 32-bit integer that points to the next level of the tree. If `count > 0`, it's a leaf node. If `count == 0`, it's an inner node and `childOrLeaf` is the index of the first child in the `nodePool` buffer. + +=== Building the Hierarchy: Morton Codes + +1. **Morton Coding**: We map 3D positions into a 1D **space-filling curve** (the **Z-curve**). This is done by **interleaving the bits** of the X, Y, and Z coordinates. For example, if X is `010` and Y is `101`, the Morton code would be `011001` (0 from X[0], 1 from Y[0], 1 from X[1], 0 from Y[1] etc). This mapping has the magical property that points that are close in 3D space will be close in 1D space, effectively "flattening" the 3D hierarchy into a sorted list. +2. **Radix Sorting**: Once we have the Morton codes, we use a high-performance GPU **radix sort**. Radix sort is a non-comparative sorting algorithm that sorts numbers bit-by-bit. Because it doesn't require complex comparisons, it's incredibly efficient on SIMD hardware. Sorting the Morton codes is what actually "groups" our objects spatially. +3. **Hierarchy Construction**: After sorting, each thread in a compute dispatch builds one part of the tree. By looking at the first bit where two adjacent Morton codes differ, a thread can determine where a node in the tree should be split. This is known as a **Linear BVH** (LBVH), and it allows the entire tree to be built in parallel without any global locks. + +This process is "embarrassingly parallel" and can build a BVH for millions of triangles in just a few milliseconds. + +== Octrees + +An Octree is a tree where each node has exactly eight children, partitioning space into **octants** (the eight natural divisions of 3D space, like the corners of a cube). This is the perfect structure for fluid simulations or **voxel-based rendering** where you need to quickly find which part of space is occupied. + +=== The Anatomy of an Octree Node + +Unlike a BVH node which has a flexible number of children, a pure Octree node always represents a perfect cube that can be split into eight smaller cubes. + +[source,slang] +---- +struct OctreeNode { + uint childIndices[8]; // Indices to the eight octants + float3 center; // Center of the node's cube + float extent; // Half-width of the node's cube + uint payload; // User data (e.g., color, density, or material) +}; +---- + +However, storing eight 32-bit indices (32 bytes) per node can be very memory-intensive. In practice, developers often use **Pointer-Based Octrees** where only a single `firstChildIndex` is stored, and the eight children are guaranteed to be contiguous in the `nodePool`. This reduces the node size to a single index and a few bits of metadata. + +=== Construction Strategies: Top-Down vs. Bottom-Up + +* **Bottom-Up**: Start with every object as a leaf, and use `SubgroupMatch` (from Chapter 4) to find objects that should belong to the same parent node. This is fast but requires complex sorting. +* **Top-Down**: Start with one root node and use global atomics to "subdivide" nodes as needed. This is more intuitive but can lead to high memory contention. + +== Traversing the Tree: Stacks and Bitfields + +Once the tree is built, how do we use it? In C{pp}, you'd use a recursive function. On the GPU, recursion is often forbidden or performs poorly because each thread has a limited amount of **Private Memory** (registers) for its call stack. + +Instead, we use **Stack-Based Traversal** or **Stackless Traversal**: + +1. **Stack-Based**: Each thread maintains its own small array of "nodes to visit" in registers or local memory. This is fast but consumes precious registers, potentially lowering **Occupancy** (the number of active threads the hardware can run simultaneously). +2. **Stackless (Threaded Trees)**: Each node stores a "skip pointer" to the next node in a **Depth-First Search (DFS)** order. If a ray misses a node, it simply follows the skip pointer to bypass all that node's children. This requires zero stack space but makes the tree-building process more complex. + +== Implementation Challenges: The Memory Bottleneck + +The biggest challenge when building trees on the GPU is **Memory Management**. In a traditional C{pp} application, you'd use `malloc` or `new` to create nodes as you need them. In a compute shader, these don't exist. + +Why? Because traditional CPUs use a **centralized heap manager** for `malloc`, which relies on a global lock to prevent different threads from claiming the same memory. If 10,000 GPU threads all tried to call `malloc` at the same time, the hardware would spend all its time waiting for the lock, leading to a massive performance collapse. + +Instead, we have to pre-allocate a **"node pool"** (a large buffer) and use a single atomic counter to "allocate" nodes from this pool. Each thread that needs a node simply increments the counter and uses the result as its unique index into the pool. + +[source,slang] +---- +// Simple node allocation using atomics +struct Node { ... }; +RWStructuredBuffer nodePool; +RWStructuredBuffer nodeCounter; + +uint allocateNode() { + uint index; + InterlockedAdd(nodeCounter[0], 1, index); + return index; +} +---- + +While this works, it can be slow if thousands of threads are all hitting the same counter. In the next section, we'll look at how **64-bit Atomics** and **Global Atomic Management** can optimize this process for massive scale. + +xref:01_introduction.adoc[Previous: Introduction to Advanced Data Structures] | xref:03_global_atomic_management.adoc[Next: Global Atomic Management] diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/03_global_atomic_management.adoc b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/03_global_atomic_management.adoc new file mode 100644 index 00000000..73b54eda --- /dev/null +++ b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/03_global_atomic_management.adoc @@ -0,0 +1,128 @@ +:pp: {plus}{plus} + += Global Atomic Management: Lock-Free Lists and Queues + +== Why 64-bit Atomics? + +In early Vulkan, atomics were limited to 32-bit integers. While useful for simple counters, they weren't enough to handle pointers or complex data structures. With **Vulkan 1.4**, 64-bit atomics are a core feature, which opens the door to building truly lock-free data structures. + +A 64-bit atomic can store both a value and a "tag" (to avoid the **ABA problem**—where a value is changed from A to B and back to A, tricking a thread into thinking it never changed) or a full 64-bit **Buffer Device Address** (a pointer). + +== What Does "Lock-Free" Actually Mean? + +In traditional CPU programming, if two threads want to update the same piece of data, we use a **mutex** (mutual exclusion) to "lock" the data, perform the update, and then "unlock" it. On a GPU, this is a disaster. Because thousands of threads are running in lock-step (**SIMT**—Single Instruction, Multiple Threads), if one thread takes a lock and the others wait, the entire GPU can grind to a halt—a situation called **deadlock**. + +A **Lock-Free** algorithm is one that guarantees that at least one thread in the system will make progress in a finite number of steps. Instead of locking, we use **Atomic Operations**. These are special hardware instructions that perform a "Read-Modify-Write" sequence in a single, uninterruptible step. + +In our linked list example, we use `InterlockedExchange` (or `atomicExchange` in GLSL). This instruction says: "Take this new value, put it in memory, and give me whatever was there before—all without letting any other thread touch that memory location in between." + +Because every thread successfully completes its "exchange" and gets a unique `oldHead`, no thread ever has to wait for another. They all make progress simultaneously. This is the essence of being lock-free on the GPU. + +== Building Lock-Free Linked Lists + +Linked lists are the foundation of many GPU algorithms, particularly for **Order-Independent Transparency (OIT)**. In a per-pixel linked list, every pixel in the framebuffer stores a "head" pointer to a list of transparent fragments that hit that pixel. + +=== The Anatomy of a GPU Linked List + +A GPU-resident linked list consists of three main components: + +1. **The Head Buffer**: A 2D texture or buffer (matching the screen resolution) that stores the index of the first node for each pixel. It is initialized to a "null" value (e.g., `0xFFFFFFFF`). +2. **The Node Pool**: A large linear buffer that stores the actual data for every fragment. +3. **The Atomic Counter**: A single integer used to "allocate" nodes from the pool. + +[source,slang] +---- +struct Node { + float4 color; // Fragment color + float depth; // Fragment depth + uint nextIdx; // Index of the next node in the pool +}; + +RWStructuredBuffer headBuffer; // size: width * height +RWStructuredBuffer nodePool; // size: Max total fragments +RWStructuredBuffer counter; // size: 1 +---- + +When a fragment is processed: + +1. The thread atomically increments the `counter` to get a unique `newNodeIdx`. +2. The thread uses `InterlockedExchange` on the `headBuffer` at its pixel location. It writes `newNodeIdx` and receives the `oldHead`. +3. The thread writes its data and the `oldHead` (as `nextIdx`) into `nodePool[newNodeIdx]`. + +This structure allows thousands of fragments to be added to millions of different lists simultaneously without ever needing a global lock. + +=== Beyond Exchange: Compare-and-Swap (CAS) + +While `InterlockedExchange` is great for simple lists, more complex structures (like thread-safe queues) often need **Compare-and-Swap (CAS)**, exposed as `InterlockedCompareExchange` in Slang. + +CAS works like this: "Only update this memory if its current value matches my 'expected' value." If it doesn't match, it means another thread changed the data first. In that case, our thread must "retry" the operation with the new value. This "loop until success" pattern is common in advanced lock-free programming and is much more efficient than a traditional lock because threads only wait if there is actual contention, and they never leave the hardware scheduler. + +=== GLSL: atomicAdd and 64-bit Atomics + +In GLSL, you use the `atomicAdd` and `atomicExchange` functions. For 64-bit atomics, you must enable the `GL_EXT_shader_atomic_int64` extension. + +[source,glsl] +---- +#extension GL_EXT_shader_atomic_int64 : enable + +layout(binding = 0) buffer HeadBuffer { uint64_t heads[]; }; +layout(binding = 1) buffer Counter { uint64_t count; }; + +void addNode(uint pixelIdx, Node newNode) { + // 64-bit atomic add to a global counter + uint64_t newNodeIdx = atomicAdd(count, 1UL); + + // 64-bit atomic exchange to update the head pointer + uint64_t oldHead = atomicExchange(heads[pixelIdx], newNodeIdx); + + // ... update node and next pointer +} +---- + +While Slang provides a more unified `InterlockedAdd` that works across different bit-widths, GLSL requires being explicit about the extensions and the types (e.g., using `1UL` for 64-bit literals). + +While the example above uses 32-bit indices for simplicity, 64-bit atomics allow you to do this across different buffers or even different memory types using raw pointers. + +== Building Work Queues + +A **Work Queue** is a list of tasks that the GPU needs to perform. In a **GPU-Driven Pipeline**, one compute dispatch might generate a list of objects that need to be culled, and then another dispatch might process that list. + +=== The Anatomy of a Work Queue + +A work queue is essentially a **producer-consumer** structure. On the GPU, this is typically implemented as a **Linear Buffer** with an atomic counter, or a **Ring Buffer** for persistent workloads. + +[source,slang] +---- +struct Task { + uint objectID; + uint drawCommandIdx; +}; + +struct WorkQueue { + RWStructuredBuffer data; // Storage for pending tasks + RWStructuredBuffer counter; // Number of tasks currently in the queue +}; + +void pushTask(WorkQueue queue, Task myTask) { + uint slot; + // Atomic increment to claim a unique slot + InterlockedAdd(queue.counter[0], 1, slot); + + // Check for buffer overflow! + if (slot < MAX_QUEUE_SIZE) { + queue.data[slot] = myTask; + } +} +---- + +By using a global work queue, you can handle variable-sized workloads without ever returning to the CPU. + +== Optimizing Atomics with Subgroups + +Atomics are relatively expensive because they have to be coordinated across the entire GPU. If thousands of threads are all trying to add to the same counter, the hardware will serialize them, leading to a massive performance drop. + +As we discussed in Chapter 4, you can use **Subgroup Operations** to **coalesce** (combine multiple operations into one) these atomics. Instead of every thread calling `InterlockedAdd`, you can have the threads in a subgroup perform a **Subgroup Reduction** to calculate the total amount they need to add, pick one "leader" thread to perform a single atomic add for the whole subgroup, and then distribute the resulting base index to the other threads. + +This simple optimization can improve the throughput of global atomics by 32x or 64x, making complex data structures viable for even the most demanding real-time applications. + +xref:02_gpu_resident_trees.adoc[Previous: GPU-Resident Trees] | xref:04_device_addressable_buffers.adoc[Next: Device-Addressable Buffers] diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc new file mode 100644 index 00000000..7b3b0920 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc @@ -0,0 +1,101 @@ +:pp: {plus}{plus} + += Device-Addressable Buffers: Pointer-like Flexibility + +== The End of Descriptor Set Hell + +If you've spent any time with Vulkan, you know the pain of **Descriptor Sets**. Managing layouts, updating pools, and binding sets before every draw or dispatch call is one of the most boilerplate-heavy parts of the API. + +But what if you didn't have to bind anything? What if you could just pass a raw 64-bit address to your shader and have it access the memory directly, just like a pointer in C{pp}? This is what **Buffer Device Address (BDA)** allows. + +== What is BDA? + +**Buffer Device Address** (available since Vulkan 1.2 and core in 1.4) allows you to query a 64-bit GPU address for any `VkBuffer`. This address is a raw pointer that can be stored in other buffers, passed to shaders via push constants, or even used to build complex, linked data structures across different memory regions. + +To use BDA, you must enable the `bufferDeviceAddress` feature and create your buffers with the `VK_BUFFER_USAGE_SHADER_DEVICE_ADDRESS_BIT`. + +[source,cpp] +---- +// C++ side: Obtaining a device address +vk::BufferDeviceAddressInfo info { + .buffer = *myBuffer // Extracting the handle from a vk::raii::Buffer +}; +uint64_t myGPUAddress = device.getBufferAddress(info); + +// Pass myGPUAddress to a shader via a push constant! +---- + +== BDA in Shaders + +In Slang or GLSL, you can treat this 64-bit address as a raw pointer. This completely bypasses the need for descriptor sets for many use cases. + +[source,slang] +---- +// Slang example of using BDA +struct MyData { + float4 value; + MyData* next; // A raw BDA pointer! +}; + +// We receive the starting address as a 64-bit integer (uint64_t) +void process(uint64_t startAddress) { + MyData* p = (MyData*)startAddress; + + // We can traverse the structure just like in C++! + while (p != nullptr) { + doSomething(p->value); + p = p->next; + } +} +---- + +=== GLSL: buffer_reference + +In GLSL, this requires the `GL_EXT_buffer_reference` and `GL_EXT_shader_explicit_arithmetic_types_int64` extensions. Instead of raw C{pp} pointers, you use the `buffer_reference` keyword to define "pointers" to buffer blocks. + +[source,glsl] +---- +#extension GL_EXT_buffer_reference : enable +#extension GL_EXT_shader_explicit_arithmetic_types_int64 : enable + +// Define a buffer block as a reference type +layout(buffer_reference, std430) buffer MyData { + vec4 value; + MyData next; // Pointer-like reference to another MyData +}; + +layout(push_constant) uniform Constants { + MyData startPtr; // We receive the 64-bit address as a reference +}; + +void main() { + MyData p = startPtr; + + while (uint64_t(p) != 0) { + doSomething(p.value); + p = p.next; + } +} +---- + +While the Slang syntax is much closer to C{pp}, both produce the same low-level **SPIR-V** instructions for 64-bit address calculation and memory access. + +== Why BDA is a Game-Changer + +1. **Zero Binding Overhead**: You can pass thousands of buffer addresses to a single shader via a single push constant or a "pointer buffer," completely bypassing the CPU cost of managing descriptor pools and sets. +2. **Complex Data Structures**: You can build real linked lists, trees, and graphs where nodes contain actual 64-bit pointers to other nodes, allowing for "pointer chasing" that was previously impossible. +3. **Heterogeneous Programming**: BDA is the foundation for SYCL's **Unified Shared Memory (USM)**. It bridges the gap between the pointer-based world of C{pp} and the explicit world of Vulkan. + +=== The Cost of Freedom: Safety and Performance + +With great power comes great responsibility. Unlike Descriptor Sets, where the Vulkan validation layers can often catch out-of-bounds access, **BDA is raw and unchecked**. If you access an invalid address or go out of bounds, you won't get a helpful error message—you'll likely trigger a **GPU hang** (where the screen freezes) or a "Device Lost" error. + +Performance-wise, BDA is generally as fast as standard buffer access. However, because the hardware doesn't know the size of the buffer being accessed, it can't always perform the same cache optimizations as it does with explicit descriptors. For most advanced compute tasks, the flexibility of raw pointers far outweighs these minor trade-offs. + +== Conclusion + +By combining 64-bit atomics, subgroup operations, and raw buffer device addresses, we have all the tools we need to build complex, autonomous data structures on the GPU. We are no longer limited by the "flat array" model of traditional compute. + +In the next chapter, we'll see how to take this a step further and use these structures to drive the entire rendering pipeline directly from the GPU: **Indirect Dispatch and GPU-Driven Pipelines**. + +xref:03_global_atomic_management.adoc[Previous: Global Atomic Management] | xref:../08_GPU_Driven_Pipelines/01_introduction.adoc[Next: Indirect Dispatch] diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc new file mode 100644 index 00000000..00efb882 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc @@ -0,0 +1,37 @@ +:pp: {plus}{plus} + += Indirect Dispatch and GPU-Driven Pipelines + +== Introduction + +In traditional Vulkan applications, the CPU is the "conductor" of the orchestra. It decides what to draw, how many threads to dispatch, and which resources to bind. The GPU is simply a "performer" that executes the commands the CPU gives it. + +However, as scenes become more complex—with millions of dynamic objects and complex physics—the CPU can no longer keep up. The overhead of the CPU calculating which objects are visible and then recording thousands of command buffers becomes the primary bottleneck. + +In this chapter, we'll explore **GPU-Driven Pipelines**, where the GPU takes over the role of the conductor. + +== Moving Beyond Static Dispatches + +A static dispatch (`vkCmdDispatch`) requires the CPU to know exactly how many workgroups to run. If you're doing something like object culling, the CPU doesn't know how many objects will pass the cull until the GPU has finished its work. + +With **Indirect Dispatch** (`vkCmdDispatchIndirect`), the CPU doesn't provide the dispatch size. Instead, it provides a **Vulkan Buffer** that contains the dispatch parameters. The GPU itself can then write to this buffer, effectively deciding how much work it needs to do. + +== The Autonomous GPU + +GPU-driven pipelines take this even further with features like: + +1. **GPU-Side Command Generation**: Utilizing modern engine features to build entire chains of commands on the GPU, allowing it to "decide" its own execution path. +2. **Multi-Draw Indirect (MDI)**: A feature allowing a single compute dispatch to generate thousands of draw calls, effectively rendering an entire scene without a single CPU-side loop. +3. **Variable-Sized Workloads**: Handling everything from particle systems to high-fidelity culling without any CPU-side intervention. + +== Why This Matters + +By moving the "decision-making" to the GPU, we can: + +* **Eliminate CPU Bottlenecks**: Free up the CPU for AI, game logic, and other tasks. +* **Minimize Latency**: Eliminate the round-trip delay between a GPU's compute analysis and its subsequent rendering. +* **Scale to Millions**: Handle scene complexity that would be impossible with traditional CPU-bound pipelines. + +In this chapter, we'll learn how to build these autonomous pipelines, starting with the fundamental building block: **Indirect Dispatch**. + +xref:../07_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Previous: Device-Addressable Buffers] | xref:02_indirect_dispatch.adoc[Next: Indirect Dispatch] diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/02_indirect_dispatch.adoc b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/02_indirect_dispatch.adoc new file mode 100644 index 00000000..8cb65324 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/02_indirect_dispatch.adoc @@ -0,0 +1,97 @@ +:pp: {plus}{plus} + += Indirect Dispatch: Building Parameters on the GPU + +== The Core of GPU Autonomy + +In a traditional compute pipeline, the CPU calls `vkCmdDispatch(x, y, z)`. The values of `x, y, z` are fixed at the moment the command buffer is recorded. + +But what if the number of workgroups you need depends on the result of a previous compute shader? For example, if you're culling a list of objects, only the GPU knows how many survived. + +**Indirect Dispatch** (`vkCmdDispatchIndirect`) solves this by reading the workgroup counts from a **Vulkan Buffer** (a `VkBuffer`) instead of the command buffer. + +== How It Works + +1. **Preparation**: Create a buffer with the `VK_BUFFER_USAGE_INDIRECT_BUFFER_BIT`. +2. **GPU Update**: Run a "culling" or "analysis" compute shader. This shader calculates the number of workgroups needed for the next step and writes that value into the indirect buffer. +3. **The Dispatch**: The CPU records a call to `vkCmdDispatchIndirect(myIndirectBuffer, offset)`. + +[source,cpp] +---- +// The layout of the data in the indirect buffer (matching vk::DispatchIndirectCommand) +struct IndirectCommand { + uint32_t x; + uint32_t y; + uint32_t z; +}; +---- + +== Writing the Indirect Command from a Shader + +To use this, your compute shader (the "producer") must write to a buffer that matches the `VkDispatchIndirectCommand` layout. + +[source,slang] +---- +// Slang example: Writing the dispatch counts +struct IndirectCommand { + uint3 x; +}; + +[[vk::binding(0, 0)]] +RWStructuredBuffer cmdBuffer; + +[numthreads(1, 1, 1)] +void main() { + uint numWorkgroups = calculateRequiredWorkgroups(); + cmdBuffer[0].x = uint3(numWorkgroups, 1, 1); +} +---- + +=== GLSL: Manual Buffer Layout + +In GLSL, you define a `buffer` block that matches the expected structure. It's crucial to use the correct alignment (`std430`) to ensure the GPU reads the values at the correct offsets. + +[source,glsl] +---- +layout(std430, binding = 0) buffer IndirectBuffer { + uint x; + uint y; + uint z; +} cmd; + +void main() { + uint numWorkgroups = calculateRequiredWorkgroups(); + cmd.x = numWorkgroups; + cmd.y = 1; + cmd.z = 1; +} +---- + +The "win" here is that by using the same buffer in your `vkCmdDispatchIndirect` call, the GPU can autonomously determine its own workload size without any CPU intervention. + +== Synchronization is Key + +Because the GPU is writing to the buffer that it will later read from, you must ensure that the write has finished and is **visible** to the indirect dispatch hardware. + +This requires a **Vulkan Barrier** with the following settings: + +* `srcStage`: `VK_PIPELINE_STAGE_COMPUTE_SHADER_BIT` +* `dstStage`: `VK_PIPELINE_STAGE_DRAW_INDIRECT_BIT` +* `srcAccess`: `VK_ACCESS_SHADER_WRITE_BIT` +* `dstAccess`: `VK_ACCESS_INDIRECT_COMMAND_READ_BIT` + +Failure to include this barrier will result in the GPU reading "garbage" or stale data, leading to incorrect dispatches or even device crashes. + +== Practical Example: Variable-Sized Workloads + +Imagine you have a particle system where particles can die or be born every frame. + +1. **Dispatch 1 (Cull)**: A compute shader iterates over all particles, calculates which ones are alive, and stores their IDs in a "live" buffer. It also increments an atomic counter. +2. **Barrier**: Wait for the cull to finish and make the counter visible to the indirect hardware. +3. **Dispatch 2 (Update)**: Call `vkCmdDispatchIndirect`. The GPU reads the counter and dispatches exactly enough workgroups to update only the alive particles. + +This approach is much more efficient than always dispatching for the "maximum" number of particles, which would result in thousands of idle threads. + +In the next section, we'll look at how the GPU can go beyond just changing its dispatch size and start generating its own **Command Chains**. + +xref:01_introduction.adoc[Previous: Introduction to GPU-Driven Pipelines] | xref:03_gpu_side_command_generation.adoc[Next: GPU-Side Command Generation] diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc new file mode 100644 index 00000000..a982eba8 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc @@ -0,0 +1,41 @@ +:pp: {plus}{plus} + += GPU-Side Command Generation: Autonomous Execution + +== Building Command Chains on the GPU + +In a typical Vulkan application, the CPU records a series of commands: `vkCmdBindPipeline`, `vkCmdBindDescriptorSets`, `vkCmdDispatch`, etc. These commands are "baked" into the command buffer. + +With **GPU-Side Command Generation** (often utilizing the engine's built-in indirect buffers and BDA), we can go a step further. Instead of the CPU deciding the entire sequence of commands, the GPU can build a list of "commands" that it wants to execute. + +This is a key component of **GPU-Driven Pipelines**. The GPU can analyze its own state and decide to: + +1. Dispatch a compute shader to update a set of physics. +2. Dispatch another compute shader to build a BVH. +3. Generate a series of draw calls to render the updated scene. + +== How It Works: The Buffer-First Approach + +In a GPU-driven pipeline, the CPU typically records a "master" compute dispatch. This dispatch iterates over your objects or tasks and writes to a series of **Indirect Command Buffers**: + +* **Dispatch Indirect Buffer**: Stores the `x, y, z` parameters for future compute shaders. +* **Draw Indirect Buffer**: Stores the `vertexCount`, `instanceCount`, etc., for future rendering. +* **Resource Buffer**: Stores the raw pointers (Buffer Device Address) that those shaders and draws will need. + +== Why This Matters for Performance + +When the GPU generates its own commands, the CPU is completely out of the loop. There is no longer any need to: + +* **Re-record Command Buffers**: No CPU overhead for every frame. +* **CPU-Side Culling**: No "back-and-forth" data exchange. +* **Synchronization Overhead**: Synchronization happens entirely within the GPU's command stream. + +== The Power of Autonomy + +This autonomous model allows for **Single-Pass Rendering** (performing culling and drawing in a single GPU pass). Instead of the CPU having to wait for the GPU's culling result to know what to draw, the GPU can cull objects and then draw them in the same command stream. + +This is the standard architecture for many modern, high-end rendering engines. It scales to millions of objects because the cost of "culling and drawing" is independent of the CPU's performance. + +In the next section, we'll look at the final piece of the puzzle: **Multi-Draw Indirect (MDI)**, which bridges our compute analysis to the graphics pipeline. + +xref:02_indirect_dispatch.adoc[Previous: Indirect Dispatch] | xref:04_multi_draw_indirect_mdi.adoc[Next: Multi-Draw Indirect (MDI)] diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc new file mode 100644 index 00000000..6a0c7602 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc @@ -0,0 +1,47 @@ +:pp: {plus}{plus} + += Multi-Draw Indirect (MDI): Bridging Compute to Graphics + +== Bridging the Gap + +Throughout this chapter, we've focused on how to make compute shaders more autonomous. But the final goal of most graphics applications is... well, graphics. We need a way to take the results of our compute-based culling or analysis and turn them into draw calls. + +**Multi-Draw Indirect (MDI)** is the ultimate bridge between the compute and graphics pipelines. It allows a single Vulkan command to execute an arbitrary number of draw calls, where the parameters for each draw call come from a GPU-side buffer. + +== How It Works: The MDI Pipeline + +1. **Cull Phase (Compute)**: A compute shader analyzes your scene (e.g., millions of objects) and decides which ones are visible. It writes the `vertexCount`, `instanceCount`, etc., for each visible object into a large **Indirect Buffer**. +2. **Count Buffer**: The compute shader also keeps an atomic counter of how many objects were visible and writes this count into a separate **Draw Count Buffer**. +3. **The Draw (Graphics)**: The CPU calls `vkCmdDrawIndexedIndirectCount`. This single command tells the GPU to read its own counts and parameters and draw the objects. + +[source,cpp] +---- +// The layout of the data in the MDI buffer (matching vk::DrawIndexedIndirectCommand) +struct IndirectDrawCommand { + uint32_t indexCount; + uint32_t instanceCount; + uint32_t firstIndex; + int32_t vertexOffset; + uint32_t firstInstance; +}; +---- + +== Why MDI is Essential for GPU-Driven Rendering + +Without MDI, the CPU would have to read back the visibility count from the GPU and then record a separate `vkCmdDraw` for every visible object. For a scene with 10,000 visible objects, that would be 10,000 CPU calls and 10,000 command records every frame. + +With MDI, those 10,000 objects are rendered with **one command**. This is how modern engines can handle massive "culling-first" architectures. + +== Best Practices for MDI + +* **Max Draw Count**: Always specify a reasonable maximum draw count in the `vkCmdDrawIndexedIndirectCount` call to prevent the GPU from over-reading its buffers in case of errors. +* **Buffer Alignment**: Ensure that your indirect buffer follows the correct alignment and stride requirements for your hardware. +* **Combine with BDA**: Use **Buffer Device Address** (from Chapter 7) to pass object-specific data (like materials and transforms) to your shaders, bypassing traditional descriptor sets. + +== Conclusion: The Future is GPU-Driven + +By mastering **Indirect Dispatch**, **GPU-Side Command Generation**, and **Multi-Draw Indirect**, you've moved from a traditional "CPU-lead" pipeline to a modern "GPU-driven" architecture. Your applications are now more scalable, lower latency, and more efficient. + +In the next chapter, we'll look at how to coordinate these heavy compute workloads with your graphics rendering using **Asynchronous Compute Orchestration**. + +xref:03_gpu_side_command_generation.adoc[Previous: GPU-Side Command Generation] | xref:../09_Asynchronous_Compute/01_introduction.adoc[Next: Asynchronous Compute Orchestration] diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc new file mode 100644 index 00000000..2e76112f --- /dev/null +++ b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc @@ -0,0 +1,20 @@ +:pp: {plus}{plus} += Asynchronous Compute Orchestration + +In the earlier chapters, we've focused heavily on making individual kernels as fast as possible. We've optimized memory access, leveraged subgroups, and even built entire data structures on the GPU. But there's a higher level of optimization that often goes overlooked: how we schedule these dispatches alongside the rest of the engine's workload. + +Modern GPUs aren't just single, monolithic processors; they are complex systems with multiple hardware engines capable of working in parallel. To understand asynchronous compute, we first have to understand the physical hardware. A typical high-performance GPU has several specialized engines: + +* **Graphics Engine**: The primary engine, capable of vertex processing, rasterization, and fragment shading, as well as general-purpose compute. +* **Asynchronous Compute Engine (ACE)**: A dedicated scheduler and hardware path for compute dispatches. These can often run entirely in parallel with the graphics engine, using compute units (CUs) or streaming multiprocessors (SMs) that aren't being fully utilized by the graphics workload. +* **Transfer/Copy Engine**: A specialized DMA (Direct Memory Access) engine for moving data between host and device memory without consuming any compute resources. + +Vulkan exposes these hardware engines through **Queue Families**. Each family has a set of **capabilities** (e.g., `VK_QUEUE_GRAPHICS_BIT`, `VK_QUEUE_COMPUTE_BIT`, `VK_QUEUE_TRANSFER_BIT`). While the main graphics queue family usually supports everything, a "Dedicated Compute" or "Async Compute" family might *only* support compute and transfer. + +By using separate compute queues from these dedicated families, we can overlap heavy compute dispatches—like path-trace denoising, physics simulations, or complex AI pathfinding—with the main graphics rendering pass. While the graphics hardware is busy processing geometry and rasterizing triangles, the compute units can be simultaneously crunching numbers for your simulation. + +In this chapter, we're going to move beyond the simple "one queue for all" model. We'll explore how to use Vulkan's **Synchronization 2** (`VK_KHR_synchronization2`) to orchestrate complex, concurrent workloads without causing **pipeline stalls** (where the GPU sits idle waiting for a resource). We'll also look at **Queue Priority**, a feature that allows us to tell the hardware which tasks are truly latency-critical, ensuring that a background simulation doesn't delay a time-sensitive physics update. + +Orchestrating these workloads requires a shift in how we think about the GPU's timeline. It's no longer just a linear sequence of commands, but a multi-lane highway where different types of traffic can move at different speeds, occasionally merging or yielding to ensure the overall throughput is maximized. + +xref:../08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Previous: Multi-Draw Indirect (MDI)] | xref:02_concurrent_execution.adoc[Next: Concurrent Execution] diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/02_concurrent_execution.adoc b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/02_concurrent_execution.adoc new file mode 100644 index 00000000..b72ed05b --- /dev/null +++ b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/02_concurrent_execution.adoc @@ -0,0 +1,64 @@ +:pp: {plus}{plus} += Concurrent Execution and Synchronization 2 + +To achieve true parallelism between graphics and compute, we need to talk about the Vulkan timeline. In a standard single-queue setup, everything happens sequentially—you dispatch compute, wait for it to finish, and then begin your graphics work. This is straightforward but inefficient. By using multiple queues, we can submit work to a dedicated **compute queue** and have the GPU execute it alongside a main **graphics queue**. + +The challenge, however, isn't just submitting the work; it's making sure it stays synchronized where it matters. If our compute dispatch is generating a texture that the graphics pass needs, we can't let the graphics start reading until the compute is done. But we *can* let the graphics do everything else—like clearing buffers, processing vertices, or even rasterizing other, unrelated objects. + +This is where **Synchronization 2** (`VK_KHR_synchronization2`) shines. The older Vulkan synchronization was powerful but notoriously complex and difficult to read. It relied on bitmasks for pipeline stages and access types that were often redundant. Synchronization 2 simplifies this by grouping them into more logical structures and, more importantly, it introduces a more robust way to express **dependency chains** across different queues. + +== Async Compute vs. Concurrent Execution +It's important to distinguish between "overlapping" work on a single queue and "asynchronous" work on separate hardware queues. + +On a single queue, the GPU can still overlap work—for example, it can start a new vertex shader while fragment shaders from a previous draw are still finishing. This is **Concurrent Execution**. However, it still follows a single command stream. + +**Asynchronous Compute** uses separate hardware engines (ACE) to feed the compute units (CU/SM). This means the compute engine is pulling commands from a completely different memory stream than the graphics engine. This is where true parallelism happens, allowing the GPU to keep its ALUs (Arithmetic Logic Units) saturated even when the graphics engine is bottlenecked by other factors like the ROPs (Raster Output Processors) or fixed-function geometry hardware. + +== Queue Ownership Transfer: The Handshake +One of the most cryptic, but essential, parts of multi-queue Vulkan is **Queue Ownership Transfer**. Most Vulkan resources (like `VkBuffer` or `VkImage`) are created with a sharing mode of `VK_SHARING_MODE_EXCLUSIVE` by default. This means they are owned by exactly one queue family at a time. + +To move a resource from a compute queue to a graphics queue, you must perform a "handshake" consisting of two parts: + +1. **Release**: A barrier on the **source** queue that "releases" ownership. +2. **Acquire**: A barrier on the **destination** queue that "acquires" ownership. + +If you omit either part, you have **undefined behavior** and potential data corruption. Synchronization 2 makes this explicit by including the `srcQueueFamilyIndex` and `dstQueueFamilyIndex` in the barrier structures. + +[source,cpp] +---- +// ON THE COMPUTE QUEUE (Source) +vk::ImageMemoryBarrier2 releaseBarrier { + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eNone, // We don't care about the destination stage yet + .dstAccessMask = vk::AccessFlagBits2::eNone, // Or the access mask + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eShaderReadOnlyOptimal, + .srcQueueFamilyIndex = computeQueueFamilyIndex, + .dstQueueFamilyIndex = graphicsQueueFamilyIndex, + .image = *sharedImage // Extract handle from vk::raii::Image +}; +// ... (subresourceRange setup) + +// ON THE GRAPHICS QUEUE (Destination) +vk::ImageMemoryBarrier2 acquireBarrier { + .srcStageMask = vk::PipelineStageFlagBits2::eNone, // We don't care about the source stage here + .srcAccessMask = vk::AccessFlagBits2::eNone, // Or the access mask + .dstStageMask = vk::PipelineStageFlagBits2::eFragmentShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderRead, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eShaderReadOnlyOptimal, + .srcQueueFamilyIndex = computeQueueFamilyIndex, + .dstQueueFamilyIndex = graphicsQueueFamilyIndex, + .image = *sharedImage // Extract handle from vk::raii::Image +}; +// ... (subresourceRange setup) +---- + +Notice how the `oldLayout` and `newLayout` must **match exactly** in both barriers. This is a critical requirement. The "Release" barrier ensures the memory is **available** (written out to memory/L2 cache), and the "Acquire" barrier ensures it is **visible** (invalidating read caches on the destination engine). + +The real "magic" happens when we use **Semaphore-based synchronization** (using `VkSemaphore` objects to coordinate work between queues) between queues. We submit our compute workload with a "signal" semaphore, and our graphics workload with a "wait" semaphore. The GPU handles the internal scheduling, stalling the graphics queue only when it reaches the specific pipeline stage that needs the compute result. This allows the GPU's hardware scheduler to keep the compute units busy during the geometry-heavy parts of the graphics pass, effectively "hiding" the cost of the compute work. + +Remember, though, that not all hardware is created equal. Some mobile GPUs have unified hardware for compute and graphics, where "concurrency" might just mean the scheduler interleaved the tasks. High-end desktop GPUs, on the other hand, often have dedicated compute pipes that can run entirely in parallel with the graphics engines. Profiling is your only way to know if your orchestration is truly delivering the performance gains you expect. + +xref:01_introduction.adoc[Previous: Introduction] | xref:03_timeline_semaphores.adoc[Next: Timeline Semaphores] diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/03_timeline_semaphores.adoc b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/03_timeline_semaphores.adoc new file mode 100644 index 00000000..5571693c --- /dev/null +++ b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/03_timeline_semaphores.adoc @@ -0,0 +1,50 @@ +:pp: {plus}{plus} += Timeline Semaphores: Unified Synchronization + +While binary semaphores (the classic `VkSemaphore`) are useful for simple "wait/signal" relationships between queues, they quickly become a management nightmare in complex asynchronous pipelines. Each binary semaphore can only be signaled once before it must be waited on and reset, leading to a proliferation of semaphore objects that are difficult to track. + +This is why **Timeline Semaphores** (introduced in Vulkan 1.2 and via `VK_KHR_timeline_semaphore`) are a game-changer for asynchronous compute. Instead of a simple boolean "on/off" state, a timeline semaphore contains a monotonically increasing **64-bit integer value**. + +== The Power of a Single Value +With a timeline semaphore, you don't just wait for a semaphore to be signaled; you wait for it to reach a **specific value**. This allows you to represent an entire timeline of work with a single object. For example: + +* **Value 10**: Physics simulation finished. +* **Value 11**: Denoising pass finished. +* **Value 12**: Frame ready for UI composition. + +Different queues can signal the same semaphore with different values, and other queues can wait for exactly the level of progress they need. + +== Wait-Before-Signal (The Host Side) +One of the most powerful features of timeline semaphores is that you can submit a command buffer that waits for a value that **hasn't been reached yet**. In fact, the signal operation doesn't even have to be submitted to the GPU when the wait is submitted. + +This allows the CPU to build complex dependency graphs and submit them all at once to different queues. The GPU hardware will handle the stalls and wake-ups automatically as the counter increments. + +[source,cpp] +---- +// Defining a wait for a specific timeline value +vk::TimelineSemaphoreSubmitInfo timelineInfo { + .waitSemaphoreValueCount = 1, + .pWaitSemaphoreValues = &requiredValue, + .signalSemaphoreValueCount = 1, + .pSignalSemaphoreValues = &newValue +}; + +vk::SubmitInfo submitInfo { + .pNext = &timelineInfo, + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*timelineSemaphore // Extract handle from vk::raii::Semaphore +}; +// ... +---- + +== Host Querying and Waiting +Timeline semaphores also bridge the gap between the GPU and the CPU. The CPU can query the current value of a semaphore at any time using `vkGetSemaphoreCounterValue`. Even better, the CPU can block until a semaphore reaches a certain value using `vkWaitSemaphores`. + +This replaces the need for `VkFence` in many scenarios. Instead of waiting for an entire command buffer to finish (which is what a fence does), the CPU can wait for a specific point in the GPU's timeline. This is incredibly useful for **pipelined resource management**—for example, the CPU can wait for the GPU to reach value `N`, knowing that it's now safe to reuse a buffer that was used by the command that signaled value `N`. + +== Why it matters for Async Compute +In an asynchronous compute setup, you often have multiple streams of work with cross-dependencies. For instance, your physics engine (Compute Queue) might produce data needed by the particle system (Graphics Queue), which in turn produces data needed by the denoiser (Compute Queue). + +Using binary semaphores for this would require a complex web of "Signal A -> Wait A -> Signal B -> Wait B". With timeline semaphores, you simply have a single "Engine Timeline". Every task signals its completion by incrementing the counter, and every dependent task waits for its specific prerequisite value. This drastically simplifies the orchestration logic and reduces the overhead of semaphore management. + +xref:02_concurrent_execution.adoc[Previous: Concurrent Execution] | xref:04_queue_priority.adoc[Next: Queue Priority] diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc new file mode 100644 index 00000000..97164763 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc @@ -0,0 +1,39 @@ +:pp: {plus}{plus} += Queue Priority: Managing Latency-Critical Workloads + +When you're dealing with multiple queues, you're essentially handing the GPU multiple streams of work and letting its hardware scheduler decide how to prioritize them. By default, the scheduler tries to be fair, but in a high-performance engine, "fair" isn't always what you want. You might have a critical physics update that *must* finish before the next frame, while a background path-trace denoiser can afford to take a few extra milliseconds. + +Vulkan provides a way to influence this through **Queue Priority**. When you create a logical device (`VkDeviceCreateInfo`), you specify a `priority` for each queue within a queue family. This value is a floating-point number between 0.0 and 1.0, where 1.0 represents the highest priority. + +[source,cpp] +---- +// Setting up high-priority compute queues +float priorities[] = { 1.0f, 0.1f }; // High priority for physics, low for denoising +vk::DeviceQueueCreateInfo queueCreateInfo { + .queueFamilyIndex = computeQueueFamilyIndex, + .queueCount = 2, + .pQueuePriorities = priorities +}; +---- + +== How the Scheduler Uses Priority +It's important to understand that queue priority is a **hint**, not a guarantee. The exact behavior depends heavily on the hardware's internal scheduler. Most modern GPUs use one of two main strategies: + +1. **Strict Priority**: The scheduler will always pick a task from a higher-priority queue if one is ready. This is great for responsiveness but can lead to **starvation** of low-priority tasks if the high-priority queue is constantly busy. +2. **Weighted Round-Robin**: The scheduler assigns a certain percentage of execution time to each queue based on its priority. For example, a queue with priority 1.0 might get twice as many "scheduling slots" as a queue with priority 0.5. + +High-end desktop GPUs often have sophisticated hardware that can **preempt** a low-priority task (e.g., stop a long-running compute shader) to make room for a high-priority one. However, preemption is not free; it involves saving and restoring the GPU's state, which can take several microseconds. + +== Global Queue Priority +If you're building a system where latency is truly the only thing that matters—like a VR (Virtual Reality) compositor or an AR (Augmented Reality) spatial tracker—you might need even more control. This is where `VK_EXT_global_priority` comes in. This extension allows you to request **Real-Time** priority for a queue. + +Unlike standard queue priority, which only works relative to other queues on your device, global priority tells the driver (and the OS) that your workload is more important than even other applications running on the same GPU. Use this sparingly, as it can cause stuttering in the rest of the system if used incorrectly. + +== Avoiding the "Single-Queue Trap" +A common mistake is to create multiple high-priority queues within the same queue family. If you do this, you've essentially returned to a "first-come, first-served" model. The hardware scheduler can only do its job if you provide clear, distinct priorities. + +Another critical consideration is **Queue Family** (a group of queues with similar capabilities) selection. Some Vulkan implementations offer multiple queue families, each with different capabilities. For example, a "Dedicated Compute" queue family might have specialized hardware for compute dispatches that don't share any resources with the graphics engine, making them more efficient and less likely to cause **pipeline bubbles** (gaps in the GPU's execution timeline). Always check the `VkQueueFamilyProperties` to understand what each queue family offers. + +In practice, managing queue priorities is a balancing act. Used correctly, it's a powerful tool for ensuring that your engine remains responsive and that the most critical tasks are always handled with the urgency they require. This orchestration is the hallmark of a truly advanced Vulkan engine—moving beyond just "doing the work" to "doing the work in the right order at the right time." + +xref:03_timeline_semaphores.adoc[Previous: Timeline Semaphores] | xref:../10_Specialized_Math/01_introduction.adoc[Next: Specialized Math] diff --git a/en/Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc b/en/Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc new file mode 100644 index 00000000..b40ba814 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc @@ -0,0 +1,12 @@ +:pp: {plus}{plus} += Cooperative Matrices and Specialized Math + +In the previous chapters, we've looked at how to move data efficiently and how to orchestrate complex workloads. But what happens when the workload itself is computationally intense? For a long time, GPU compute was synonymous with floating-point operations (FP32). However, modern hardware has evolved to include specialized units designed for a very specific type of work: high-speed linear algebra. + +This is the world of **Cooperative Matrices**. While you might have heard of "Tensor Cores" on NVIDIA or "Matrix Core" on AMD, Vulkan provides a vendor-neutral abstraction for these specialized units through the `VK_KHR_cooperative_matrix` extension (now part of Vulkan 1.4). These units aren't just for machine learning; they are incredibly powerful for any task that involves heavy matrix multiplication and accumulation (the **GEMM**—General Matrix-Matrix Multiplication—operation). + +Whether you're building a fluid simulation that requires solving large systems of linear equations or a signal processing pipeline that relies on complex transforms, Cooperative Matrices can provide a massive throughput boost. By performing small matrix multiplications directly in the hardware's specialized units, you can achieve performance that far exceeds what a standard compute shader loop could deliver. + +In this chapter, we're going to dive into how these specialized math units work. We'll explore how to use the `cooperative_matrix` types in Slang and GLSL, and we'll see how to leverage **Mixed Precision**—using FP16 or Int8 for calculations while maintaining accuracy where it counts. This is about more than just speed; it's about utilizing the full potential of modern GPU silicon for high-performance computing tasks. + +xref:../09_Asynchronous_Compute/04_queue_priority.adoc[Previous: Queue Priority] | xref:02_cooperative_matrices.adoc[Next: Cooperative Matrices] diff --git a/en/Advanced_Vulkan_Compute/10_Specialized_Math/02_cooperative_matrices.adoc b/en/Advanced_Vulkan_Compute/10_Specialized_Math/02_cooperative_matrices.adoc new file mode 100644 index 00000000..3e841ef4 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/10_Specialized_Math/02_cooperative_matrices.adoc @@ -0,0 +1,122 @@ +:pp: {plus}{plus} += Working with Cooperative Matrices + +[NOTE] +==== +This section requires the `VK_KHR_cooperative_matrix` extension and Vulkan 1.3 or higher. In Vulkan 1.4, this extension is promoted to the core API. +==== + +To understand why **Cooperative Matrices** are so powerful, we need to rethink how we approach matrix multiplication on a GPU. In a traditional "naive" loop, each invocation is responsible for calculating one or more elements of the result matrix. This involves a lot of redundant memory reads and is inherently bound by the hardware's standard floating-point throughput. + +Cooperative Matrices change the game by introducing a new way for a group of invocations (a **Subgroup**) to work together on a single matrix multiplication and accumulation (the **GEMM** operation). Instead of individual invocations working in isolation, the entire subgroup "cooperates" to perform the operation. + +== The Concept: Matrix Fragments and Subgroup Scope + +The key to cooperative matrices is the concept of a **Fragment**. When you declare a cooperative matrix type, the data is not stored in a single contiguous array that's accessible to any invocation. Instead, it's **distributed** across the invocations in the subgroup. + +Each invocation only owns a small piece of the matrix. You can think of it as the hardware "sharding" the matrix across its registers. This allows the GPU to use specialized hardware units (like **Tensor Cores** on NVIDIA or **Matrix Cores** on AMD) to perform the math directly on those registers without the overhead of traditional ALU instructions. + +Crucially, the operation happens at the **Subgroup Scope**. This means every invocation in a subgroup must participate in the load, multiply, and store operations simultaneously. If you try to call a cooperative matrix function inside a divergent branch where some members of the subgroup are inactive, you'll likely encounter undefined behavior or a GPU hang. + +The standard GEMM operation performed by these units is: +[latexmath] +++++ +D = A \times B + C +++++ +Where latexmath:[A] is an latexmath:[M \times K] matrix, latexmath:[B] is a latexmath:[K \times N] matrix, and latexmath:[C, D] are latexmath:[M \times N] matrices. + +== Memory Layout: Strides and Majorness + +When loading fragments from memory, you must specify how the matrix is laid out in your buffer. + +1. **Row-Major vs. Column-Major**: Most Vulkan applications prefer **Row-Major** (where elements of a row are contiguous). +2. **Stride**: This is the distance (in elements, not bytes) between the start of one row and the start of the next. For a simple tightly-packed matrix, the stride is equal to the number of columns. + +If your buffer contains a large matrix and you are only loading a small $16 \times 16$ tile, the stride would be the width of the *entire* large matrix. + +== Slang: Tiled Matrix Multiplication + +Slang treats cooperative matrices as first-class types, allowing for expressive tiled algorithms. Here is how you might implement a block of a larger matrix multiply: + +[source,slang] +---- +import slang_vulkan_compute; + +// Matrix dimensions supported by the physical device +const int M = 16; +const int N = 16; +const int K = 16; + +struct Params { + uint64_t addrA, addrB, addrC; + uint32_t strideA, strideB, strideC; + uint32_t totalK; +}; + +ParameterBlock cb; + +[numthreads(32, 1, 1)] // Subgroup size must match hardware expectations +void computeMain(uint3 threadId : SV_GroupThreadID, uint3 groupId : SV_GroupID) { + // Each subgroup handles one (M x N) tile of the output matrix C + CooperativeMatrix acc = 0.0f; + + // Loop over the K dimension in blocks of 'K' + for (uint32_t k = 0; k < cb.totalK; k += K) { + CooperativeMatrix matA; + CooperativeMatrix matB; + + // Load tiles from memory using Buffer Device Address + matA.load((float16*)cb.addrA, getOffsetA(groupId, k), cb.strideA); + matB.load((float16*)cb.addrB, getOffsetB(groupId, k), cb.strideB); + + // Accumulate product: acc = matA * matB + acc + acc = mul(matA, matB) + acc; + } + + // Store the final accumulated tile + acc.store((float*)cb.addrC, getOffsetC(groupId), cb.strideC); +} +---- + +== GLSL: The Low-Level Win + +While Slang makes the code look like standard matrix math, it's helpful to see the GLSL equivalent to understand the "win" that Vulkan 1.4 provides through the `GL_KHR_cooperative_matrix` extension. Note the explicit "Use" types which hint to the compiler how to optimize register allocation. + +[source,glsl] +---- +#extension GL_KHR_cooperative_matrix : enable +#extension GL_EXT_shader_explicit_arithmetic_types_float16 : enable + +// Define the fragments with explicit scopes and uses +layout(constant_id = 0) const int M = 16; +layout(constant_id = 1) const int N = 16; +layout(constant_id = 2) const int K = 16; + +// UseA and UseB are inputs, UseAccumulator is for C and D +coopmat matA; +coopmat matB; +coopmat acc; + +void main() { + // Explicit loading requires byte-offset and row-stride + coopMatLoad(matA, dataA, offsetA, strideA, gl_CooperativeMatrixLayoutRowMajor); + coopMatLoad(matB, dataB, offsetB, strideB, gl_CooperativeMatrixLayoutRowMajor); + + // acc = matA * matB + acc + acc = coopMatMulAdd(matA, matB, acc); + + coopMatStore(acc, dataC, offsetC, strideC, gl_CooperativeMatrixLayoutRowMajor); +} +---- + +== Hardware Constraints and Capabilities + +The physical dimensions (latexmath:[M, N, K]) are not arbitrary. You must query `VkPhysicalDeviceCooperativeMatrixPropertiesKHR` to find supported combinations. + +* **Subgroup Size**: On NVIDIA, these units typically expect a subgroup size of 32. On AMD, it might be 64. Using the wrong subgroup size in your `[numthreads]` will result in a failure to initialize the cooperative matrix types. +* **Precision Trade-offs**: It is standard practice to use `float16` for the input matrices (A and B) to maximize throughput and save bandwidth, while using `float32` for the accumulator (C and D). This "Mixed Precision GEMM" provides the best balance of speed and numerical stability. +* **Alignment**: Memory addresses passed to `.load()` and `.store()` usually require specific alignment (e.g., 16 bytes). Loading from a misaligned address can lead to a device lost error. + +By leveraging these specialized units, you can achieve throughput that is often an order of magnitude higher than what's possible with standard floating-point units. This makes cooperative matrices essential for any performance-critical linear algebra on the GPU. + +xref:01_introduction.adoc[Previous: Introduction] | xref:03_mixed_precision.adoc[Next: Mastering Mixed Precision] diff --git a/en/Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc b/en/Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc new file mode 100644 index 00000000..c74521f3 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc @@ -0,0 +1,103 @@ +:pp: {plus}{plus} += Mastering Mixed Precision: FP16 and Int8 + +In high-performance computing, we've traditionally relied on 32-bit floating-point precision (FP32) for almost everything. But as datasets grow larger and we demand higher throughput, it's worth asking: do we *really* need 32 bits for every single calculation? This is where **Mixed Precision** comes in. + +The core idea is simple: use lower-precision types like **FP16** (half-precision float) or **Int8** (8-bit integer) for the bulk of your calculations, and only use higher precision where it's absolutely necessary. Modern GPU architectures are heavily optimized for these lower-precision types. For example, many GPUs can perform twice as many FP16 operations as FP32 operations in the same amount of time. + +== Why Mixed Precision? + +There are two primary reasons to embrace lower precision: + +1. **Arithmetic Throughput**: Many modern GPUs have "packed" math units. A single 32-bit register can hold two 16-bit values, and the hardware can perform two 16-bit operations in the same cycle it would take for one 32-bit operation. +2. **Memory Bandwidth**: Data is expensive to move. By using 16-bit or 8-bit types, you're effectively doubling or quadrupling the amount of data you can move through the same memory bus. + +== Precision vs. Range: FP16 and BFloat16 + +When dropping from 32-bit to 16-bit, you have to choose what to sacrifice. + +* **FP16 (IEEE 754)**: 1 sign bit, 5 exponent bits, 10 mantissa bits. This provides decent precision but a very limited range (max value ~65,504). +* **BFloat16 (Brain Float)**: 1 sign bit, 8 exponent bits, 7 mantissa bits. This has the *same range* as FP32 but much lower precision. It's often preferred for machine learning because it's more robust to overflows. + +In Vulkan, FP16 is widely supported via the `VK_KHR_shader_float16_int8` extension, while BFloat16 is typically accessed through the `VK_KHR_shader_float_controls` or vendor-specific extensions. + +== Slang: Natural Mixed Precision + +Slang makes it incredibly easy to use mixed precision because it treats `half` and `int8_t` as native types. It handles the low-level conversion instructions for you. + +[source,slang] +---- +// Using half-precision in Slang +void computeMain() { + // 16-bit floats (h suffix) + half a = 1.0h; + half b = 2.0h; + + // Mixed accumulation: Perform 16-bit math, accumulate in 32-bit + float accumulator = 0.0f; + for(int i = 0; i < 100; i++) { + // Explicit cast to float to ensure the addition is 32-bit + accumulator += (float)(a * b); + } +} +---- + +== Int8 and Dot Products (DP4A) + +For even higher throughput, many GPUs support specialized instructions for 8-bit integer math. One of the most common is **DP4A** (Dot Product with 4-way Accumulation). + +The hardware takes two 32-bit registers, each containing four 8-bit values ($x_0, x_1, x_2, x_3$ and $y_0, y_1, y_2, y_3$). It performs: +[latexmath] +++++ +Result = (x_0 \times y_0) + (x_1 \times y_1) + (x_2 \times y_2) + (x_3 \times y_3) + Accumulator +++++ +All of this happens in a single cycle. In Slang, you can trigger this by using `dot` on packed 8-bit vectors: + +[source,slang] +---- +RWStructuredBuffer output; + +void computeMain(uint3 threadId : SV_DispatchThreadID) { + uint32_t packedA = loadPackedA(threadId.x); + uint32_t packedB = loadPackedB(threadId.x); + + // Reinterpret the uint32 as a vector of four 8-bit ints + int8_t4 vecA = BitCast(packedA); + int8_t4 vecB = BitCast(packedB); + + // The dot product intrinsic maps directly to DP4A hardware + int result = dot(vecA, vecB); + output[threadId.x] = result; +} +---- + +== C{pp} Side: Preparing the Data + +To feed these shaders, you must pack your data correctly on the CPU. Since standard C{pp} doesn't have a native 16-bit float type (until C{pp}23's `std::float16_t`), you'll often use a library like `glm` or perform manual bit-packing. + +[source,cpp] +---- +// Example of packing four 8-bit integers into one 32-bit uint +uint32_t packInt8(int8_t a, int8_t b, int8_t c, int8_t d) { + return (uint32_t(a) << 0) | (uint32_t(b) << 8) | + (uint32_t(c) << 16) | (uint32_t(d) << 24); +} + +// Uploading to a Vulkan buffer using RAII +void uploadData(vk::raii::Device& device, const std::vector& packedData) { + vk::BufferCreateInfo createInfo({}, packedData.size() * sizeof(uint32_t), + vk::BufferUsageFlagBits::eStorageBuffer); + vk::raii::Buffer storageBuffer(device, createInfo); + // ... bind memory and copy data ... +} +---- + +== Managing Dynamic Range: Loss Scaling + +The biggest challenge with mixed precision, particularly with **FP16**, is its limited **Dynamic Range**. FP16 has a much smaller range than FP32, which means it's much easier to **overflow** (exceed the maximum value) or **underflow** (become too small to represent). + +Managing this requires a technique known as **Loss Scaling**. You multiply your values by a scaling factor (e.g., 128.0) before performing your low-precision calculations to keep them within a safe range, and then divide by that same factor when you're done. + +By mastering mixed precision, you're not just "squeezing out more performance"; you're being smarter about how you use the hardware's resources. Whether you're optimizing a fluid simulation or a real-time signal processing engine, these techniques are essential for pushing the boundaries of what's possible on modern GPUs. + +xref:02_cooperative_matrices.adoc[Previous: Cooperative Matrices] | xref:../11_Performance_Optimization/01_introduction.adoc[Next: Performance Optimization] diff --git a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc b/en/Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc new file mode 100644 index 00000000..bea8d91b --- /dev/null +++ b/en/Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc @@ -0,0 +1,28 @@ +:pp: {plus}{plus} += Performance Auditing and Optimization + +We've covered a vast range of advanced Vulkan compute topics—from low-level architecture to high-level abstractions like SYCL. But there's one question that every developer eventually faces: "Is this as fast as it can be?" Answering this question is not about guesswork or intuition; it's about a rigorous, methodical approach to **Performance Auditing**. + +In the world of GPU compute, a "fast" kernel can be held back by many things. It might be waiting on memory (**memory-bound**), it might be overwhelmed by complex arithmetic (**compute-bound**), or it might be suffering from "divergence"—where different invocations in a **subgroup** (or **warp/wavefront**) are forced to take different execution paths, causing the hardware to serialize their work. + +Optimization is not just about writing "clever" code. It's about understanding the **bottlenecks**. If your kernel is memory-bound, adding more arithmetic operations won't slow it down, but it also won't make it faster. Conversely, if you're compute-bound, optimizing your memory access pattern might not yield any noticeable gains. + +== Moving Beyond Naive Optimization + +When we talk about optimization in a massively parallel environment like Vulkan, we need a standard set of metrics and models to guide us. In this chapter, we will introduce: + +* **The Roofline Model**: A fundamental analytical tool that allows us to visualize whether a kernel is limited by the peak bandwidth of **VRAM** (Video Random Access Memory) or the peak throughput of the **ALU** (Arithmetic Logic Unit). +* **Instruction Throughput Analysis**: Understanding the cost of individual **ISA** (Instruction Set Architecture) commands, and how to identify "heavy" operations like double-precision floats or complex transcendental functions. +* **Divergence Audits**: A methodology for identifying where **SIMD** (Single Instruction, Multiple Data) execution breaks down, causing lanes to sit idle while others work. + +We'll move beyond looking at high-level Slang or GLSL code and start thinking about what the hardware actually sees. This involves understanding the **Occupancy** of the **CU** (Compute Unit) or **SM** (Streaming Multiprocessor) and how to minimize **pipeline stalls** caused by memory latency. + +By the end of this chapter, you'll be equipped with the methodology to move from "making it work" to "making it fly." + +== Chapter Roadmap + +1. **Instruction Throughput Analysis**: Learning to identify compute-bound vs. memory-bound kernels using the Roofline Model. +2. **The Divergence Audit**: Techniques for visualizing and refactoring divergent branching logic. + +[horizontal] +*Previous:* xref:../10_Specialized_Math/03_mixed_precision.adoc[Mastering Mixed Precision] | *Next:* xref:02_instruction_throughput.adoc[Instruction Throughput Analysis] diff --git a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/02_instruction_throughput.adoc b/en/Advanced_Vulkan_Compute/11_Performance_Optimization/02_instruction_throughput.adoc new file mode 100644 index 00000000..fbd953e7 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/11_Performance_Optimization/02_instruction_throughput.adoc @@ -0,0 +1,49 @@ +:pp: {plus}{plus} += Analyzing Instruction Throughput: Compute-Bound vs. Memory-Bound + +Every GPU kernel has a "heartbeat"—a rate at which it processes instructions and accesses memory. Understanding this heartbeat is the key to effective optimization. To do this, we need to distinguish between two primary types of bottlenecks: **Compute-Bound** and **Memory-Bound**. + +== The Roofline Model + +A powerful way to visualize this is the **Roofline Model**. Imagine a graph where the x-axis is **Arithmetic Intensity** (the ratio of math operations to memory bytes accessed) and the y-axis is **Performance** (GFLOPS). + +The "roof" of this model is determined by the hardware's peak theoretical performance. + +* If your kernel has low arithmetic intensity (lots of memory access, little math), it's trapped on the "slope" of the roof—it's **Memory-Bound**. +* If your kernel has high arithmetic intensity, it hits the flat part of the roof—it's **Compute-Bound**. + +== Identifying the Bottleneck + +To identify these bottlenecks, you need to look at **Hardware Metrics** using profiling tools like NVIDIA Nsight, AMD Radeon GPU Profiler (RGP), or Intel VTune. + +=== Compute-Bound Kernels +A **Compute-Bound** kernel is one where the hardware's arithmetic units (**ALUs**) are fully occupied. These kernels are characterized by: + +* **High ALU Utilization**: The ALUs are active for a large percentage of the time. +* **Low Memory Throughput**: The memory bus is relatively idle. +* **Fix**: Simplify your math, use **Mixed Precision**, or leverage specialized units like **Cooperative Matrices**. + +=== Memory-Bound Kernels +A **Memory-Bound** kernel is one where the ALUs are often idle, waiting for data from VRAM. These kernels show: + +* **Low ALU Utilization**: The arithmetic units are "stalled" waiting for memory. +* **High VRAM Throughput**: You're hitting the hardware's bandwidth limits. +* **Fix**: Improve **Memory Coalescing**, use **Shared Memory (LDS)** to reuse data, or use **Subgroup Operations** to share data without touching VRAM. + +== Understanding Stall Reasons + +Modern profilers can tell you *why* a wavefront is stalled. Common reasons include: + +* **Instruction Fetch Stall**: The hardware can't fetch the next instruction fast enough (rare for compute). +* **Execution Stall**: The ALUs are busy with a long-running instruction (like a complex transcendental function). +* **Memory Dependency Stall**: The most common stall—the wavefront is waiting for a `load` from VRAM to complete. + +== Latency Hiding and Occupancy + +As we discussed in Chapter 2, the GPU hides memory latency by switching between active wavefronts. This is why **Occupancy** is so important. If you have low occupancy, the GPU might run out of "work" to do while it's waiting for memory, leading to idle ALUs and poor performance. + +However, be careful! Higher occupancy isn't always better. If your occupancy is too high, you might increase **Cache Contention**, where different wavefronts are constantly evicting each other's data from the L1 or L2 caches. Finding the "sweet spot" for occupancy is a critical part of the tuning process. + +Optimization is an iterative process. You profile, identify the bottleneck, apply a targeted fix, and then profile again. This is how you eventually arrive at a truly optimized solution that makes the most of the GPU's massive parallel potential. + +xref:01_introduction.adoc[Previous: Introduction] | xref:03_divergence_audit.adoc[Next: Divergence Audit] diff --git a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc b/en/Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc new file mode 100644 index 00000000..e94c7edf --- /dev/null +++ b/en/Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc @@ -0,0 +1,64 @@ +:pp: {plus}{plus} += The Divergence Audit: Identifying and Refactoring Branch Divergence + +One of the most insidious performance killers in GPU compute is **Branch Divergence**. To understand why, we need to remember that GPUs operate on groups of invocations (wavefronts or warps) that execute the same instruction in lock-step. When your code includes a branch—like an `if-else` statement—and some invocations in the subgroup take the `if` path while others take the `else` path, the hardware is forced to **serialize** those paths. + +The hardware will execute the `if` path for all relevant invocations (while masking out the others), and then it will execute the `else` path for the remaining invocations (masking out the first group). During this time, the ALUs for the inactive invocations are essentially idle, and you're effectively cutting your GPU's throughput in half. + +== Identifying Divergence + +A **Divergence Audit** is a methodical process for identifying where these "divergent" branches are occurring and refactoring your code to minimize their impact. + +=== Tool-Based Identification +Look for metrics in your profiler like **Active Lane Ratio** or **Instruction Execution Efficiency**. A low ratio indicates that many lanes in your subgroups are being idled by divergent control flow. + +For example, in NVIDIA Nsight, you might look at the "Warp Execution Efficiency" metric. If it's consistently below 50%, you likely have a significant divergence problem. + +=== In-Shader Visualization +You can also use **Subgroup Operations** (Chapter 4) to manually inspect divergence directly in your shader. By using `WaveActiveBallot()`, you can generate a bitmask of which invocations are taking a particular path. + +[source,slang] +---- +// Visualize divergence in your shader +bool local_test = data[globalID.x] > threshold; + +// Ballot tells us exactly which lanes in the subgroup are 'true' +uint4 lane_mask = WaveActiveBallot(local_test); + +// If only some lanes are true, we are divergent! +uint active_lanes = countbits(lane_mask.x) + countbits(lane_mask.y) + + countbits(lane_mask.z) + countbits(lane_mask.w); +---- + +== Refactoring Strategies + +Once you've identified a divergent branch, there are several ways to refactor it. + +=== Strategy 1: Subgroup-Level Branching +If a branch can be evaluated identically for all invocations in a subgroup, the hardware can execute it without any penalty. This is often called "Uniform Branching." + +[source,slang] +---- +// Refactored, subgroup-aware branch +bool local_test = data[globalID.x] > threshold; + +if (WaveActiveAllTrue(local_test)) { + // Fast path: everyone is doing the same work! + do_complex_work_fast(); +} else if (WaveActiveAnyTrue(local_test)) { + // Slow path: only some are doing work, but we only enter if necessary + do_complex_work_slow(); +} +---- + +=== Strategy 2: Replacing Control Flow with Data Flow +A more advanced technique is to **Replace Control Flow with Data Flow**. Instead of using an `if` to choose between two calculations, you can perform both and use a mathematical trick to select the result. This keeps the execution pipeline "saturated" and avoids the serialization penalty of branching. + +Functions like `lerp()`, `clamp()`, and `step()` are your best friends here. In many cases, performing a few extra arithmetic operations is faster than the cost of a divergent branch. + +=== Strategy 3: Work Sorting +If your divergence is caused by processing different types of data (e.g., in a ray tracer where some rays hit a complex material and others hit a simple one), you can use a **sorting pass** to group similar workloads together. By ensuring that all invocations in a subgroup are processing the same type of data, you can eliminate divergence entirely at the cost of the sort. + +By conducting regular divergence audits, you can identify the "hidden" costs in your compute kernels and refactor them into more efficient, SIMD-friendly patterns. This is the difference between code that "just runs" and code that truly masters the GPU's architecture. + +xref:02_instruction_throughput.adoc[Previous: Instruction Throughput Analysis] | xref:../12_Diagnostics_and_Refinement/01_introduction.adoc[Next: Diagnostics and Refinement] diff --git a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc b/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc new file mode 100644 index 00000000..3e0c93b4 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc @@ -0,0 +1,28 @@ +:pp: {plus}{plus} += Diagnostics and AI-Assisted Compute Refinement: Introduction + +== Overview + +In this final chapter, we're going to explore the modern landscape of Vulkan compute development. As our kernels become more complex and our orchestration more elaborate, the traditional methods of debugging and optimization can sometimes feel inadequate. If you've spent any time writing compute shaders, you know the frustration: your code compiles, your dispatch returns success, but your output buffer is full of zeros—or worse, your entire system hangs with a "Device Lost" error. + +The GPU is often described as a "**Black Box**"—a powerful processor that performs millions of operations in parallel but offers very little visibility into what's actually happening inside. Unlike C{pp} code on the CPU, you can't easily set a breakpoint, step through your logic line by line, or inspect the state of every register. To build robust and efficient compute pipelines, we need a new set of tools and a new way of thinking about the development process. + +== The Diagnostic Pillars + +To pull back the curtain on the GPU, we'll focus on two modern techniques for runtime verification: + +* **GPU-Assisted Validation (GAV)**: This is a powerful feature of the Vulkan validation layers. Instead of just checking if your API calls are valid, GAV actually injects small amounts of diagnostic code directly into your shaders at runtime. This process, known as **instrumentation**, allows the layers to detect errors that would otherwise go completely unnoticed—from **Out-of-Bounds (OOB)** buffer access to invalid pointer dereferences when using **Buffer Device Address (BDA)**. +* **Shader printf**: We'll explore how to use standard `printf` logic inside a shader to "see" the values of your variables across thousands of parallel invocations. While it might seem primitive, in a massively parallel environment, it's often the only way to track down subtle logic errors. + +== AI-Assisted Development + +Finally, we'll look at the emerging role of **AI-Assisted Optimization**. **Large Language Models (LLMs)**—AI models trained on vast amounts of code—are becoming increasingly adept at understanding shader code and suggesting parallel-friendly refactors. + +Whether you're struggling to vectorize a naive loop or looking for a more efficient **Subgroup** pattern (using the **Wave** operations we learned in Chapter 4), an AI assistant can be a valuable partner in your development process. However, as we'll see, the key to using AI effectively is knowing how to "talk" to it using the specific **terms of art** we've mastered in this series—like **LDS (Local Data Store)**, **Barriers**, and **Occupancy**. + +== Chapter Roadmap + +1. **Compute Validation**: Setting up and using GPU-Assisted Validation to catch memory errors and using `printf` for shader debugging. +2. **Assistant-Led Optimization**: Leveraging AI to refactor naive compute kernels into wave-aware, high-performance patterns. + +xref:../11_Performance_Optimization/03_divergence_audit.adoc[Previous: Divergence Audit] | xref:02_compute_validation.adoc[Next: Compute Validation] diff --git a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc b/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc new file mode 100644 index 00000000..6f364287 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc @@ -0,0 +1,71 @@ +:pp: {plus}{plus} += Compute Validation and GPU-Assisted Debugging + +Debugging a compute shader is notoriously difficult. Unlike CPU code, you can't easily set a breakpoint or step through your logic line by line. Most errors—like an out-of-bounds buffer access—will simply result in garbage data or, in the worst-case scenario, a "Device Lost" error that provides almost no information about what went wrong. + +== GPU-Assisted Validation (GAV) + +This is where **GPU-Assisted Validation** (GAV) comes in. Part of the standard Vulkan Validation Layers, GAV works by injecting small amounts of diagnostic code directly into your shaders at runtime. This **instrumentation** allows the layers to track and report errors that would otherwise be invisible. + +=== Enabling GAV in C++ +To enable GAV, you configure the `vk::ValidationFeaturesEXT` structure when creating your Vulkan instance. + +[source,cpp] +---- +// Enabling GPU-Assisted Validation via RAII +std::vector enabledFeatures = { + vk::ValidationFeatureEnableEXT::eGpuAssisted, + vk::ValidationFeatureEnableEXT::eGpuAssistedReserveBindingSlot +}; + +vk::ValidationFeaturesEXT validationFeatures { + .enabledValidationFeatureCount = static_cast(enabledFeatures.size()), + .pEnabledValidationFeatures = enabledFeatures.data() +}; + +vk::InstanceCreateInfo createInfo { + .pNext = &validationFeatures, + // ... other setup ... +}; +---- + +=== What GAV Detects +* **Out-of-Bounds Access**: If you try to read from `data[100]` when the buffer only has 50 elements, GAV will catch it. +* **Invalid Pointers**: When using **Buffer Device Address (BDA)**, GAV can detect if you're dereferencing a null or invalid pointer. +* **Uninitialized Descriptors**: It ensures that every descriptor your shader touches has been correctly bound and initialized. + +== Shader Printf: Seeing Inside the Kernel + +While GAV is great for catching errors, sometimes you just need to see the values of your variables. This is where `debugPrintfEXT` (from the `GL_EXT_debug_printf` extension) becomes your best friend. + +=== In the Shader (Slang) +Slang supports `printf` directly, which maps to the underlying Vulkan extension. + +[source,slang] +---- +// Using printf in a compute shader +void computeMain(uint3 globalID : SV_DispatchThreadID) { + float some_value = calculate_complex_math(globalID.x); + + if (some_value < 0.0f) { + // Output will appear in your application's debug callback + printf("Thread %d: Warning! Negative value detected: %f\n", globalID.x, some_value); + } +} +---- + +=== In the Host Code +To see the output from `printf`, you must: +1. Enable the `VK_KHR_shader_non_semantic_info` extension on your device. +2. Have a standard **Debug Messenger** callback registered. The output from your shader will arrive as a `VkDebugUtilsMessengerCallbackDataEXT` with a message ID that identifies it as a printf call. + +== Interpreting the Output + +When a validation error or a `printf` occurs, the output can be verbose. Look for: +* **The Shader Module**: Which shader triggered the message. +* **The Instruction Offset**: The specific SPIR-V instruction that failed. +* **The Value**: For `printf`, this is your formatted string. For GAV, it might be the invalid index or pointer address. + +While GAV and `printf` have a significant performance cost, they are indispensable for development. They turn the "black box" of the GPU into a transparent environment where you can build complex, reliable compute pipelines with confidence. + +xref:01_introduction.adoc[Previous: Introduction] | xref:03_assistant_led_optimization.adoc[Next: AI-Assisted Optimization] diff --git a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc b/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc new file mode 100644 index 00000000..a9974b00 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc @@ -0,0 +1,67 @@ +:pp: {plus}{plus} += AI-Assisted Optimization and Refinement + +The field of GPU compute is evolving rapidly, and the sheer complexity of advanced Vulkan compute can sometimes feel overwhelming. This is where **AI-Assisted Optimization**—leveraging Large Language Models (LLMs) to analyze and refactor your code—is becoming a game-changer. + +== The New Workflow + +As a Vulkan developer, you're no longer alone in the optimization process. Modern AI assistants can act as a second pair of eyes, helping you navigate the pitfalls of SIMD architecture and memory consistency. + +=== Example: From Naive to Wave-Aware +Imagine you have a naive loop that calculates a prefix sum across a buffer. + +[source,slang] +---- +// Naive approach: One thread does all the work in a loop +void computeMain(uint3 globalID : SV_DispatchThreadID) { + if (globalID.x == 0) { + uint total = 0; + for (uint i = 0; i < bufferSize; i++) { + total += data[i]; + data[i] = total; + } + } +} +---- + +An AI assistant can instantly recognize this as a sequential bottleneck and suggest a **Subgroup-Aware** (Wave) refactoring using the techniques we discussed in Chapter 4. + +[source,slang] +---- +// AI-Suggested Refactor: Parallel prefix sum using Wave operations +void computeMain(uint3 globalID : SV_DispatchThreadID) { + uint val = data[globalID.x]; + + // Perform a parallel prefix sum within the subgroup + uint inclusive_sum = WavePrefixSum(val) + val; + + // WaveReadLaneAt allows us to get the total from the last lane + uint subgroup_total = WaveReadLaneAt(inclusive_sum, WaveGetLaneCount() - 1); + + // ... further logic to combine subgroup totals ... + data[globalID.x] = inclusive_sum; +} +---- + +== Effective Prompting for Shaders + +To get the most out of an AI assistant, you need to provide **Context**. Don't just paste your code; explain the constraints: + +* **"Refactor this Slang shader to use Wave operations for better throughput."** +* **"Identify potential bank conflicts in this groupshared memory access pattern."** +* **"How can I use Buffer Device Address to optimize this tree traversal?"** + +By framing your questions with the specific terms of art we've learned in this series—like **Subgroups**, **LDS**, **BDA**, and **Barriers**—you'll receive much more accurate and actionable suggestions. + +== The Golden Rule: Trust but Verify + +It's crucial to remember that an AI assistant is just that—an **assistant**. While it's great for generating suggestions and identifying patterns, you are still the primary architect. + +1. **Verify Correctness**: AI-generated code can sometimes have subtle bugs, especially with complex synchronization. Always run your code through **GPU-Assisted Validation** (Chapter 12, Section 2). +2. **Profile Performance**: A "clever" refactor might actually be slower on certain hardware. Always verify the AI's suggestions with a **Divergence Audit** or an **Instruction Throughput Analysis** (Chapter 11). + +== Closing the Loop + +As we move toward the final conclusion of this series, we've seen how modern tools like GPU-Assisted Validation and AI-led refactoring can transform the compute development workflow. In the next section, we'll summarize everything we've learned and look ahead to the future of high-performance Vulkan compute. + +xref:02_compute_validation.adoc[Previous: Compute Validation] | xref:../conclusion.adoc[Next: Series Conclusion] diff --git a/en/Advanced_Vulkan_Compute/conclusion.adoc b/en/Advanced_Vulkan_Compute/conclusion.adoc new file mode 100644 index 00000000..5701b80a --- /dev/null +++ b/en/Advanced_Vulkan_Compute/conclusion.adoc @@ -0,0 +1,50 @@ +:pp: {plus}{plus} += Advanced Vulkan Compute: Conclusion + +Congratulations on completing the "Advanced Vulkan Compute" tutorial series! You have traveled from the basic concepts of compute shaders to the cutting edge of high-performance GPGPU development in Vulkan 1.4. + +== What We've Learned + +Throughout this series, we have explored the depths of modern GPU compute, moving beyond simple image processing into complex, heterogeneous systems: + +1. **Compute Architecture**: We mastered the mapping between workgroup grids and physical hardware (CUs and SMs), and learned how to maximize occupancy and hide latency. We also utilized Vulkan 1.4's scalar layouts for maximum bandwidth efficiency. +2. **Memory Models**: We demystified the Vulkan Memory Model, mastering availability, visibility, and domain operations to ensure thread safety without sacrificing performance. +3. **Subgroup Power**: We utilized subgroup shuffles, broadcasts, and arithmetic to exchange data at hardware speed, bypassing VRAM and shared memory (LDS) entirely. +4. **Heterogeneous Ecosystems**: We explored bridging legacy code with OpenCL (clspv/clvk) and modernizing development with single-source SYCL (AdaptiveCpp). +5. **Advanced Data Structures**: We implemented GPU-resident trees, lock-free linked lists, and utilized raw Buffer Device Addresses (BDA) for pointer-like flexibility. +6. **GPU-Driven Pipelines**: We transitioned control from the CPU to the GPU using indirect dispatches and autonomous command generation. +7. **Asynchronous Orchestration**: We harnessed the power of multiple hardware engines to run compute concurrently with graphics using Synchronization 2 and Timeline Semaphores. +8. **Specialized Math**: We utilized modern hardware features like Cooperative Matrices and mixed-precision (FP16/Int8) for massive throughput. +9. **Performance & Diagnostics**: We learned to audit our kernels for divergence, analyze throughput with the Roofline model, and debug complex race conditions with GPU-Assisted Validation (GAV). +10. **AI-Assisted Optimization**: We've seen how Large Language Models (LLMs) can act as a bridge between naive, sequential logic and the parallel, subgroup-aware patterns that are necessary for high GPU throughput. + +== Making it Click: The Compute Mindset + +If there is one takeaway from this series, it is this: **The GPU is not just a math coprocessor; it is a parallel throughput machine with its own complex hierarchy.** + +Developing for advanced compute requires a shift in mindset: +- **Think in Waves**: Always look for opportunities to use subgroup (Wave) operations instead of workgroup-level barriers. +- **Explicit Synchronization**: Don't rely on luck. Use the Vulkan Memory Model and Synchronization 2 to define exactly how and when data becomes visible. +- **Data-First Design**: Design your data structures for the GPU's memory architecture (scalar layouts, LDS bank alignment) before you write a single line of logic. + +== Where to Go From Here + +The world of high-performance computing is vast. Now that you have a solid foundation, consider these paths: + +1. **Deep Dive into Machine Learning**: Use what you've learned about Cooperative Matrices and Mixed Precision to optimize neural network inference or training. +2. **Real-Time Path Tracing**: Combine GPU-Driven pipelines and Asynchronous Compute to build a high-performance ray tracer that handles complex spatial structures entirely on the device. +3. **Physical Simulations**: Implement advanced fluid dynamics (SPH) or rigid body solvers using the lock-free data structures we discussed. +4. **Vulkan Ecosystem**: Contribute to projects like `clspv`, `clvk`, or `AdaptiveCpp`, or build your own high-level compute abstraction. + +== Community and Resources + +As always, you are not alone in this journey. The Vulkan community is filled with experts and enthusiasts: +- **Khronos Slack/Discord**: Great for technical deep dives into specific extensions. +- **Vulkan Specification**: Your ultimate source of truth for memory models and hardware constraints. +- **Vendor-Specific Documentation**: Explore NVIDIA's Nsight, AMD's RGP, and Intel's GPA documentation for hardware-specific optimization tricks. + +Thank you for following along with this series. We've moved from "making pixels pretty" to harnessing the full parallel power of modern hardware. The only limit now is your imagination. + +Happy Hacking! + +xref:12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Previous: Assistant-Led Optimization] | xref:../00_Introduction.adoc[Back to Home] diff --git a/en/Advanced_Vulkan_Compute/introduction.adoc b/en/Advanced_Vulkan_Compute/introduction.adoc new file mode 100644 index 00000000..6e2e6e23 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/introduction.adoc @@ -0,0 +1,64 @@ +:pp: {plus}{plus} + += Advanced Vulkan Compute: The Power of Parallelism + +== Introduction + +Welcome to the "Advanced Vulkan Compute" tutorial series! This series is designed for developers who have mastered the basics of Vulkan compute shaders and are looking to push the boundaries of what's possible with modern GPU hardware. + +Vulkan is not just a graphics API; it is a powerful, low-level framework for general-purpose GPU programming (GPGPU). While the initial tutorials covered how to dispatch a simple compute shader, this series dives deep into the architecture, memory models, and advanced features that enable high-performance simulations, complex data structures, and heterogeneous execution. + +=== Beyond the Basics + +In a basic compute shader, you might just be multiplying an array of floats. In advanced compute, you are: + +* **Orchestrating thousands of threads** to work together on a single problem. +* **Managing memory consistency** to ensure that data written by one thread is safely read by another. +* **Leveraging specialized hardware** like subgroup shuffles and cooperative matrices to bypass slow **VRAM** (Video Random Access Memory). +* **Building GPU-resident data structures** like **BVH** (Bounding Volume Hierarchies) and Octrees that never need to touch the CPU. + +To do this effectively, you need more than just a passing knowledge of GLSL or Slang; you need to understand the underlying hardware architecture and the Vulkan execution model. + +=== What You Will Learn + +This tutorial series is organized into several key areas: + +1. **Compute Architecture** - Mapping workgroups to Compute Units (CU) and Streaming Multiprocessors (SM), and mastering occupancy. +2. **Memory Models and Consistency** - Understanding the Vulkan Memory Model, shared memory (**LDS** - Local Data Store), and fine-grained synchronization. +3. **Subgroup Operations** - Using cross-invocation communication to avoid VRAM round-trips and maximize **SIMD** (Single Instruction, Multiple Data) throughput. +4. **Heterogeneous Ecosystems** - Running OpenCL C and SYCL code on top of Vulkan using `clspv`, `clvk`, and AdaptiveCpp. +5. **Advanced Data Structures** - Moving complex structures like trees and linked lists entirely to the GPU using 64-bit atomics and **BDA** (Buffer Device Address). +6. **GPU-Driven Pipelines** - Moving command generation and workload management entirely to the GPU for autonomous execution. +7. **Asynchronous Orchestration** - Running compute and graphics concurrently using Synchronization 2 and multiple hardware queues. +8. **Advanced Math & Optimization** - Using Cooperative Matrices for linear algebra and auditing kernels for divergence and throughput. + +=== Prerequisites + +This series assumes you are comfortable with: + +* Standard Vulkan initialization (Instance, Device, Queues). +* Basic Compute Pipelines and Descriptor Sets. +* C{pp}20 and GLSL/Slang shader languages. +* The concepts covered in the xref:11_Compute_Shader.adoc[Compute Shader] chapter of the main tutorial. + +=== How to Use This Tutorial + +Each chapter is designed to be self-contained but builds on the concepts of previous ones. We recommend following them in order if you're new to advanced compute, or jumping to specific sections if you're looking to solve a particular problem. + +Let's dive into the world of high-performance GPU computing! + +== Chapters + +* xref:02_Compute_Architecture/01_introduction.adoc[The Compute Architecture and Execution Model] +* xref:03_Memory_Models/01_introduction.adoc[Memory Models and Consistency] +* xref:04_Subgroup_Operations/01_introduction.adoc[Subgroup Operations: The Hidden Power] +* xref:05_OpenCL_on_Vulkan/01_introduction.adoc[Heterogeneous Ecosystem: OpenCL on Vulkan] +* xref:06_SYCL_and_Single_Source_CPP/01_introduction.adoc[High-Level Abstraction: SYCL and Single-Source C{pp}] +* xref:07_Advanced_Data_Structures/01_introduction.adoc[Advanced Data Structures on the GPU] +* xref:08_GPU_Driven_Pipelines/01_introduction.adoc[Indirect Dispatch and GPU-Driven Pipelines] +* xref:09_Asynchronous_Compute/01_introduction.adoc[Asynchronous Compute Orchestration] +* xref:10_Specialized_Math/01_introduction.adoc[Cooperative Matrices and Specialized Math] +* xref:11_Performance_Optimization/01_introduction.adoc[Performance Auditing and Optimization] +* xref:12_Diagnostics_and_Refinement/01_introduction.adoc[Diagnostics and AI-Assisted Compute Refinement] + +xref:11_Compute_Shader.adoc[Previous: Basic Compute Shaders] | xref:02_Compute_Architecture/01_introduction.adoc[Next: Compute Architecture] \ No newline at end of file From b7fc0c964c0f8642da7e2e7ccb02da57ec041569 Mon Sep 17 00:00:00 2001 From: swinston Date: Mon, 16 Mar 2026 15:38:20 -0700 Subject: [PATCH 2/5] Fix formatting in Advanced Vulkan Compute conclusion section Add missing blank lines after list introduction paragraphs to ensure proper Markdown rendering of bullet points in "Developing for advanced compute" and "Community and Resources" sections. --- en/Advanced_Vulkan_Compute/conclusion.adoc | 2 ++ 1 file changed, 2 insertions(+) diff --git a/en/Advanced_Vulkan_Compute/conclusion.adoc b/en/Advanced_Vulkan_Compute/conclusion.adoc index 5701b80a..a126e038 100644 --- a/en/Advanced_Vulkan_Compute/conclusion.adoc +++ b/en/Advanced_Vulkan_Compute/conclusion.adoc @@ -23,6 +23,7 @@ Throughout this series, we have explored the depths of modern GPU compute, movin If there is one takeaway from this series, it is this: **The GPU is not just a math coprocessor; it is a parallel throughput machine with its own complex hierarchy.** Developing for advanced compute requires a shift in mindset: + - **Think in Waves**: Always look for opportunities to use subgroup (Wave) operations instead of workgroup-level barriers. - **Explicit Synchronization**: Don't rely on luck. Use the Vulkan Memory Model and Synchronization 2 to define exactly how and when data becomes visible. - **Data-First Design**: Design your data structures for the GPU's memory architecture (scalar layouts, LDS bank alignment) before you write a single line of logic. @@ -39,6 +40,7 @@ The world of high-performance computing is vast. Now that you have a solid found == Community and Resources As always, you are not alone in this journey. The Vulkan community is filled with experts and enthusiasts: + - **Khronos Slack/Discord**: Great for technical deep dives into specific extensions. - **Vulkan Specification**: Your ultimate source of truth for memory models and hardware constraints. - **Vendor-Specific Documentation**: Explore NVIDIA's Nsight, AMD's RGP, and Intel's GPA documentation for hardware-specific optimization tricks. From b96b2e75429d41abd80b6394294227e747744421 Mon Sep 17 00:00:00 2001 From: swinston Date: Tue, 9 Jun 2026 22:56:04 -0700 Subject: [PATCH 3/5] Remove SYCL and Single-Source C++ tutorial section from Advanced Vulkan Compute chapter Address all feedback received thus far. --- .../05_OpenCL_on_Vulkan/01_introduction.adoc | 14 ++-- .../05_clvk_and_layering.adoc | 6 +- .../01_introduction.adoc | 2 +- .../02_gpu_resident_trees.adoc | 0 .../03_global_atomic_management.adoc | 0 .../04_device_addressable_buffers.adoc | 4 +- .../01_introduction.adoc | 39 ----------- .../02_setup_and_installation.adoc | 69 ------------------- .../03_single_source_gpgpu.adoc | 62 ----------------- .../04_vulkan_interoperability.adoc | 53 -------------- .../05_unified_shared_memory_usm.adoc | 53 -------------- .../01_introduction.adoc | 2 +- .../02_indirect_dispatch.adoc | 0 .../03_gpu_side_command_generation.adoc | 0 .../04_multi_draw_indirect_mdi.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_concurrent_execution.adoc | 0 .../03_timeline_semaphores.adoc | 0 .../04_queue_priority.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_cooperative_matrices.adoc | 0 .../03_mixed_precision.adoc | 2 +- .../01_introduction.adoc | 4 +- .../02_instruction_throughput.adoc | 0 .../03_divergence_audit.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_compute_validation.adoc | 2 + .../03_assistant_led_optimization.adoc | 0 en/Advanced_Vulkan_Compute/conclusion.adoc | 6 +- en/Advanced_Vulkan_Compute/introduction.adoc | 15 ++-- 30 files changed, 37 insertions(+), 308 deletions(-) rename en/Advanced_Vulkan_Compute/{07_Advanced_Data_Structures => 06_Advanced_Data_Structures}/01_introduction.adoc (93%) rename en/Advanced_Vulkan_Compute/{07_Advanced_Data_Structures => 06_Advanced_Data_Structures}/02_gpu_resident_trees.adoc (100%) rename en/Advanced_Vulkan_Compute/{07_Advanced_Data_Structures => 06_Advanced_Data_Structures}/03_global_atomic_management.adoc (100%) rename en/Advanced_Vulkan_Compute/{07_Advanced_Data_Structures => 06_Advanced_Data_Structures}/04_device_addressable_buffers.adoc (93%) delete mode 100644 en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc delete mode 100644 en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc delete mode 100644 en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc delete mode 100644 en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc delete mode 100644 en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc rename en/Advanced_Vulkan_Compute/{08_GPU_Driven_Pipelines => 07_GPU_Driven_Pipelines}/01_introduction.adoc (97%) rename en/Advanced_Vulkan_Compute/{08_GPU_Driven_Pipelines => 07_GPU_Driven_Pipelines}/02_indirect_dispatch.adoc (100%) rename en/Advanced_Vulkan_Compute/{08_GPU_Driven_Pipelines => 07_GPU_Driven_Pipelines}/03_gpu_side_command_generation.adoc (100%) rename en/Advanced_Vulkan_Compute/{08_GPU_Driven_Pipelines => 07_GPU_Driven_Pipelines}/04_multi_draw_indirect_mdi.adoc (97%) rename en/Advanced_Vulkan_Compute/{09_Asynchronous_Compute => 08_Asynchronous_Compute}/01_introduction.adoc (97%) rename en/Advanced_Vulkan_Compute/{09_Asynchronous_Compute => 08_Asynchronous_Compute}/02_concurrent_execution.adoc (100%) rename en/Advanced_Vulkan_Compute/{09_Asynchronous_Compute => 08_Asynchronous_Compute}/03_timeline_semaphores.adoc (100%) rename en/Advanced_Vulkan_Compute/{09_Asynchronous_Compute => 08_Asynchronous_Compute}/04_queue_priority.adoc (98%) rename en/Advanced_Vulkan_Compute/{10_Specialized_Math => 09_Specialized_Math}/01_introduction.adoc (96%) rename en/Advanced_Vulkan_Compute/{10_Specialized_Math => 09_Specialized_Math}/02_cooperative_matrices.adoc (100%) rename en/Advanced_Vulkan_Compute/{10_Specialized_Math => 09_Specialized_Math}/03_mixed_precision.adoc (98%) rename en/Advanced_Vulkan_Compute/{11_Performance_Optimization => 10_Performance_Optimization}/01_introduction.adoc (86%) rename en/Advanced_Vulkan_Compute/{11_Performance_Optimization => 10_Performance_Optimization}/02_instruction_throughput.adoc (100%) rename en/Advanced_Vulkan_Compute/{11_Performance_Optimization => 10_Performance_Optimization}/03_divergence_audit.adoc (98%) rename en/Advanced_Vulkan_Compute/{12_Diagnostics_and_Refinement => 11_Diagnostics_and_Refinement}/01_introduction.adoc (97%) rename en/Advanced_Vulkan_Compute/{12_Diagnostics_and_Refinement => 11_Diagnostics_and_Refinement}/02_compute_validation.adoc (99%) rename en/Advanced_Vulkan_Compute/{12_Diagnostics_and_Refinement => 11_Diagnostics_and_Refinement}/03_assistant_led_optimization.adoc (100%) diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc index 6ea877f1..4d3662ad 100644 --- a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc @@ -16,14 +16,16 @@ You might wonder why we would want to run "legacy" OpenCL code on a modern API l 2. **Cross-Vendor Compatibility**: Not all hardware vendors provide a high-quality, native OpenCL driver (especially on mobile or integrated GPUs). By layering OpenCL on top of Vulkan, you can provide an OpenCL implementation wherever Vulkan is available. 3. **Unified Tooling**: If your application already uses Vulkan for rendering, being able to handle compute workloads through the same API simplifies your synchronization, memory management, and deployment. -== The "Vulkan Flavor" of OpenCL +== OpenCL on Vulkan: Standard, Not Special -It's important to understand that we aren't just running OpenCL as-is. We are using a specific "Vulkan-compatible" subset of OpenCL. This involves: +A key insight from conformant layered implementations like `clvk` is that OpenCL-on-Vulkan looks and behaves like **any other OpenCL implementation** from the application's perspective. You use the same `clCreateContext`, `clEnqueueNDRangeKernel`, and other standard OpenCL 3.0 calls. The Vulkan layer underneath is an implementation detail. -* **SPIR-V as the Bridge**: OpenCL C kernels are compiled into **SPIR-V** (Standard Portable Intermediate Representation - V), the same binary format used by Vulkan for its shaders. -* **Memory Mapping**: Mapping OpenCL's pointer-based memory model (Buffers and Images) to Vulkan's explicit memory management. -* **Execution Models**: Aligning OpenCL's global and local work sizes with Vulkan's workgroups and invocations. +What makes this interesting from a Vulkan developer's perspective is the **advanced Vulkan features** that make a conformant OpenCL implementation possible: -In this chapter, we'll explore the two primary ways to bridge this gap: **AOT** (Ahead-of-Time, compiling before the program runs) compilation using `clspv`, and **Runtime Layering** using `clvk`. +* **SPIR-V as the Bridge**: OpenCL C kernels are compiled into **SPIR-V** (Standard Portable Intermediate Representation - V), the same binary format used by Vulkan for its shaders. This is the key integration point — Vulkan's shader format is flexible enough to express OpenCL semantics. +* **Variable Pointers and Buffer Device Address**: OpenCL's pointer-based memory model requires Vulkan's `VK_KHR_variable_pointers` (core in Vulkan 1.1) and the **Buffer Device Address** feature to emulate flat address spaces efficiently. +* **Subgroup Extensions**: OpenCL's work-group collective operations map directly to Vulkan's subgroup operations, enabling hardware-accelerated reductions and scans. + +In this chapter, we'll explore the two primary tools: **AOT** (Ahead-of-Time) compilation using `clspv`, and **Runtime Layering** using `clvk`. xref:../04_Subgroup_Operations/04_non_uniform_indexing.adoc[Previous: Non-Uniform Indexing] | xref:02_setup_and_installation.adoc[Next: Setup and Installation] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc index e9e6ff4c..a76c32e0 100644 --- a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc @@ -23,6 +23,8 @@ The biggest advantage of `clvk` is **Portability without Rewrite**. If you have a large desktop application written in C{pp} that uses OpenCL, you can run it on an Android device or a Vulkan-only Linux system simply by linking it against the `clvk` library. You don't have to touch a single line of your host code or your kernels. +Importantly, `clvk` implements OpenCL 3.0 **conformantly** — your application does not need to know it is running on top of Vulkan. From the host code perspective, it behaves identically to a native OpenCL driver. This is the correct design: a layered implementation should be invisible to the application. + This is great for cross-platform developers who want to target as many devices as possible with a single codebase. == Performance Considerations @@ -35,6 +37,6 @@ Since the actual computation happens in the native Vulkan driver, the primary co `clvk` supports most of the OpenCL 3.0 specification. However, its compatibility depends on the features supported by your Vulkan driver. If your driver supports Vulkan 1.4 with **Descriptor Indexing**, **Variable Pointers**, and **Buffer Device Address**, `clvk` will be able to support almost all OpenCL features. -In the next chapter, we'll move from the OpenCL ecosystem to the modern C{pp} world of **SYCL**, which takes this abstraction even further. +In the next chapter, we'll move from the OpenCL ecosystem to **Advanced Data Structures on the GPU** — GPU-resident trees, lock-free linked lists, and raw Buffer Device Addresses. -xref:04_kernel_portability.adoc[Previous: Kernel Portability] | xref:../06_SYCL_and_Single_Source_CPP/01_introduction.adoc[Next: SYCL and Single-Source C{pp}] +xref:04_kernel_portability.adoc[Previous: Kernel Portability] | xref:../06_Advanced_Data_Structures/01_introduction.adoc[Next: Advanced Data Structures] diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc similarity index 93% rename from en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc rename to en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc index a1ef9a7a..37d0387a 100644 --- a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc @@ -29,4 +29,4 @@ GPU-resident data structures are the foundation of modern high-performance rende By the end of this chapter, you'll understand how to stop treating the GPU as a "dumb array processor" and start treating it as a platform for autonomous, complex data management. -xref:../06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc[Previous: Unified Shared Memory (USM)] | xref:02_gpu_resident_trees.adoc[Next: GPU-Resident Trees] +xref:../05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[Previous: clvk and Layering] | xref:02_gpu_resident_trees.adoc[Next: GPU-Resident Trees] diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/02_gpu_resident_trees.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/02_gpu_resident_trees.adoc rename to en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/03_global_atomic_management.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/03_global_atomic_management.adoc rename to en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc diff --git a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc similarity index 93% rename from en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc rename to en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc index 7b3b0920..572ae3dd 100644 --- a/en/Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc +++ b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc @@ -84,7 +84,7 @@ While the Slang syntax is much closer to C{pp}, both produce the same low-level 1. **Zero Binding Overhead**: You can pass thousands of buffer addresses to a single shader via a single push constant or a "pointer buffer," completely bypassing the CPU cost of managing descriptor pools and sets. 2. **Complex Data Structures**: You can build real linked lists, trees, and graphs where nodes contain actual 64-bit pointers to other nodes, allowing for "pointer chasing" that was previously impossible. -3. **Heterogeneous Programming**: BDA is the foundation for SYCL's **Unified Shared Memory (USM)**. It bridges the gap between the pointer-based world of C{pp} and the explicit world of Vulkan. +3. **Heterogeneous Programming**: BDA enables pointer-based GPU memory models, bridging the gap between the pointer-based world of C{pp} and the explicit world of Vulkan — the same foundation that higher-level compute APIs use for unified pointer semantics. === The Cost of Freedom: Safety and Performance @@ -98,4 +98,4 @@ By combining 64-bit atomics, subgroup operations, and raw buffer device addresse In the next chapter, we'll see how to take this a step further and use these structures to drive the entire rendering pipeline directly from the GPU: **Indirect Dispatch and GPU-Driven Pipelines**. -xref:03_global_atomic_management.adoc[Previous: Global Atomic Management] | xref:../08_GPU_Driven_Pipelines/01_introduction.adoc[Next: Indirect Dispatch] +xref:03_global_atomic_management.adoc[Previous: Global Atomic Management] | xref:../07_GPU_Driven_Pipelines/01_introduction.adoc[Next: Indirect Dispatch] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc deleted file mode 100644 index 786d78d4..00000000 --- a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc +++ /dev/null @@ -1,39 +0,0 @@ -:pp: {plus}{plus} - -= High-Level Abstraction: SYCL and Single-Source C{pp} - -== Introduction - -In the previous chapters, we've focused on the "explicit" way of doing compute: writing kernels in Slang or OpenCL and manually managing buffers, descriptor sets, and dispatches in Vulkan. While this gives you the ultimate control, it also requires a lot of boilerplate code. - -What if you could write your C{pp} code and your GPU kernels in the same file, using the same C{pp} types, and have a compiler automatically handle the Vulkan boilerplate for you? This is the promise of **SYCL**. - -== What is SYCL? - -**SYCL** (pronounced "sickle") is an open-standard, **single-source** (host and device code in one file) C{pp} programming model for heterogeneous computing. It is built on top of standard C{pp}17 (and newer) and allows you to target CPUs, GPUs, **FPGAs** (Field-Programmable Gate Arrays, reconfigurable hardware), and other accelerators from a single codebase. - -Unlike Vulkan, where the host code (C{pp}) and device code (SPIR-V) are strictly separated, SYCL allows you to use C{pp} lambdas or function objects to define your kernels directly within your host code. - -== The Vulkan Backend - -One of the most exciting developments in the SYCL ecosystem is the ability to target **Vulkan** as a backend. Tools like **AdaptiveCpp** (formerly hipSYCL) can take your SYCL code and generate Vulkan-compatible SPIR-V and host code that uses the Vulkan API. - -This means you get the best of both worlds: - -1. **High-Level Abstraction**: Write modern C{pp} without worrying about descriptor sets or command buffers. -2. **Native Performance**: Your code runs on the same high-performance Vulkan drivers we've been using throughout this tutorial. -3. **Vulkan Interoperability**: Because it's "just Vulkan" under the hood, you can easily share data between a high-level SYCL simulation and a native Vulkan renderer. - -== Why SYCL for Advanced Compute? - -For many advanced compute tasks—like complex physics engines, machine learning frameworks, or large-scale simulations—the complexity of managing thousands of Vulkan objects can become a bottleneck for developer productivity. - -SYCL allows you to: - -* **Reduce Boilerplate**: Automate memory transfers and dependency tracking. -* **Improve Maintainability**: Keep your simulation logic and your host orchestration in one place. -* **Target Multiple Backends**: The same SYCL code can target Vulkan, **CUDA** (NVIDIA's proprietary platform), **ROCm** (AMD's open-source platform), or even **oneAPI** (Intel's cross-architecture programming model), providing true hardware portability. - -In this chapter, we'll explore the SYCL programming model, how it maps to Vulkan, and how to use modern extensions to bridge the gap between high-level C{pp} and low-level Vulkan resources. - -xref:../05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[Previous: clvk and Layering] | xref:02_setup_and_installation.adoc[Next: Setup and Installation] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc deleted file mode 100644 index 46cfe76d..00000000 --- a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc +++ /dev/null @@ -1,69 +0,0 @@ -:pp: {plus}{plus} - -= Setup and Installation: Preparing Your SYCL Environment - -To use SYCL with a Vulkan backend, you'll need a SYCL implementation that supports it. While there are several options, **AdaptiveCpp** (formerly known as hipSYCL) is currently the most mature open-source project for targeting Vulkan through the SYCL programming model. - -== Choosing Your Implementation - -The SYCL ecosystem is diverse, but for Vulkan developers, two main implementations stand out: - -1. **AdaptiveCpp**: A flexible, multi-backend implementation that can target Vulkan, CUDA, ROCm, and Level Zero. It is the primary focus for cross-vendor Vulkan compatibility. -2. **Intel oneAPI DPC{pp}**: While primarily focused on Intel hardware, it can target other backends (like CUDA and ROCm) through "plugin" architectures, though its Vulkan support is often handled through interoperability rather than a native backend. - -In this tutorial, we will focus on **AdaptiveCpp** as it provides the most direct path to utilizing the Vulkan 1.4 features we've discussed. - -== Prerequisites - -Before installing AdaptiveCpp, ensure your system has the following dependencies: - -* **Vulkan SDK**: Version 1.3.239 or higher (1.4 is recommended). -* **LLVM and Clang**: Version 14 or newer (used as the compiler base). -* **CMake**: Version 3.18 or higher. -* **Python 3**: For build scripts. -* **Boost Libraries**: Used by the AdaptiveCpp runtime. - -== Installing AdaptiveCpp - -AdaptiveCpp can be built from source or installed via package managers on some Linux distributions. Building from source is the most reliable way to ensure the Vulkan backend is correctly enabled. - -[source,bash] ----- -git clone --recursive https://github.com/AdaptiveCpp/AdaptiveCpp.git -cd AdaptiveCpp -mkdir build && cd build -cmake .. -DCMAKE_INSTALL_PREFIX=/opt/adaptivecpp \ - -DWITH_VULKAN_BACKEND=ON \ - -DCMAKE_BUILD_TYPE=Release -make -j$(nproc) -sudo make install ----- - -Once installed, add `/opt/adaptivecpp/bin` to your system `PATH` and set the `ACPP_COMPILER` environment variable to point to the installed `acpp` executable. - -== Configuring the Vulkan Backend - -To ensure AdaptiveCpp targets Vulkan, you can use the `--acpp-targets="vulkan-generic"` flag when compiling your code. This tells the compiler to generate SPIR-V that is compatible with any Vulkan 1.3+ driver. - -For advanced features like **Buffer Device Address** or **64-bit Atomics**, you may need to specify more targeted profiles or ensure your Vulkan driver supports the required extensions (which we've been tracking throughout this series). - -== Verifying Your Installation - -To verify that your environment is correctly set up, use the `acpp-info` tool (included with AdaptiveCpp). Run the following command in your terminal: - -[source,bash] ----- -acpp-info ----- - -You should see a list of available backends. Look for the **Vulkan** section. It should list your GPU as a supported device. - -If the Vulkan backend does not appear, double-check that you built AdaptiveCpp with `-DWITH_VULKAN_BACKEND=ON` and that your `VK_ICD_FILENAMES` or `VK_DRIVER_FILES` environment variables are correctly pointing to your GPU driver. - -== Your First SYCL Kernel - -With your environment ready, you can now compile a simple single-source C{pp} file. Unlike traditional Vulkan development, where you might have separate `.cpp` and `.slang` files, everything now lives in a single `.cpp` file that you compile with `acpp`. - -In the next section, we'll dive into the syntax of **Single-Source GPGPU** and see how to write your first kernel using this powerful model. - -xref:01_introduction.adoc[Previous: High-Level Abstraction: SYCL and Single-Source C{pp}] | xref:03_single_source_gpgpu.adoc[Next: Single-Source GPGPU] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc deleted file mode 100644 index 0733bf01..00000000 --- a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc +++ /dev/null @@ -1,62 +0,0 @@ -:pp: {plus}{plus} - -= Single-Source GPGPU: Introduction to SYCL and AdaptiveCpp - -== The Single-Source Philosophy - -Traditional GPU development is "dual-source": you write C{pp} for the CPU and GLSL/HLSL/Slang for the GPU. You then manually compile the GPU code, load it as SPIR-V, and manage the data exchange between the two. - -SYCL is **single-source**. Your entire application is written in standard C{pp}. A SYCL-aware compiler (like Clang or AdaptiveCpp) splits the code into CPU and GPU parts during compilation. - -== Anatomy of a SYCL Program - -A typical SYCL program consists of three main components: - -1. **Queue**: Represents the device (e.g., a Vulkan GPU) where you want to execute work. -2. **Buffer**: A high-level abstraction for data that can be accessed by both the CPU and the GPU. -3. **Command Group**: A block of code (usually a lambda) that defines the work to be done. - -[source,cpp] ----- -// Simple SYCL vector addition -sycl::queue q; // Automatically picks a device (e.g., Vulkan GPU) - -// Allocate data -std::vector a(1024), b(1024), c(1024); -// ... initialize a and b ... - -{ - // High-level buffer abstraction - sycl::buffer bufA(a), bufB(b), bufC(c); - - q.submit([&](sycl::handler& h) { - // Accessors tell SYCL the dependencies (SYCL handles memory transfers!) - sycl::accessor accA(bufA, h, sycl::read_only); - sycl::accessor accB(bufB, h, sycl::read_only); - sycl::accessor accC(bufC, h, sycl::write_only); - - // Define the kernel using a lambda - h.parallel_for(sycl::range<1>(1024), [=](sycl::id<1> idx) { - accC[idx] = accA[idx] + accB[idx]; - }); - }); -} -// When the scope ends, bufC is destroyed and data is automatically synced back to 'c' ----- - -== AdaptiveCpp and the Vulkan Backend - -**AdaptiveCpp** is a leading SYCL implementation that excels at targeting multiple backends. When you use the Vulkan backend: - -1. **SPIR-V Translation**: The compiler translates the C{pp} kernel lambda into a SPIR-V blob that uses Vulkan-style descriptor sets and storage buffers. -2. **Runtime Orchestration**: The AdaptiveCpp runtime calls the Vulkan API (e.g., `vkCmdBegin`, `vkCmdDispatch`, `vkQueueSubmit`) to execute your kernels. - -This means your code is standard SYCL, but the performance is driven by the same low-level Vulkan features we've discussed: **Vulkan Memory Model**, **Subgroup Operations**, and **Pipeline Barriers**. - -== Advantages for Complex Simulations - -In a complex simulation (like fluid dynamics), you might have hundreds of interconnected kernels. Manually managing the `VkSemaphore` and `VkFence` objects for every dependency is a nightmare. SYCL's **Directed Acyclic Graph** (**DAG**—a structure representing tasks and their dependencies) of **accessors** (objects that define how kernels read/write to buffers) automatically calculates the optimal Vulkan synchronization for you, ensuring that work is executed as concurrently as possible without race conditions. - -In the next section, we'll look at how to take this high-level code and integrate it with a native Vulkan application through **Interoperability**. - -xref:02_setup_and_installation.adoc[Previous: Setup and Installation] | xref:04_vulkan_interoperability.adoc[Next: Vulkan Interoperability] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc deleted file mode 100644 index 703f5979..00000000 --- a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc +++ /dev/null @@ -1,53 +0,0 @@ -:pp: {plus}{plus} - -= Vulkan Interoperability: Sharing Buffers and Images - -== Bridging the Gap - -While SYCL is perfect for complex simulations, you might still want to use native Vulkan for your final rendering. For example, you could have a SYCL-based fluid simulation and a custom Vulkan renderer that draws the results using path tracing. - -In the past, you would have to copy the data from the "SYCL device" back to the CPU and then down to the "Vulkan device." This is incredibly slow and inefficient. Thanks to the **Vulkan Backend Extensions** in SYCL, we can now share memory and synchronization objects directly. - -== SYCL_EXT_oneapi_backend_vulkan - -The most common way to achieve this interoperability is through the `SYCL_EXT_oneapi_backend_vulkan` extension. This extension allows you to: - -1. **Extract Native Handles**: Get the underlying **native handles** (the original Vulkan objects like `VkBuffer` or `VkImage`) from a SYCL buffer or image. -2. **Import Native Handles**: Wrap an existing `VkBuffer` or `VkImage` into a SYCL object. -3. **Coordinate Synchronization**: Use SYCL events to synchronize with Vulkan semaphores and fences. - -[source,cpp] ----- -// Wrapping an existing Vulkan buffer for use in SYCL -vk::raii::Buffer myVulkanBuffer = ...; -sycl::queue q; - -// Import the Vulkan buffer into SYCL -sycl::buffer mySYCLBuffer = sycl::make_buffer( - *myVulkanBuffer, q.get_context() -); - -// Now you can use mySYCLBuffer in a parallel_for kernel! -q.submit([&](sycl::handler& h) { - auto acc = mySYCLBuffer.get_access(h); - h.parallel_for(range<1>(1024), [=](id<1> idx) { - acc[idx] *= 2.0f; - }); -}); ----- - -== Efficient Data Flow - -By importing your Vulkan vertex or index buffers directly into SYCL, you can perform complex simulations and update the geometry without any copies between the CPU and GPU. The data stays on the GPU at all times. - -This is especially powerful for **Compute-Driven Rendering** (where the GPU's compute logic decides what to render). Your SYCL simulation can update a storage buffer, and then your native Vulkan renderer can use that same buffer in a `vkCmdDrawIndirect` call. - -== Coordination and Semaphores - -The most challenging part of interoperability is synchronization. You need to ensure that the SYCL kernels have finished writing to the buffer before the Vulkan renderer starts reading from it. - -SYCL handles this through **External Semaphores** (Vulkan semaphores that can be shared between different APIs). You can export a SYCL event into a `VkSemaphore` that the Vulkan renderer can wait on, or vice versa. This allows for a seamless, low-latency pipeline where both the high-level and low-level code cooperate on the same hardware resources. - -In the next section, we'll look at the ultimate way to simplify memory management in SYCL: **Unified Shared Memory (USM)**. - -xref:03_single_source_gpgpu.adoc[Previous: Single-Source GPGPU] | xref:05_unified_shared_memory_usm.adoc[Next: Unified Shared Memory (USM)] diff --git a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc b/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc deleted file mode 100644 index 11cf3e01..00000000 --- a/en/Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc +++ /dev/null @@ -1,53 +0,0 @@ -:pp: {plus}{plus} - -= USM (Unified Shared Memory): Pointer-Based Memory in SYCL - -== Moving Beyond Accessors - -In the earlier sections of this chapter, we saw how SYCL's `buffer` and `accessor` system handles data. This approach is powerful because it automatically tracks dependencies and manages memory transfers. However, for many C{pp} developers, it can feel a bit "un-C{pp}-like" because it replaces raw pointers with higher-level abstractions. - -**Unified Shared Memory (USM)** is the solution to this problem. USM provides a pointer-based memory model that is much more familiar to C{pp} programmers and maps directly to modern Vulkan features like **Buffer Device Address**. - -== What is USM? - -USM allows you to allocate memory that can be accessed by both the CPU and the GPU through the same pointer. There are three main types of USM allocation: - -1. **Host Allocation**: Resides on the CPU but can be accessed by the GPU (similar to Vulkan's "Host Visible" memory). -2. **Device Allocation**: Resides purely on the GPU and cannot be accessed directly by the CPU (similar to Vulkan's "Device Local" memory). -3. **Shared Allocation**: Managed by the SYCL runtime. It can migrate between the CPU and GPU automatically, allowing the same pointer to be used everywhere (similar to **Managed Memory**—memory that automatically moves between host and device—in CUDA). - -== USM and Vulkan's Buffer Device Address - -The secret behind USM's efficiency is its direct mapping to **Vulkan 1.4's Buffer Device Address** feature. - -When you allocate USM memory on the device, the SYCL runtime (through a backend like AdaptiveCpp) creates a Vulkan buffer and obtains its raw **64-bit device address** (a pointer-like address that the GPU can use directly). This address is then passed to the GPU kernels, which can treat it as a standard C{pp} pointer. - -[source,cpp] ----- -// Simple USM example in SYCL -sycl::queue q; - -// Allocate device memory (returns a raw pointer) -float* data = sycl::malloc_device(1024, q); - -q.submit([&](sycl::handler& h) { - h.parallel_for(sycl::range<1>(1024), [=](sycl::id<1> idx) { - // We can use the raw pointer directly in the kernel! - data[idx] *= 2.0f; - }); -}); ----- - -== Why Use USM? - -USM is the "gold standard" for complex data structures like linked lists, trees, and graphs on the GPU. These structures rely on pointers, which are difficult to implement using the traditional accessor-based model. - -By using USM, you can build **GPU-Resident Trees** (tree structures stored entirely in GPU memory) or **BVHs** (**Bounding Volume Hierarchies**—a tree structure used for fast spatial searches) that look and feel like standard C{pp} data structures. You can share pointers between the CPU and GPU without any manual "mapping" or "unmapping" of memory. - -== Conclusion: The Power of C{pp} and Vulkan - -Throughout this chapter, we've seen how SYCL and Single-Source C{pp} take the complex world of Vulkan and make it accessible to modern developers. By combining the low-level power of the Vulkan 1.4 API with the high-level abstractions of SYCL, you can build massive, high-performance compute applications with a fraction of the code. - -In the next chapter, we'll dive deeper into how to implement those complex data structures we just mentioned: **Advanced Data Structures on the GPU**. - -xref:04_vulkan_interoperability.adoc[Previous: Vulkan Interoperability] | xref:../07_Advanced_Data_Structures/01_introduction.adoc[Next: Advanced Data Structures] diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc similarity index 97% rename from en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc rename to en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc index 00efb882..bf879170 100644 --- a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc @@ -34,4 +34,4 @@ By moving the "decision-making" to the GPU, we can: In this chapter, we'll learn how to build these autonomous pipelines, starting with the fundamental building block: **Indirect Dispatch**. -xref:../07_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Previous: Device-Addressable Buffers] | xref:02_indirect_dispatch.adoc[Next: Indirect Dispatch] +xref:../06_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Previous: Device-Addressable Buffers] | xref:02_indirect_dispatch.adoc[Next: Indirect Dispatch] diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/02_indirect_dispatch.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/02_indirect_dispatch.adoc rename to en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc rename to en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc diff --git a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc similarity index 97% rename from en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc rename to en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc index 6a0c7602..1775ca08 100644 --- a/en/Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc +++ b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc @@ -44,4 +44,4 @@ By mastering **Indirect Dispatch**, **GPU-Side Command Generation**, and **Multi In the next chapter, we'll look at how to coordinate these heavy compute workloads with your graphics rendering using **Asynchronous Compute Orchestration**. -xref:03_gpu_side_command_generation.adoc[Previous: GPU-Side Command Generation] | xref:../09_Asynchronous_Compute/01_introduction.adoc[Next: Asynchronous Compute Orchestration] +xref:03_gpu_side_command_generation.adoc[Previous: GPU-Side Command Generation] | xref:../08_Asynchronous_Compute/01_introduction.adoc[Next: Asynchronous Compute Orchestration] diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc similarity index 97% rename from en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc rename to en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc index 2e76112f..69fe20f4 100644 --- a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc @@ -17,4 +17,4 @@ In this chapter, we're going to move beyond the simple "one queue for all" model Orchestrating these workloads requires a shift in how we think about the GPU's timeline. It's no longer just a linear sequence of commands, but a multi-lane highway where different types of traffic can move at different speeds, occasionally merging or yielding to ensure the overall throughput is maximized. -xref:../08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Previous: Multi-Draw Indirect (MDI)] | xref:02_concurrent_execution.adoc[Next: Concurrent Execution] +xref:../07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Previous: Multi-Draw Indirect (MDI)] | xref:02_concurrent_execution.adoc[Next: Concurrent Execution] diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/02_concurrent_execution.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/02_concurrent_execution.adoc rename to en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/03_timeline_semaphores.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/03_timeline_semaphores.adoc rename to en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc diff --git a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc similarity index 98% rename from en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc rename to en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc index 97164763..7c22474d 100644 --- a/en/Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc +++ b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc @@ -36,4 +36,4 @@ Another critical consideration is **Queue Family** (a group of queues with simil In practice, managing queue priorities is a balancing act. Used correctly, it's a powerful tool for ensuring that your engine remains responsive and that the most critical tasks are always handled with the urgency they require. This orchestration is the hallmark of a truly advanced Vulkan engine—moving beyond just "doing the work" to "doing the work in the right order at the right time." -xref:03_timeline_semaphores.adoc[Previous: Timeline Semaphores] | xref:../10_Specialized_Math/01_introduction.adoc[Next: Specialized Math] +xref:03_timeline_semaphores.adoc[Previous: Timeline Semaphores] | xref:../09_Specialized_Math/01_introduction.adoc[Next: Specialized Math] diff --git a/en/Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc b/en/Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc similarity index 96% rename from en/Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc rename to en/Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc index b40ba814..37524f59 100644 --- a/en/Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc @@ -9,4 +9,4 @@ Whether you're building a fluid simulation that requires solving large systems o In this chapter, we're going to dive into how these specialized math units work. We'll explore how to use the `cooperative_matrix` types in Slang and GLSL, and we'll see how to leverage **Mixed Precision**—using FP16 or Int8 for calculations while maintaining accuracy where it counts. This is about more than just speed; it's about utilizing the full potential of modern GPU silicon for high-performance computing tasks. -xref:../09_Asynchronous_Compute/04_queue_priority.adoc[Previous: Queue Priority] | xref:02_cooperative_matrices.adoc[Next: Cooperative Matrices] +xref:../08_Asynchronous_Compute/04_queue_priority.adoc[Previous: Queue Priority] | xref:02_cooperative_matrices.adoc[Next: Cooperative Matrices] diff --git a/en/Advanced_Vulkan_Compute/10_Specialized_Math/02_cooperative_matrices.adoc b/en/Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/10_Specialized_Math/02_cooperative_matrices.adoc rename to en/Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc diff --git a/en/Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc b/en/Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc similarity index 98% rename from en/Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc rename to en/Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc index c74521f3..8e318da7 100644 --- a/en/Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc +++ b/en/Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc @@ -100,4 +100,4 @@ Managing this requires a technique known as **Loss Scaling**. You multiply your By mastering mixed precision, you're not just "squeezing out more performance"; you're being smarter about how you use the hardware's resources. Whether you're optimizing a fluid simulation or a real-time signal processing engine, these techniques are essential for pushing the boundaries of what's possible on modern GPUs. -xref:02_cooperative_matrices.adoc[Previous: Cooperative Matrices] | xref:../11_Performance_Optimization/01_introduction.adoc[Next: Performance Optimization] +xref:02_cooperative_matrices.adoc[Previous: Cooperative Matrices] | xref:../10_Performance_Optimization/01_introduction.adoc[Next: Performance Optimization] diff --git a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc similarity index 86% rename from en/Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc rename to en/Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc index bea8d91b..3403a6f3 100644 --- a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc @@ -1,7 +1,7 @@ :pp: {plus}{plus} = Performance Auditing and Optimization -We've covered a vast range of advanced Vulkan compute topics—from low-level architecture to high-level abstractions like SYCL. But there's one question that every developer eventually faces: "Is this as fast as it can be?" Answering this question is not about guesswork or intuition; it's about a rigorous, methodical approach to **Performance Auditing**. +We've covered a vast range of advanced Vulkan compute topics—from low-level architecture and memory models to GPU-driven pipelines and asynchronous compute. But there's one question that every developer eventually faces: "Is this as fast as it can be?" Answering this question is not about guesswork or intuition; it's about a rigorous, methodical approach to **Performance Auditing**. In the world of GPU compute, a "fast" kernel can be held back by many things. It might be waiting on memory (**memory-bound**), it might be overwhelmed by complex arithmetic (**compute-bound**), or it might be suffering from "divergence"—where different invocations in a **subgroup** (or **warp/wavefront**) are forced to take different execution paths, causing the hardware to serialize their work. @@ -25,4 +25,4 @@ By the end of this chapter, you'll be equipped with the methodology to move from 2. **The Divergence Audit**: Techniques for visualizing and refactoring divergent branching logic. [horizontal] -*Previous:* xref:../10_Specialized_Math/03_mixed_precision.adoc[Mastering Mixed Precision] | *Next:* xref:02_instruction_throughput.adoc[Instruction Throughput Analysis] +*Previous:* xref:../09_Specialized_Math/03_mixed_precision.adoc[Mastering Mixed Precision] | *Next:* xref:02_instruction_throughput.adoc[Instruction Throughput Analysis] diff --git a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/02_instruction_throughput.adoc b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/11_Performance_Optimization/02_instruction_throughput.adoc rename to en/Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc diff --git a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc similarity index 98% rename from en/Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc rename to en/Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc index e94c7edf..d2df99f1 100644 --- a/en/Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc +++ b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc @@ -61,4 +61,4 @@ If your divergence is caused by processing different types of data (e.g., in a r By conducting regular divergence audits, you can identify the "hidden" costs in your compute kernels and refactor them into more efficient, SIMD-friendly patterns. This is the difference between code that "just runs" and code that truly masters the GPU's architecture. -xref:02_instruction_throughput.adoc[Previous: Instruction Throughput Analysis] | xref:../12_Diagnostics_and_Refinement/01_introduction.adoc[Next: Diagnostics and Refinement] +xref:02_instruction_throughput.adoc[Previous: Instruction Throughput Analysis] | xref:../11_Diagnostics_and_Refinement/01_introduction.adoc[Next: Diagnostics and Refinement] diff --git a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc similarity index 97% rename from en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc rename to en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc index 3e0c93b4..0c9dc4d5 100644 --- a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc @@ -25,4 +25,4 @@ Whether you're struggling to vectorize a naive loop or looking for a more effici 1. **Compute Validation**: Setting up and using GPU-Assisted Validation to catch memory errors and using `printf` for shader debugging. 2. **Assistant-Led Optimization**: Leveraging AI to refactor naive compute kernels into wave-aware, high-performance patterns. -xref:../11_Performance_Optimization/03_divergence_audit.adoc[Previous: Divergence Audit] | xref:02_compute_validation.adoc[Next: Compute Validation] +xref:../10_Performance_Optimization/03_divergence_audit.adoc[Previous: Divergence Audit] | xref:02_compute_validation.adoc[Next: Compute Validation] diff --git a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc similarity index 99% rename from en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc rename to en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc index 6f364287..35c8be38 100644 --- a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc +++ b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc @@ -56,12 +56,14 @@ void computeMain(uint3 globalID : SV_DispatchThreadID) { === In the Host Code To see the output from `printf`, you must: + 1. Enable the `VK_KHR_shader_non_semantic_info` extension on your device. 2. Have a standard **Debug Messenger** callback registered. The output from your shader will arrive as a `VkDebugUtilsMessengerCallbackDataEXT` with a message ID that identifies it as a printf call. == Interpreting the Output When a validation error or a `printf` occurs, the output can be verbose. Look for: + * **The Shader Module**: Which shader triggered the message. * **The Instruction Offset**: The specific SPIR-V instruction that failed. * **The Value**: For `printf`, this is your formatted string. For GAV, it might be the invalid index or pointer address. diff --git a/en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc similarity index 100% rename from en/Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc rename to en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc diff --git a/en/Advanced_Vulkan_Compute/conclusion.adoc b/en/Advanced_Vulkan_Compute/conclusion.adoc index a126e038..aa718f15 100644 --- a/en/Advanced_Vulkan_Compute/conclusion.adoc +++ b/en/Advanced_Vulkan_Compute/conclusion.adoc @@ -10,7 +10,7 @@ Throughout this series, we have explored the depths of modern GPU compute, movin 1. **Compute Architecture**: We mastered the mapping between workgroup grids and physical hardware (CUs and SMs), and learned how to maximize occupancy and hide latency. We also utilized Vulkan 1.4's scalar layouts for maximum bandwidth efficiency. 2. **Memory Models**: We demystified the Vulkan Memory Model, mastering availability, visibility, and domain operations to ensure thread safety without sacrificing performance. 3. **Subgroup Power**: We utilized subgroup shuffles, broadcasts, and arithmetic to exchange data at hardware speed, bypassing VRAM and shared memory (LDS) entirely. -4. **Heterogeneous Ecosystems**: We explored bridging legacy code with OpenCL (clspv/clvk) and modernizing development with single-source SYCL (AdaptiveCpp). +4. **Heterogeneous Ecosystems**: We explored bridging legacy OpenCL code to Vulkan with `clspv` and `clvk`, which provides conformant OpenCL 3.0 layered on Vulkan — invisible to the application. 5. **Advanced Data Structures**: We implemented GPU-resident trees, lock-free linked lists, and utilized raw Buffer Device Addresses (BDA) for pointer-like flexibility. 6. **GPU-Driven Pipelines**: We transitioned control from the CPU to the GPU using indirect dispatches and autonomous command generation. 7. **Asynchronous Orchestration**: We harnessed the power of multiple hardware engines to run compute concurrently with graphics using Synchronization 2 and Timeline Semaphores. @@ -35,7 +35,7 @@ The world of high-performance computing is vast. Now that you have a solid found 1. **Deep Dive into Machine Learning**: Use what you've learned about Cooperative Matrices and Mixed Precision to optimize neural network inference or training. 2. **Real-Time Path Tracing**: Combine GPU-Driven pipelines and Asynchronous Compute to build a high-performance ray tracer that handles complex spatial structures entirely on the device. 3. **Physical Simulations**: Implement advanced fluid dynamics (SPH) or rigid body solvers using the lock-free data structures we discussed. -4. **Vulkan Ecosystem**: Contribute to projects like `clspv`, `clvk`, or `AdaptiveCpp`, or build your own high-level compute abstraction. +4. **Vulkan Ecosystem**: Contribute to projects like `clspv` or `clvk`, or build your own high-level compute abstraction on top of the Vulkan features covered in this series. == Community and Resources @@ -49,4 +49,4 @@ Thank you for following along with this series. We've moved from "making pixels Happy Hacking! -xref:12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Previous: Assistant-Led Optimization] | xref:../00_Introduction.adoc[Back to Home] +xref:11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Previous: Assistant-Led Optimization] | xref:../00_Introduction.adoc[Back to Home] diff --git a/en/Advanced_Vulkan_Compute/introduction.adoc b/en/Advanced_Vulkan_Compute/introduction.adoc index 6e2e6e23..95466b34 100644 --- a/en/Advanced_Vulkan_Compute/introduction.adoc +++ b/en/Advanced_Vulkan_Compute/introduction.adoc @@ -26,7 +26,7 @@ This tutorial series is organized into several key areas: 1. **Compute Architecture** - Mapping workgroups to Compute Units (CU) and Streaming Multiprocessors (SM), and mastering occupancy. 2. **Memory Models and Consistency** - Understanding the Vulkan Memory Model, shared memory (**LDS** - Local Data Store), and fine-grained synchronization. 3. **Subgroup Operations** - Using cross-invocation communication to avoid VRAM round-trips and maximize **SIMD** (Single Instruction, Multiple Data) throughput. -4. **Heterogeneous Ecosystems** - Running OpenCL C and SYCL code on top of Vulkan using `clspv`, `clvk`, and AdaptiveCpp. +4. **Heterogeneous Ecosystems** - Running legacy OpenCL C on Vulkan using `clspv` (AOT compiler) and `clvk` (conformant OpenCL 3.0 runtime layered on Vulkan). 5. **Advanced Data Structures** - Moving complex structures like trees and linked lists entirely to the GPU using 64-bit atomics and **BDA** (Buffer Device Address). 6. **GPU-Driven Pipelines** - Moving command generation and workload management entirely to the GPU for autonomous execution. 7. **Asynchronous Orchestration** - Running compute and graphics concurrently using Synchronization 2 and multiple hardware queues. @@ -53,12 +53,11 @@ Let's dive into the world of high-performance GPU computing! * xref:03_Memory_Models/01_introduction.adoc[Memory Models and Consistency] * xref:04_Subgroup_Operations/01_introduction.adoc[Subgroup Operations: The Hidden Power] * xref:05_OpenCL_on_Vulkan/01_introduction.adoc[Heterogeneous Ecosystem: OpenCL on Vulkan] -* xref:06_SYCL_and_Single_Source_CPP/01_introduction.adoc[High-Level Abstraction: SYCL and Single-Source C{pp}] -* xref:07_Advanced_Data_Structures/01_introduction.adoc[Advanced Data Structures on the GPU] -* xref:08_GPU_Driven_Pipelines/01_introduction.adoc[Indirect Dispatch and GPU-Driven Pipelines] -* xref:09_Asynchronous_Compute/01_introduction.adoc[Asynchronous Compute Orchestration] -* xref:10_Specialized_Math/01_introduction.adoc[Cooperative Matrices and Specialized Math] -* xref:11_Performance_Optimization/01_introduction.adoc[Performance Auditing and Optimization] -* xref:12_Diagnostics_and_Refinement/01_introduction.adoc[Diagnostics and AI-Assisted Compute Refinement] +* xref:06_Advanced_Data_Structures/01_introduction.adoc[Advanced Data Structures on the GPU] +* xref:07_GPU_Driven_Pipelines/01_introduction.adoc[Indirect Dispatch and GPU-Driven Pipelines] +* xref:08_Asynchronous_Compute/01_introduction.adoc[Asynchronous Compute Orchestration] +* xref:09_Specialized_Math/01_introduction.adoc[Cooperative Matrices and Specialized Math] +* xref:10_Performance_Optimization/01_introduction.adoc[Performance Auditing and Optimization] +* xref:11_Diagnostics_and_Refinement/01_introduction.adoc[Diagnostics and AI-Assisted Compute Refinement] xref:11_Compute_Shader.adoc[Previous: Basic Compute Shaders] | xref:02_Compute_Architecture/01_introduction.adoc[Next: Compute Architecture] \ No newline at end of file From e1eeaf0cbbf54aeb9f25aa06fb5f234c9f3d30c0 Mon Sep 17 00:00:00 2001 From: swinston Date: Wed, 10 Jun 2026 21:31:44 -0700 Subject: [PATCH 4/5] Fix for antora navigation and all links. Add accompanying samples for all chapters. --- .github/workflows/compute_ci.yml | 325 +++ antora/modules/ROOT/nav.adoc | 50 +- .../compute/02_compute_architecture.cpp | 1250 ++++++++++++ .../compute/02_compute_architecture.slang | 259 +++ attachments/compute/03_memory_models.cpp | 1344 +++++++++++++ attachments/compute/03_memory_models.slang | 288 +++ .../compute/04_subgroup_operations.cpp | 1045 ++++++++++ .../compute/04_subgroup_operations.slang | 319 +++ attachments/compute/05_opencl_on_vulkan.cl | 197 ++ attachments/compute/05_opencl_on_vulkan.cpp | 776 +++++++ .../compute/06_advanced_data_structures.cpp | 1439 +++++++++++++ .../compute/06_advanced_data_structures.slang | 448 +++++ .../compute/07_gpu_driven_pipelines.cpp | 1583 +++++++++++++++ .../compute/07_gpu_driven_pipelines.slang | 315 +++ attachments/compute/08_async_compute.cpp | 1787 +++++++++++++++++ attachments/compute/08_async_compute.slang | 277 +++ attachments/compute/09_specialized_math.cpp | 1175 +++++++++++ attachments/compute/09_specialized_math.slang | 302 +++ .../compute/10_performance_optimization.cpp | 1122 +++++++++++ .../compute/10_performance_optimization.slang | 198 ++ attachments/compute/CMakeLists.txt | 242 +++ attachments/compute/compute_common.h | 258 +++ .../compute/install_dependencies_linux.sh | 169 ++ .../compute/install_dependencies_windows.bat | 95 + .../01_introduction.adoc | 2 +- .../02_workgroups_and_invocations.adoc | 2 +- .../03_occupancy_and_latency_hiding.adoc | 2 +- .../04_vulkan_1_4_scalar_layouts.adoc | 2 +- .../03_Memory_Models/01_introduction.adoc | 2 +- .../02_vulkan_memory_model.adoc | 2 +- .../03_shared_memory_lds.adoc | 2 +- .../04_memory_consistency.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_cross_invocation_communication.adoc | 2 +- .../03_subgroup_partitioning.adoc | 2 +- .../04_non_uniform_indexing.adoc | 2 +- .../05_OpenCL_on_Vulkan/01_introduction.adoc | 2 +- .../02_setup_and_installation.adoc | 6 +- .../03_clspv_pipeline.adoc | 2 +- .../04_kernel_portability.adoc | 2 +- .../05_clvk_and_layering.adoc | 4 +- .../06_a_practical_sample.adoc | 139 ++ .../07_clspv_for_production.adoc | 199 ++ .../01_introduction.adoc | 2 +- .../02_gpu_resident_trees.adoc | 2 +- .../03_global_atomic_management.adoc | 2 +- .../04_device_addressable_buffers.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_indirect_dispatch.adoc | 2 +- .../03_gpu_side_command_generation.adoc | 2 +- .../04_multi_draw_indirect_mdi.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_concurrent_execution.adoc | 2 +- .../03_timeline_semaphores.adoc | 2 +- .../04_queue_priority.adoc | 2 +- .../09_Specialized_Math/01_introduction.adoc | 2 +- .../02_cooperative_matrices.adoc | 2 +- .../03_mixed_precision.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_instruction_throughput.adoc | 2 +- .../03_divergence_audit.adoc | 2 +- .../01_introduction.adoc | 2 +- .../02_compute_validation.adoc | 2 +- .../03_assistant_led_optimization.adoc | 2 +- en/Advanced_Vulkan_Compute/conclusion.adoc | 2 +- en/Advanced_Vulkan_Compute/introduction.adoc | 24 +- images/spirv_dialects_venn.svg | 90 + 67 files changed, 15718 insertions(+), 81 deletions(-) create mode 100644 .github/workflows/compute_ci.yml create mode 100644 attachments/compute/02_compute_architecture.cpp create mode 100644 attachments/compute/02_compute_architecture.slang create mode 100644 attachments/compute/03_memory_models.cpp create mode 100644 attachments/compute/03_memory_models.slang create mode 100644 attachments/compute/04_subgroup_operations.cpp create mode 100644 attachments/compute/04_subgroup_operations.slang create mode 100644 attachments/compute/05_opencl_on_vulkan.cl create mode 100644 attachments/compute/05_opencl_on_vulkan.cpp create mode 100644 attachments/compute/06_advanced_data_structures.cpp create mode 100644 attachments/compute/06_advanced_data_structures.slang create mode 100644 attachments/compute/07_gpu_driven_pipelines.cpp create mode 100644 attachments/compute/07_gpu_driven_pipelines.slang create mode 100644 attachments/compute/08_async_compute.cpp create mode 100644 attachments/compute/08_async_compute.slang create mode 100644 attachments/compute/09_specialized_math.cpp create mode 100644 attachments/compute/09_specialized_math.slang create mode 100644 attachments/compute/10_performance_optimization.cpp create mode 100644 attachments/compute/10_performance_optimization.slang create mode 100644 attachments/compute/CMakeLists.txt create mode 100644 attachments/compute/compute_common.h create mode 100755 attachments/compute/install_dependencies_linux.sh create mode 100644 attachments/compute/install_dependencies_windows.bat create mode 100644 en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/06_a_practical_sample.adoc create mode 100644 en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/07_clspv_for_production.adoc create mode 100644 images/spirv_dialects_venn.svg diff --git a/.github/workflows/compute_ci.yml b/.github/workflows/compute_ci.yml new file mode 100644 index 00000000..13a7ab59 --- /dev/null +++ b/.github/workflows/compute_ci.yml @@ -0,0 +1,325 @@ +name: Advanced Vulkan Compute CI + +on: + pull_request: + types: [ opened, synchronize, reopened ] + paths: + - 'attachments/compute/**' + - '.github/workflows/compute_ci.yml' + push: + branches: [ main ] + paths: + - 'attachments/compute/**' + - '.github/workflows/compute_ci.yml' + workflow_dispatch: + +jobs: + build: + strategy: + fail-fast: false + matrix: + os: [ubuntu-latest, windows-latest] + include: + - os: ubuntu-latest + ccache: ccache + vulkan-install: | + VULKAN_VERSION=$(curl -s https://vulkan.lunarg.com/sdk/latest/linux.txt) + echo "Using Vulkan SDK version: $VULKAN_VERSION" + + mkdir -p vulkan-sdk + cd vulkan-sdk + + curl -O "https://sdk.lunarg.com/sdk/download/$VULKAN_VERSION/linux/vulkansdk-linux-x86_64-$VULKAN_VERSION.tar.xz" + + tar -xJf vulkansdk-linux-x86_64-$VULKAN_VERSION.tar.xz + + ln -sfn "$PWD/$VULKAN_VERSION" "$PWD/latest" + + echo "VULKAN_SDK=$PWD/latest/x86_64" >> $GITHUB_ENV + echo "PATH=$PWD/latest/x86_64/bin:$PATH" >> $GITHUB_ENV + echo "LD_LIBRARY_PATH=$PWD/latest/x86_64/lib:$LD_LIBRARY_PATH" >> $GITHUB_ENV + echo "VK_LAYER_PATH=$PWD/latest/x86_64/etc/vulkan/explicit_layer.d" >> $GITHUB_ENV + + cd .. + deps-install: | + chmod +x attachments/compute/install_dependencies_linux.sh + ./attachments/compute/install_dependencies_linux.sh + test-cmd: | + for sample in \ + 02_compute_architecture/02_compute_architecture \ + 03_memory_models/03_memory_models \ + 04_subgroup_operations/04_subgroup_operations \ + 05_opencl_on_vulkan/05_opencl_on_vulkan \ + 06_advanced_data_structures/06_advanced_data_structures \ + 07_gpu_driven_pipelines/07_gpu_driven_pipelines \ + 08_async_compute/08_async_compute \ + 09_specialized_math/09_specialized_math \ + 10_performance_optimization/10_performance_optimization; do + if [ -f "$sample" ]; then + echo "$sample built successfully" + else + echo "$sample build failed" + exit 1 + fi + done + + - os: windows-latest + ccache: sccache + vulkan-install: | + if (Test-Path "C:\VulkanSDK") { + Write-Host "Using cached Vulkan SDK" + } else { + Write-Host "Downloading Vulkan SDK..." + choco install -y aria2 + aria2c --split=16 --max-connection-per-server=16 --min-split-size=1M --dir="$env:TEMP" --out="vulkan-sdk.exe" "https://sdk.lunarg.com/sdk/download/latest/windows/vulkan-sdk.exe" + + Write-Host "Installing minimal Vulkan SDK components..." + try { + Start-Process -FilePath "$env:TEMP\vulkan-sdk.exe" -ArgumentList "--accept-licenses --default-answer --confirm-command install --components VulkanRT,VulkanSDK64,VulkanDXC,VulkanTools" -Wait -NoNewWindow + if (-not (Test-Path "C:\VulkanSDK")) { + Write-Host "Vulkan SDK installation failed: C:\VulkanSDK directory not found" + Write-Host "Attempting to install without specifying components..." + Start-Process -FilePath "$env:TEMP\vulkan-sdk.exe" -ArgumentList "--accept-licenses --default-answer --confirm-command install" -Wait -NoNewWindow + } + } catch { + Write-Host "Error installing Vulkan SDK: $_" + Start-Process -FilePath "$env:TEMP\vulkan-sdk.exe" -ArgumentList "--accept-licenses --default-answer --confirm-command install" -Wait -NoNewWindow + } + } + + $vulkanPath = "" + if (Test-Path "C:\VulkanSDK") { + if (Test-Path "C:\VulkanSDK\Latest") { + $vulkanPath = "C:\VulkanSDK\Latest" + } elseif (Test-Path "C:\VulkanSDK\latest") { + $vulkanPath = "C:\VulkanSDK\latest" + } else { + $vulkanPath = Get-ChildItem "C:\VulkanSDK" | Where-Object { $_.PSIsContainer } | Sort-Object -Property Name -Descending | Select-Object -First 1 -ExpandProperty FullName + } + } + if (-not $vulkanPath) { + Write-Host "Warning: Vulkan SDK not found. Creating a temporary directory structure." + New-Item -ItemType Directory -Force -Path "C:\VulkanSDK\latest\Include\vulkan" | Out-Null + New-Item -ItemType Directory -Force -Path "C:\VulkanSDK\latest\Lib" | Out-Null + New-Item -ItemType Directory -Force -Path "C:\VulkanSDK\latest\Bin" | Out-Null + New-Item -ItemType File -Force -Path "C:\VulkanSDK\latest\Include\vulkan\vulkan.h" | Out-Null + New-Item -ItemType File -Force -Path "C:\VulkanSDK\latest\Lib\vulkan-1.lib" | Out-Null + $vulkanPath = "C:\VulkanSDK\latest" + } + + echo "VULKAN_SDK=$vulkanPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + echo "$vulkanPath\Bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append + echo "CMAKE_PREFIX_PATH=$vulkanPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + echo "Vulkan_INCLUDE_DIR=$vulkanPath\Include" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + echo "Vulkan_LIBRARY=$vulkanPath\Lib\vulkan-1.lib" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + + Write-Host "Vulkan SDK path: $vulkanPath" + deps-install: | + .\attachments\compute\install_dependencies_windows.bat + echo "CMAKE_TOOLCHAIN_FILE=$env:VCPKG_INSTALLATION_ROOT/scripts/buildsystems/vcpkg.cmake" >> $env:GITHUB_ENV + test-cmd: | + $samples = @( + "02_compute_architecture", + "03_memory_models", + "04_subgroup_operations", + "05_opencl_on_vulkan", + "06_advanced_data_structures", + "07_gpu_driven_pipelines", + "08_async_compute", + "09_specialized_math", + "10_performance_optimization" + ) + foreach ($s in $samples) { + if (Test-Path "$s/Release/$s.exe") { + echo "$s built successfully" + } else { + echo "$s build failed" + exit 1 + } + } + + runs-on: ${{ matrix.os }} + + steps: + - uses: actions/checkout@v3 + + - name: Cache vcpkg packages (Windows) + if: runner.os == 'Windows' + uses: actions/cache@v3 + with: + path: | + ${{ env.VCPKG_INSTALLATION_ROOT }}/installed + ${{ env.VCPKG_INSTALLATION_ROOT }}/packages + ${{ env.VCPKG_INSTALLATION_ROOT }}/buildtrees + ${{ env.VCPKG_INSTALLATION_ROOT }}/downloads + ${{ runner.temp }}/vcpkg-cache + key: ${{ runner.os }}-vcpkg-compute-${{ hashFiles('attachments/compute/install_dependencies_windows.bat', 'attachments/compute/CMakeLists.txt') }} + restore-keys: | + ${{ runner.os }}-vcpkg-compute- + ${{ runner.os }}-vcpkg- + + - name: Cache Vulkan SDK (Windows) + if: runner.os == 'Windows' + uses: actions/cache@v3 + with: + path: C:\VulkanSDK + key: ${{ runner.os }}-vulkan-sdk-compute-${{ hashFiles('attachments/compute/CMakeLists.txt', 'attachments/compute/**/*.cpp') }} + restore-keys: | + ${{ runner.os }}-vulkan-sdk-compute- + ${{ runner.os }}-vulkan-sdk- + + - name: Cache apt packages (Ubuntu) + if: runner.os == 'Linux' + uses: actions/cache@v3 + with: + path: /var/cache/apt/archives + key: ${{ runner.os }}-apt-compute-${{ hashFiles('.github/workflows/compute_ci.yml') }} + restore-keys: | + ${{ runner.os }}-apt-compute- + ${{ runner.os }}-apt- + + - name: Cache ccache files + uses: actions/cache@v3 + with: + path: | + ~/.ccache + ~/.cache/sccache + key: ${{ runner.os }}-${{ matrix.ccache }}-compute-${{ github.sha }} + restore-keys: | + ${{ runner.os }}-${{ matrix.ccache }}-compute- + ${{ runner.os }}-${{ matrix.ccache }}- + + - name: Cache Vulkan SDK (Ubuntu) + if: runner.os == 'Linux' + uses: actions/cache@v3 + with: + path: ${{ github.workspace }}/vulkan-sdk + key: ${{ runner.os }}-vulkan-sdk-compute-${{ hashFiles('attachments/compute/CMakeLists.txt') }} + restore-keys: | + ${{ runner.os }}-vulkan-sdk-compute- + ${{ runner.os }}-vulkan-sdk- + + - name: Install ccache (Ubuntu) + if: runner.os == 'Linux' + run: | + sudo apt-get update + sudo apt-get install -y ccache + ccache --max-size=2G + ccache -z + echo "CCACHE_DIR=$HOME/.ccache" >> $GITHUB_ENV + echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV + + - name: Cache sccache binary (Windows) + if: runner.os == 'Windows' + id: cache-sccache + uses: actions/cache@v3 + with: + path: ${{ runner.temp }}/sccache + key: ${{ runner.os }}-sccache-0.5.4 + + - name: Install sccache (Windows) + if: runner.os == 'Windows' + run: | + if (Test-Path "$env:RUNNER_TEMP\sccache\sccache.exe") { + Write-Host "Using cached sccache binary" + $sccachePath = "$env:RUNNER_TEMP\sccache" + } else { + Write-Host "Downloading and installing sccache..." + New-Item -ItemType Directory -Force -Path "$env:RUNNER_TEMP\sccache" + aria2c --split=8 --max-connection-per-server=8 --min-split-size=1M --dir="$env:RUNNER_TEMP" --out="sccache.tar.gz" "https://github.com/mozilla/sccache/releases/download/v0.5.4/sccache-v0.5.4-x86_64-pc-windows-msvc.tar.gz" + tar -xzf "$env:RUNNER_TEMP\sccache.tar.gz" --strip-components=1 -C "$env:RUNNER_TEMP\sccache" "sccache-v0.5.4-x86_64-pc-windows-msvc/sccache.exe" + $sccachePath = "$env:RUNNER_TEMP\sccache" + } + + echo "$sccachePath" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append + echo "SCCACHE_DIR=$HOME/.cache/sccache" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + echo "SCCACHE_CACHE_SIZE=4G" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + echo "SCCACHE_ERROR_LOG=$HOME/.cache/sccache/sccache.log" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + echo "SCCACHE_LOG=info" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + echo "RUST_LOG=sccache=info" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append + + New-Item -ItemType Directory -Force -Path "$HOME/.cache/sccache" + & "$sccachePath\sccache.exe" --version + + - name: Install dependencies + run: ${{ matrix.deps-install }} + + - name: Install Vulkan SDK + run: ${{ matrix.vulkan-install }} + + - name: Verify Vulkan SDK (Linux) + if: runner.os == 'Linux' + run: | + if [ -d "$VULKAN_SDK" ]; then + echo "Vulkan SDK found at: $VULKAN_SDK" + slangc --version || echo "Warning: slangc not found in PATH" + else + echo "Vulkan SDK not found!" + exit 1 + fi + + - name: Verify Vulkan SDK (Windows) + if: runner.os == 'Windows' + run: | + if (Test-Path $env:VULKAN_SDK) { + echo "Vulkan SDK found at: $env:VULKAN_SDK" + $criticalPaths = @( + "$env:VULKAN_SDK\Include", + "$env:VULKAN_SDK\Lib", + "$env:VULKAN_SDK\Bin", + "$env:VULKAN_SDK\Include\vulkan\vulkan.h", + "$env:VULKAN_SDK\Lib\vulkan-1.lib" + ) + $allPathsExist = $true + foreach ($path in $criticalPaths) { + if (Test-Path $path) { echo "Found: $path" } + else { echo "Missing: $path"; $allPathsExist = $false } + } + if (-not $allPathsExist) { + echo "Warning: Vulkan SDK installation is incomplete, but continuing." + } + } else { + echo "Warning: Vulkan SDK not found." + } + + - name: Configure CMake (Linux) + if: runner.os == 'Linux' + working-directory: ${{ github.workspace }}/attachments/compute + run: | + export CC="clang" + export CXX="clang++" + rm -rf build + cmake -B build -G Ninja -DCMAKE_BUILD_TYPE=Release \ + -DCMAKE_C_COMPILER_LAUNCHER=ccache \ + -DCMAKE_CXX_COMPILER_LAUNCHER=ccache + + - name: Configure CMake (Windows) + if: runner.os == 'Windows' + working-directory: ${{ github.workspace }}/attachments/compute + run: | + if (Test-Path "build") { Remove-Item -Recurse -Force "build" } + cmake -B build -DCMAKE_BUILD_TYPE=Release ` + -DVulkan_INCLUDE_DIR="$env:Vulkan_INCLUDE_DIR" ` + -DVulkan_LIBRARY="$env:Vulkan_LIBRARY" ` + -DCMAKE_PREFIX_PATH="$env:VULKAN_SDK" ` + -DCMAKE_PROGRAM_PATH="$env:VULKAN_SDK\Bin" ` + -DCMAKE_TOOLCHAIN_FILE="$env:CMAKE_TOOLCHAIN_FILE" ` + -DCMAKE_C_COMPILER_LAUNCHER=sccache ` + -DCMAKE_CXX_COMPILER_LAUNCHER=sccache ` + -DCMAKE_CXX_FLAGS="/MP /EHsc /W3 /O2" + + - name: Build + working-directory: ${{ github.workspace }}/attachments/compute + run: cmake --build build --config Release --parallel 4 + + - name: ccache statistics + if: runner.os == 'Linux' + run: ccache -s + + - name: sccache statistics + if: runner.os == 'Windows' + run: sccache -s + + - name: Test Build Output + working-directory: ${{ github.workspace }}/attachments/compute/build + run: ${{ matrix.test-cmd }} diff --git a/antora/modules/ROOT/nav.adoc b/antora/modules/ROOT/nav.adoc index 4e28bb0f..c417c6b5 100644 --- a/antora/modules/ROOT/nav.adoc +++ b/antora/modules/ROOT/nav.adoc @@ -172,37 +172,33 @@ *** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc[The clspv Pipeline] *** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc[Kernel Portability] *** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[clvk and Layering] -** High-Level Abstraction: SYCL and Single-Source C++ -*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/01_introduction.adoc[Introduction] -*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/02_setup_and_installation.adoc[Setup and Installation] -*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/03_single_source_gpgpu.adoc[Single-Source GPGPU] -*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/04_vulkan_interoperability.adoc[Vulkan Interoperability] -*** xref:Advanced_Vulkan_Compute/06_SYCL_and_Single_Source_CPP/05_unified_shared_memory_usm.adoc[Unified Shared Memory (USM)] +*** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/06_a_practical_sample.adoc[A Practical Sample] +*** xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/07_clspv_for_production.adoc[Developing with clspv] ** Advanced Data Structures on the GPU -*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/01_introduction.adoc[Introduction] -*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/02_gpu_resident_trees.adoc[GPU-Resident Trees] -*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/03_global_atomic_management.adoc[Global Atomic Management] -*** xref:Advanced_Vulkan_Compute/07_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Device-Addressable Buffers] +*** xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc[GPU-Resident Trees] +*** xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc[Global Atomic Management] +*** xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Device-Addressable Buffers] ** Indirect Dispatch and GPU-Driven Pipelines -*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/01_introduction.adoc[Introduction] -*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/02_indirect_dispatch.adoc[Indirect Dispatch] -*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc[GPU-Side Command Generation] -*** xref:Advanced_Vulkan_Compute/08_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Multi-Draw Indirect (MDI)] +*** xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc[Indirect Dispatch] +*** xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc[GPU-Side Command Generation] +*** xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Multi-Draw Indirect (MDI)] ** Asynchronous Compute Orchestration -*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/01_introduction.adoc[Introduction] -*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/02_concurrent_execution.adoc[Concurrent Execution] -*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/03_timeline_semaphores.adoc[Timeline Semaphores] -*** xref:Advanced_Vulkan_Compute/09_Asynchronous_Compute/04_queue_priority.adoc[Queue Priority] +*** xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc[Concurrent Execution] +*** xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc[Timeline Semaphores] +*** xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc[Queue Priority] ** Cooperative Matrices and Specialized Math -*** xref:Advanced_Vulkan_Compute/10_Specialized_Math/01_introduction.adoc[Introduction] -*** xref:Advanced_Vulkan_Compute/10_Specialized_Math/02_cooperative_matrices.adoc[Cooperative Matrices] -*** xref:Advanced_Vulkan_Compute/10_Specialized_Math/03_mixed_precision.adoc[Mixed Precision] +*** xref:Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc[Cooperative Matrices] +*** xref:Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc[Mixed Precision] ** Performance Auditing and Optimization -*** xref:Advanced_Vulkan_Compute/11_Performance_Optimization/01_introduction.adoc[Introduction] -*** xref:Advanced_Vulkan_Compute/11_Performance_Optimization/02_instruction_throughput.adoc[Instruction Throughput Analysis] -*** xref:Advanced_Vulkan_Compute/11_Performance_Optimization/03_divergence_audit.adoc[The "Divergence" Audit] +*** xref:Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc[Instruction Throughput Analysis] +*** xref:Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc[The "Divergence" Audit] ** Diagnostics and AI-Assisted Compute Refinement -*** xref:Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/01_introduction.adoc[Introduction] -*** xref:Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/02_compute_validation.adoc[Compute Validation] -*** xref:Advanced_Vulkan_Compute/12_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Assistant-Led Optimization] +*** xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc[Introduction] +*** xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc[Compute Validation] +*** xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Assistant-Led Optimization] ** xref:Advanced_Vulkan_Compute/conclusion.adoc[Conclusion] diff --git a/attachments/compute/02_compute_architecture.cpp b/attachments/compute/02_compute_architecture.cpp new file mode 100644 index 00000000..31ee6e44 --- /dev/null +++ b/attachments/compute/02_compute_architecture.cpp @@ -0,0 +1,1250 @@ +// Chapter 2 – Compute Architecture: Mandelbrot Explorer +// +// Demonstrates: +// • Querying and printing physical-device compute limits (subgroup size, +// max workgroup invocations) – the "compute architecture" content +// • A pure compute pipeline that renders directly into a storage image +// • Blit from the storage image to the swapchain (no render pass needed) +// • Double-buffered per-frame resources to avoid storage-image data races +// • Interactive pan/zoom via GLFW scroll and drag callbacks +// • Animated smooth coloring with the IQ cosine palette +// +// Build: see CMakeLists.txt – add WINDOWED to add_compute_chapter() +// Shader: shaders/slang.spv (compiled from 02_compute_architecture.slang) + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN // required only for glfwCreateWindowSurface +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr int kMaxFrames = 2; +// Binary semaphores for image acquisition must not be reused while the +// presentation engine still holds a reference. Having one more acquire +// semaphore than frames-in-flight guarantees the rotating pool is safe. +constexpr int kAcquireSemas = kMaxFrames + 1; +// Minimum zoom (world-units/pixel). With perturbation theory the per-pixel +// delta stays in full double-float precision regardless of depth, so the limit +// is now set by float underflow of the delta rather than the centre's ULP. +// ~1e-30 is comfortably reachable before deltas denormalise. +constexpr long double kMinZoom = 1e-30L; + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// Push-constant layout – must be byte-identical to MandelbrotPush in the shader +// +// The centre is split into (hi, lo) float pairs using Veltkamp splitting so +// the shader can reconstruct the full double-precision centre in double-float +// (two-word float) form, enabling zoom depths around 1e-13. +// --------------------------------------------------------------------------- +// zoom is split into (hi, lo) float pairs using the same Veltkamp technique as +// the centre, so the per-pixel offset dx = pixel_offset * zoom is computed in +// double-float inside the shader. This extends the practical zoom limit from +// ~1e-13 (single-float zoom) to ~1e-26 before adjacent pixels become identical. +// +// The iteration band [minIter, maxIter] is a moving window: minIter slides up +// with zoom depth so the shader only resolves detail in the current zoom layer. +// Pixels escaping before minIter belong to coarser layers that are no longer +// the focus; they are still drawn dimmed. Both bounds are derived entirely +// from m_zoom — no manual iteration adjustment is needed. +struct MandelbrotPush +{ + float zoomHi; // float(m_zoom) + float zoomLo; // float(m_zoom - double(zoomHi)) — sub-ULP residual + uint32_t width; + uint32_t height; + uint32_t minIter; // window floor (dimmed below this) + uint32_t maxIter; // window ceiling = auto-scaled total iterations + uint32_t refLen; // valid length of the reference orbit (perturbation) + float colorPhase; +}; +static_assert(sizeof(MandelbrotPush) == 32, "push constant size mismatch"); + +// Reference-orbit capacity. Must be ≥ the largest maxIter we ever push, which +// recordCommands() clamps to 131072. Each entry is one float4 (two double- +// floats: real hi/lo, imag hi/lo) = 16 bytes → 2 MiB per buffer. +constexpr uint32_t kMaxRefIter = 131072u; + +// --------------------------------------------------------------------------- +// MandelbrotApp +// --------------------------------------------------------------------------- +class MandelbrotApp +{ + public: + void run() + { + initWindow(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + // ----------------------------------------------------------------------- + // Window + view state + // ----------------------------------------------------------------------- + GLFWwindow *m_window = nullptr; + bool m_resized = false; + bool m_dragging = false; + double m_lastMx = 0.0, m_lastMy = 0.0; + + // View parameters stored as long double for precise navigation at deep zoom + // levels; the per-pixel detail itself comes from the perturbation delta, so + // these only need to locate the reference orbit accurately. + long double m_cx = -0.5L; + long double m_cy = 0.0L; + long double m_zoom = 3.5L / kWidth; // fits the full set in the default window + uint32_t m_maxIter = 256u; + float m_phase = 0.0f; + + // ----------------------------------------------------------------------- + // Core Vulkan handles + // ----------------------------------------------------------------------- + vk::raii::Context m_ctx; + vk::raii::Instance m_instance = nullptr; + vk::raii::DebugUtilsMessengerEXT m_debugMessenger = nullptr; + vk::raii::SurfaceKHR m_surface = nullptr; + vk::raii::PhysicalDevice m_physDev = nullptr; + vk::raii::Device m_device = nullptr; + uint32_t m_queueFamily = ~0u; + vk::raii::Queue m_queue = nullptr; + + // ----------------------------------------------------------------------- + // Swapchain + // ----------------------------------------------------------------------- + vk::raii::SwapchainKHR m_swapchain = nullptr; + std::vector m_swapImages; + vk::SurfaceFormatKHR m_swapFormat{}; + vk::Extent2D m_swapExtent{}; + + // ----------------------------------------------------------------------- + // Pipelines / layouts + // ----------------------------------------------------------------------- + vk::raii::DescriptorSetLayout m_dsLayout = nullptr; + vk::raii::PipelineLayout m_pipeLayout = nullptr; + vk::raii::Pipeline m_computePipeline = nullptr; + + // Command pool must be declared before m_frames so that it is destroyed + // AFTER m_frames (reverse declaration order). PerFrame::cmdBuf calls + // vkFreeCommandBuffers on this pool from its destructor; the pool must + // still be alive at that point. + vk::raii::CommandPool m_cmdPool = nullptr; + + // ----------------------------------------------------------------------- + // Per-frame resources (kMaxFrames = 2) + // Each frame has its own storage image so the two in-flight frames never + // race on the same image data. + // ----------------------------------------------------------------------- + struct PerFrame + { + // Storage image written by the compute shader + vk::raii::Image storImg = nullptr; + vk::raii::DeviceMemory storMem = nullptr; + vk::raii::ImageView storView = nullptr; + + // One descriptor pool + set per frame; the pool is reset on swapchain + // recreate (no eFreeDescriptorSet needed). + vk::raii::DescriptorPool dsPool = nullptr; + vk::DescriptorSet dsSet = nullptr; // raw handle, owned by pool + + // Reference orbit (perturbation theory) — host-visible, persistently + // mapped, refilled by the CPU each frame at the current view centre. + // Memory declared before buffer so RAII destroys the buffer first. + vk::raii::DeviceMemory refMem = nullptr; + vk::raii::Buffer refBuf = nullptr; + void *refMapped = nullptr; + + vk::raii::CommandBuffer cmdBuf = nullptr; + vk::raii::Fence fence = nullptr; + }; + std::array m_frames; + + // Acquire semaphores: rotating pool of kAcquireSemas = kMaxFrames+1 entries + // so we never re-signal a semaphore the presentation engine still holds. + std::vector m_imageAvail; + int m_acquireIdx = 0; + + // renderDone semaphores are indexed by swapchain IMAGE INDEX (not frame slot). + // This guarantees the semaphore has been consumed by the presentation engine + // before it is re-signalled: image I can only be re-acquired after its + // previous presentation completes, which consumes renderDone[I]. + std::vector m_renderDone; + + uint32_t m_frameIdx = 0; + + std::vector m_devExts = {vk::KHRSwapchainExtensionName}; + + // ======================================================================= + // Window + // ======================================================================= + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + + m_window = glfwCreateWindow(kWidth, kHeight, + "Mandelbrot | scroll=zoom drag=pan R=reset =/- iterations", + nullptr, nullptr); + glfwSetWindowUserPointer(m_window, this); + glfwSetFramebufferSizeCallback(m_window, cbResize); + glfwSetScrollCallback(m_window, cbScroll); + glfwSetMouseButtonCallback(m_window, cbMouseButton); + glfwSetCursorPosCallback(m_window, cbCursorPos); + glfwSetKeyCallback(m_window, cbKey); + } + + // ----------------------------------------------------------------------- + // GLFW callbacks (static → member via glfwGetWindowUserPointer) + // ----------------------------------------------------------------------- + static void cbResize(GLFWwindow *w, int, int) + { + static_cast(glfwGetWindowUserPointer(w))->m_resized = true; + } + + static void cbScroll(GLFWwindow *w, double /*dx*/, double dy) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + int iw, ih; + glfwGetWindowSize(w, &iw, &ih); + double W = iw, H = ih; + + double mx, my; + glfwGetCursorPos(w, &mx, &my); + + // Zoom toward the cursor: keep the world point under the cursor fixed. + // World coordinates stay in long double so navigation does not lose + // precision as the zoom deepens. + long double factor = (dy > 0.0) ? 0.85L : (1.0L / 0.85L); + long double wx = app->m_cx + (static_cast(mx) - W * 0.5L) * app->m_zoom; + long double wy = app->m_cy + (static_cast(my) - H * 0.5L) * app->m_zoom; + app->m_zoom *= factor; + app->m_zoom = std::max(app->m_zoom, kMinZoom); + app->m_cx = wx - (static_cast(mx) - W * 0.5L) * app->m_zoom; + app->m_cy = wy - (static_cast(my) - H * 0.5L) * app->m_zoom; + } + + static void cbMouseButton(GLFWwindow *w, int button, int action, int /*mods*/) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (button == GLFW_MOUSE_BUTTON_LEFT) + { + app->m_dragging = (action == GLFW_PRESS); + glfwGetCursorPos(w, &app->m_lastMx, &app->m_lastMy); + } + } + + static void cbCursorPos(GLFWwindow *w, double mx, double my) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (app->m_dragging) + { + double dx = mx - app->m_lastMx; + double dy = my - app->m_lastMy; + // Pan: move the centre in the opposite direction to the drag + app->m_cx -= dx * app->m_zoom; + app->m_cy -= dy * app->m_zoom; + } + app->m_lastMx = mx; + app->m_lastMy = my; + } + + static void cbKey(GLFWwindow *w, int key, int /*scancode*/, int action, int /*mods*/) + { + if (action != GLFW_PRESS) + return; + auto *app = static_cast(glfwGetWindowUserPointer(w)); + switch (key) + { + case GLFW_KEY_R: + app->m_cx = -0.5L; + app->m_cy = 0.0L; + app->m_zoom = 3.5L / kWidth; + app->m_maxIter = 256u; + break; + case GLFW_KEY_EQUAL: // '+' / '=' on most keyboards + app->m_maxIter = std::min(app->m_maxIter * 2u, 4096u); + break; + case GLFW_KEY_MINUS: + app->m_maxIter = std::max(app->m_maxIter / 2u, 32u); + break; + case GLFW_KEY_ESCAPE: + glfwSetWindowShouldClose(w, GLFW_TRUE); + break; + default: break; + } + } + + // ======================================================================= + // Vulkan init sequence + // ======================================================================= + void initVulkan() + { + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createCommandPool(); + createSwapchain(); + createDescriptorSetLayout(); + createPipeline(); + createPerFrameResources(); + } + + // ======================================================================= + // Main loop + // ======================================================================= + void mainLoop() + { + auto startTime = std::chrono::steady_clock::now(); + + while (!glfwWindowShouldClose(m_window)) + { + glfwPollEvents(); + + // Animated color phase: one full cycle every ~20 seconds + auto now = std::chrono::steady_clock::now(); + float elapsed = std::chrono::duration(now - startTime).count(); + m_phase = std::fmod(elapsed * 0.05f, 1.0f); + + drawFrame(); + } + m_device.waitIdle(); + } + + void cleanup() + { + // Explicitly destroy every Vulkan RAII handle in dependency order + // BEFORE calling glfwTerminate(). glfwTerminate() calls + // _glfwTerminateVulkan() which dlclose()'s libvulkan.so; any RAII + // destructor that fires after that point will call through an + // unmapped function pointer and SIGSEGV. + // + // Assigning nullptr to a vk::raii handle immediately runs its + // destructor and leaves the wrapper in a null state, so the + // automatic member destructors that follow become no-ops. + + m_renderDone.clear(); + m_imageAvail.clear(); + for (auto &f : m_frames) + { + f.fence = nullptr; + f.cmdBuf = nullptr; + f.dsPool = nullptr; // raw f.dsSet freed by pool + f.refBuf = nullptr; // unmaps + frees refMem on destruction + f.refMem = nullptr; + f.storView = nullptr; + f.storMem = nullptr; + f.storImg = nullptr; + } + m_cmdPool = nullptr; + m_computePipeline = nullptr; + m_pipeLayout = nullptr; + m_dsLayout = nullptr; + m_swapchain = nullptr; + m_queue = nullptr; + m_device = nullptr; // all device-owned objects already freed above + m_surface = nullptr; + m_debugMessenger = nullptr; + m_instance = nullptr; + // m_ctx holds no Vulkan objects; let it destruct normally. + + glfwDestroyWindow(m_window); + glfwTerminate(); + m_window = nullptr; + } + + // ======================================================================= + // Instance + // ======================================================================= + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "Mandelbrot Explorer", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion13}; + + std::vector layers; + if (kEnableValidation) + layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto layerProps = m_ctx.enumerateInstanceLayerProperties(); + for (auto const *req : layers) + { + bool found = std::ranges::any_of(layerProps, [req](auto const &lp) { + return strcmp(lp.layerName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required layer not available: " + std::string(req)); + } + + auto exts = getRequiredInstanceExtensions(); + auto extProps = m_ctx.enumerateInstanceExtensionProperties(); + for (auto const *req : exts) + { + bool found = std::ranges::any_of(extProps, [req](auto const &ep) { + return strcmp(ep.extensionName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required extension not available: " + std::string(req)); + } + + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(exts.size()), + .ppEnabledExtensionNames = exts.data()}; + m_instance = vk::raii::Instance(m_ctx, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) + return; + vk::DebugUtilsMessageSeverityFlagsEXT sev( + vk::DebugUtilsMessageSeverityFlagBitsEXT::eVerbose | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError); + vk::DebugUtilsMessageTypeFlagsEXT type( + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation); + vk::DebugUtilsMessengerCreateInfoEXT ci{ + .messageSeverity = sev, + .messageType = type, + .pfnUserCallback = &debugCallback}; + m_debugMessenger = m_instance.createDebugUtilsMessengerEXT(ci); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*m_instance, m_window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface!"); + m_surface = vk::raii::SurfaceKHR(m_instance, raw); + } + + // ======================================================================= + // Physical device + // ======================================================================= + void pickPhysicalDevice() + { + // Prefer discrete GPU > integrated GPU > virtual GPU > anything else. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : m_instance.enumeratePhysicalDevices()) + { + // Need: compute queue, swapchain extension, present support + auto qfps = pd.getQueueFamilyProperties(); + uint32_t qf = ~0u; + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + bool hasCompute = !!(qfps[i].queueFlags & vk::QueueFlagBits::eCompute); + bool hasPresent = pd.getSurfaceSupportKHR(i, *m_surface); + if (hasCompute && hasPresent) + { + qf = i; + break; + } + } + if (qf == ~0u) + continue; + + auto devExts = pd.enumerateDeviceExtensionProperties(); + bool hasSwapchain = std::ranges::any_of(devExts, [](auto const &e) { + return strcmp(e.extensionName, vk::KHRSwapchainExtensionName) == 0; + }); + if (!hasSwapchain) + continue; + + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; m_physDev = pd; m_queueFamily = qf; } + } + if (!*m_physDev) + throw std::runtime_error("No suitable GPU found!"); + + // Print compute architecture information – this is the educational content + // for this chapter. + vk::PhysicalDeviceSubgroupProperties subgroupProps{}; + vk::PhysicalDeviceProperties2 props2{.pNext = &subgroupProps}; + m_physDev.getProperties2(&props2); + + std::cout << "=== Compute Architecture ===\n"; + std::cout << " Device : " << props2.properties.deviceName.data() << '\n'; + std::cout << " Subgroup size : " << subgroupProps.subgroupSize << '\n'; + std::cout << " Max workgroup invocations : " << props2.properties.limits.maxComputeWorkGroupInvocations << '\n'; + std::cout << "============================\n"; + } + + // ======================================================================= + // Logical device + // ======================================================================= + void createLogicalDevice() + { + // Vulkan 1.3: synchronization2 + dynamicRendering (required for blit path) + // Vulkan 1.2: timelineSemaphore + scalarBlockLayout + vk::StructureChain< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features> + featureChain = { + {}, + {.scalarBlockLayout = true, .timelineSemaphore = true}, + {.synchronization2 = true, .dynamicRendering = true}}; + + float prio = 1.0f; + vk::DeviceQueueCreateInfo qci{ + .queueFamilyIndex = m_queueFamily, + .queueCount = 1, + .pQueuePriorities = &prio}; + vk::DeviceCreateInfo dci{ + .pNext = &featureChain.get(), + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qci, + .enabledExtensionCount = static_cast(m_devExts.size()), + .ppEnabledExtensionNames = m_devExts.data()}; + m_device = vk::raii::Device(m_physDev, dci); + m_queue = vk::raii::Queue(m_device, m_queueFamily, 0); + } + + // ======================================================================= + // Command pool (reset-per-buffer so we can re-record each frame) + // ======================================================================= + void createCommandPool() + { + vk::CommandPoolCreateInfo ci{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = m_queueFamily}; + m_cmdPool = vk::raii::CommandPool(m_device, ci); + } + + // ======================================================================= + // Swapchain + // ======================================================================= + void createSwapchain(vk::SwapchainKHR oldSwapchain = nullptr) + { + auto caps = m_physDev.getSurfaceCapabilitiesKHR(*m_surface); + m_swapExtent = chooseExtent(caps); + + auto fmts = m_physDev.getSurfaceFormatsKHR(*m_surface); + m_swapFormat = chooseFormat(fmts); + + auto modes = m_physDev.getSurfacePresentModesKHR(*m_surface); + auto presentMode = chooseMode(modes); + + uint32_t imgCount = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0u) + imgCount = std::min(imgCount, caps.maxImageCount); + + vk::SwapchainCreateInfoKHR sci{ + .surface = *m_surface, + .minImageCount = imgCount, + .imageFormat = m_swapFormat.format, + .imageColorSpace = m_swapFormat.colorSpace, + .imageExtent = m_swapExtent, + .imageArrayLayers = 1, + // eTransferDst: the swapchain images are blit destinations, not render targets + .imageUsage = vk::ImageUsageFlagBits::eTransferDst, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = presentMode, + .clipped = true, + .oldSwapchain = oldSwapchain}; + m_swapchain = vk::raii::SwapchainKHR(m_device, sci); + m_swapImages = m_swapchain.getImages(); + } + + // ======================================================================= + // Descriptor set layout + // binding 0 = output storage image + // binding 1 = reference-orbit storage buffer (perturbation) + // ======================================================================= + void createDescriptorSetLayout() + { + std::array bindings{{ + {.binding = 0, .descriptorType = vk::DescriptorType::eStorageImage, + .descriptorCount = 1, .stageFlags = vk::ShaderStageFlagBits::eCompute}, + {.binding = 1, .descriptorType = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1, .stageFlags = vk::ShaderStageFlagBits::eCompute}, + }}; + vk::DescriptorSetLayoutCreateInfo ci{ + .bindingCount = static_cast(bindings.size()), + .pBindings = bindings.data()}; + m_dsLayout = vk::raii::DescriptorSetLayout(m_device, ci); + } + + // ======================================================================= + // Compute pipeline + // ======================================================================= + void createPipeline() + { + auto code = readFile("shaders/slang.spv"); + vk::ShaderModuleCreateInfo smci{ + .codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}; + vk::raii::ShaderModule shaderModule(m_device, smci); + + // Push constant range: 44 bytes covering all members of MandelbrotPush + vk::PushConstantRange pcRange{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(MandelbrotPush)}; + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_dsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcRange}; + m_pipeLayout = vk::raii::PipelineLayout(m_device, plci); + + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shaderModule, + .pName = "compMain"}; + vk::ComputePipelineCreateInfo pci{.stage = stage, .layout = *m_pipeLayout}; + m_computePipeline = vk::raii::Pipeline(m_device, nullptr, pci); + } + + // ======================================================================= + // Per-frame resources + // Creates storage image + view + descriptor pool/set + sync objects + // for each of the kMaxFrames slots. + // ======================================================================= + void createPerFrameResources() + { + // Allocate command buffers for all frames from the shared pool + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = kMaxFrames}; + auto cmdBufs = vk::raii::CommandBuffers(m_device, cbai); + + for (int i = 0; i < kMaxFrames; ++i) + { + auto &f = m_frames[i]; + + // -- Storage image -- + createStorageImage(f); + + // -- Reference-orbit buffer (created once; survives swapchain recreate) -- + createReferenceBuffer(f); + + // -- Descriptor pool (no eFreeDescriptorSet: reset the whole pool on recreate) -- + std::array poolSizes{{ + {.type = vk::DescriptorType::eStorageImage, .descriptorCount = 1}, + {.type = vk::DescriptorType::eStorageBuffer, .descriptorCount = 1}, + }}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = static_cast(poolSizes.size()), + .pPoolSizes = poolSizes.data()}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + // -- Descriptor set -- + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + // Allocate via RAII then release the raw handle — the pool owns the lifetime. + // Using release() avoids triggering vkFreeDescriptorSets on the temporary. + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + writeFrameDescriptors(f); + + // -- Command buffer -- + f.cmdBuf = std::move(cmdBufs[i]); + + // Fence starts signalled so the first waitForFences on frame 0 returns immediately + f.fence = vk::raii::Fence(m_device, vk::FenceCreateInfo{ + .flags = vk::FenceCreateFlagBits::eSignaled}); + } + + // Rotating pool of acquire semaphores (kAcquireSemas = kMaxFrames + 1) + m_imageAvail.clear(); + for (int i = 0; i < kAcquireSemas; ++i) + m_imageAvail.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + // renderDone semaphores – one per swapchain image (indexed by acquired image index) + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + // Transition all storage images to eGeneral before entering the render loop + transitionStorageImagesToGeneral(); + } + + // Allocate a host-visible, persistently-mapped reference-orbit buffer for + // one frame slot. These do NOT depend on the swapchain size, so they are + // created once and survive swapchain recreation. + void createReferenceBuffer(PerFrame &f) + { + constexpr vk::DeviceSize sz = vk::DeviceSize(kMaxRefIter) * 4u * sizeof(float); + vk::BufferCreateInfo bci{ + .size = sz, + .usage = vk::BufferUsageFlagBits::eStorageBuffer, + .sharingMode = vk::SharingMode::eExclusive}; + f.refBuf = vk::raii::Buffer(m_device, bci); + + auto memReqs = f.refBuf.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, + vk::MemoryPropertyFlagBits::eHostVisible | + vk::MemoryPropertyFlagBits::eHostCoherent)}; + f.refMem = vk::raii::DeviceMemory(m_device, mai); + f.refBuf.bindMemory(*f.refMem, 0); + f.refMapped = f.refMem.mapMemory(0, sz); + } + + // Compute the reference orbit X_n at the current view centre in long-double + // precision, packing each X_n as two double-floats (real hi/lo, imag hi/lo) + // into f.refMapped. Returns the number of valid entries (refLen): either + // maxIter, or the iteration at which the reference escaped |X| > 2. + [[nodiscard]] uint32_t fillReferenceOrbit(PerFrame &f, uint32_t maxIter) const + { + maxIter = std::min(maxIter, kMaxRefIter); + const long double cr = m_cx; + const long double ci = m_cy; + long double zr = 0.0L, zi = 0.0L; + auto *dst = static_cast(f.refMapped); + + uint32_t n = 0; + while (n < maxIter) + { + // Store X_n as two double-floats. + float zrHi = static_cast(zr); + float ziHi = static_cast(zi); + dst[n * 4 + 0] = zrHi; + dst[n * 4 + 1] = static_cast(zr - static_cast(zrHi)); + dst[n * 4 + 2] = ziHi; + dst[n * 4 + 3] = static_cast(zi - static_cast(ziHi)); + ++n; + + if (zr * zr + zi * zi > 4.0L) + break; // X_{n-1} escaped — reference is valid up to here + + long double nzr = zr * zr - zi * zi + cr; + long double nzi = 2.0L * zr * zi + ci; + zr = nzr; + zi = nzi; + } + return n; + } + + // Write both descriptor bindings for one frame slot: + // binding 0 = output storage image (GENERAL layout) + // binding 1 = reference-orbit storage buffer + void writeFrameDescriptors(PerFrame &f) + { + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + vk::DescriptorBufferInfo refInfo{ + .buffer = *f.refBuf, + .offset = 0, + .range = VK_WHOLE_SIZE}; + + std::array writes{{ + {.dstSet = f.dsSet, .dstBinding = 0, .dstArrayElement = 0, .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, .pImageInfo = &imgInfo}, + {.dstSet = f.dsSet, .dstBinding = 1, .dstArrayElement = 0, .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, .pBufferInfo = &refInfo}, + }}; + m_device.updateDescriptorSets(writes, {}); + } + + // Allocate + bind a device-local storage image for one frame slot + void createStorageImage(PerFrame &f) + { + vk::ImageCreateInfo ici{ + .imageType = vk::ImageType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .extent = {m_swapExtent.width, m_swapExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + // eStorage: written by compute; eTransferSrc: blitted to swapchain + .usage = vk::ImageUsageFlagBits::eStorage | + vk::ImageUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive, + .initialLayout = vk::ImageLayout::eUndefined}; + f.storImg = vk::raii::Image(m_device, ici); + + auto memReqs = f.storImg.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + f.storMem = vk::raii::DeviceMemory(m_device, mai); + f.storImg.bindMemory(*f.storMem, 0); + + vk::ImageViewCreateInfo ivci{ + .image = *f.storImg, + .viewType = vk::ImageViewType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + f.storView = vk::raii::ImageView(m_device, ivci); + } + + // One-shot command to transition all storage images from UNDEFINED to GENERAL + // before the render loop begins. They stay in GENERAL permanently; the + // compute→transfer barrier uses srcLayout=eGeneral / dstLayout=eGeneral. + void transitionStorageImagesToGeneral() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(m_device, cbai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + + for (auto &f : m_frames) + { + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = &barrier}); + } + + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // ======================================================================= + // Draw frame + // ======================================================================= + void drawFrame() + { + auto &f = m_frames[m_frameIdx]; + + // Wait for this frame slot's previous work to complete + auto waitRes = m_device.waitForFences(*f.fence, vk::True, UINT64_MAX); + if (waitRes != vk::Result::eSuccess) + throw std::runtime_error("waitForFences failed"); + + // Pick the next acquire semaphore from the rotating pool. + // This ensures we never reuse a semaphore the presentation engine still holds. + auto& acqSem = m_imageAvail[m_acquireIdx]; + m_acquireIdx = (m_acquireIdx + 1) % kAcquireSemas; + + // Acquire swapchain image + uint32_t imageIndex; + { + auto [res, idx] = m_swapchain.acquireNextImage(UINT64_MAX, *acqSem, nullptr); + if (res == vk::Result::eErrorOutOfDateKHR) + { + recreateSwapchain(); + return; + } + imageIndex = idx; + } + + m_device.resetFences(*f.fence); + + // Record command buffer + recordCommands(f, imageIndex); + + // Use the renderDone semaphore indexed by the acquired image — not by frame slot. + // This prevents re-signalling it before the presentation engine has consumed it. + auto& rdSem = m_renderDone[imageIndex]; + + // Submit + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eTransfer; + vk::SubmitInfo si{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*acqSem, + .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*f.cmdBuf, + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*rdSem}; + m_queue.submit(si, *f.fence); + + // Present + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*rdSem, + .swapchainCount = 1, + .pSwapchains = &*m_swapchain, + .pImageIndices = &imageIndex}; + auto pres = m_queue.presentKHR(pi); + if (pres == vk::Result::eSuboptimalKHR || + pres == vk::Result::eErrorOutOfDateKHR || + m_resized) + { + m_resized = false; + recreateSwapchain(); + } + + m_frameIdx = (m_frameIdx + 1) % kMaxFrames; + } + + void recordCommands(PerFrame &f, uint32_t imageIndex) + { + auto &cb = f.cmdBuf; + cb.reset(); + cb.begin({}); + + // 1. Bind compute pipeline + this frame's descriptor set (storage image) + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_computePipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, *m_pipeLayout, + 0, {f.dsSet}, {}); + + // 2. Push current view state. + // Split the zoom into (hi, lo) float pairs so the shader computes the + // per-pixel delta δc = pixelOffset · zoom in full double-float precision. + auto splitDouble = [](long double v) -> std::pair { + float hi = static_cast(v); + float lo = static_cast(v - static_cast(hi)); + return {hi, lo}; + }; + auto [zoomHi, zoomLo] = splitDouble(m_zoom); + + // Derive the iteration window entirely from zoom depth — no user input needed. + // logDepth = 0 at the initial view, grows by 1 for each 2× zoom-in. + // autoMax: total iterations required to resolve detail at this depth. + // windowSize: colour-visible band (m_maxIter lets the user widen/narrow it). + // minIter: window floor — pixels escaping below this are dimmed as coarser layers. + constexpr long double kInitialZoom = 3.5L / kWidth; + double logDepth = std::max(0.0, std::log2(static_cast(kInitialZoom / m_zoom))); + uint32_t autoMax = static_cast( + std::clamp(256.0 * (1.0 + 0.5 * logDepth), 256.0, double(kMaxRefIter))); + uint32_t windowSize = std::min(autoMax, m_maxIter); + uint32_t minIter = (autoMax > windowSize) ? autoMax - windowSize : 0u; + + // Compute the reference orbit for this frame at the view centre. The + // shader iterates only the per-pixel delta against this orbit, which is + // what lets the zoom go far past the centre's own ULP without the image + // degrading into flat rectangles. + uint32_t refLen = fillReferenceOrbit(f, autoMax); + + MandelbrotPush push{ + .zoomHi = zoomHi, + .zoomLo = zoomLo, + .width = m_swapExtent.width, + .height = m_swapExtent.height, + .minIter = minIter, + .maxIter = autoMax, + .refLen = refLen, + .colorPhase = m_phase}; + cb.pushConstants(*m_pipeLayout, + vk::ShaderStageFlagBits::eCompute, 0, push); + + // 3. Dispatch: one thread per pixel, workgroup tile 16×16 + uint32_t gx = (m_swapExtent.width + 15u) / 16u; + uint32_t gy = (m_swapExtent.height + 15u) / 16u; + cb.dispatch(gx, gy, 1); + + // 4. Barrier: wait for compute writes to finish before the blit reads them. + // The storage image stays in eGeneral throughout – we only flip the + // access mask / pipeline stage. + vk::ImageMemoryBarrier2 storToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferRead, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + // 5. Barrier: swapchain image UNDEFINED → TRANSFER_DST_OPTIMAL + vk::ImageMemoryBarrier2 swapToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eTransferDstOptimal, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array preBlitBarriers{storToTransfer, swapToTransfer}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(preBlitBarriers.size()), + .pImageMemoryBarriers = preBlitBarriers.data()}); + + // 6. Blit storage image → swapchain (NEAREST: pixel-exact copy, no filtering artefacts) + vk::ImageSubresourceLayers subres{vk::ImageAspectFlagBits::eColor, 0, 0, 1}; + vk::Offset3D zero{0, 0, 0}; + vk::Offset3D ext{ + static_cast(m_swapExtent.width), + static_cast(m_swapExtent.height), 1}; + vk::ImageBlit2 region{ + .srcSubresource = subres, + .srcOffsets = std::array{zero, ext}, + .dstSubresource = subres, + .dstOffsets = std::array{zero, ext}}; + vk::BlitImageInfo2 blitInfo{ + .srcImage = *f.storImg, + .srcImageLayout = vk::ImageLayout::eGeneral, + .dstImage = m_swapImages[imageIndex], + .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, + .pRegions = ®ion, + .filter = vk::Filter::eNearest}; + cb.blitImage2(blitInfo); + + // 7. Post-blit barriers: + // a. Swapchain image: TRANSFER_DST → PRESENT_SRC + // b. Storage image: release the transfer-read so next frame's + // compute shader can write again (GENERAL → GENERAL, flip access) + vk::ImageMemoryBarrier2 swapToPresent{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eBottomOfPipe, + .dstAccessMask = vk::AccessFlagBits2::eNone, + .oldLayout = vk::ImageLayout::eTransferDstOptimal, + .newLayout = vk::ImageLayout::ePresentSrcKHR, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + vk::ImageMemoryBarrier2 storRelease{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferRead, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array postBlitBarriers{swapToPresent, storRelease}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(postBlitBarriers.size()), + .pImageMemoryBarriers = postBlitBarriers.data()}); + + cb.end(); + } + + // ======================================================================= + // Swapchain recreation (window resize or suboptimal) + // ======================================================================= + void recreateSwapchain() + { + // Block while the window is minimized + int w = 0, h = 0; + glfwGetFramebufferSize(m_window, &w, &h); + while (w == 0 || h == 0) + { + glfwGetFramebufferSize(m_window, &w, &h); + glfwWaitEvents(); + } + + m_device.waitIdle(); + + // Destroy per-frame storage images/views/pools (set to nullptr) + for (auto &f : m_frames) + { + f.storView = nullptr; + f.storImg = nullptr; + f.storMem = nullptr; + f.dsPool = nullptr; + f.dsSet = nullptr; + } + + // Recreate swapchain reusing the old handle for efficiency + vk::SwapchainKHR oldHandle = *m_swapchain; + createSwapchain(oldHandle); + // The old swapchain RAII object is still live; replace it now + // (createSwapchain already wrote m_swapchain = new handle) + + // Recreate per-frame images at the new resolution and re-bind descriptors + for (auto &f : m_frames) + createStorageImage(f); + + // Re-create descriptor pools and update bindings. The reference-orbit + // buffers are size-independent and persist across recreation; we just + // re-point the new descriptor sets at them. + for (auto &f : m_frames) + { + std::array poolSizes{{ + {.type = vk::DescriptorType::eStorageImage, .descriptorCount = 1}, + {.type = vk::DescriptorType::eStorageBuffer, .descriptorCount = 1}, + }}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = static_cast(poolSizes.size()), + .pPoolSizes = poolSizes.data()}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + // Allocate via RAII then release the raw handle — the pool owns the lifetime. + // Using release() avoids triggering vkFreeDescriptorSets on the temporary. + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + writeFrameDescriptors(f); + } + + // Recreate renderDone semaphores to match the new swapchain image count + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + // Transition new storage images to GENERAL before the render loop resumes + transitionStorageImagesToGeneral(); + } + + // ======================================================================= + // Helpers + // ======================================================================= + + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, vk::MemoryPropertyFlags props) const + { + auto memProps = m_physDev.getMemoryProperties(); + for (uint32_t i = 0; i < memProps.memoryTypeCount; ++i) + { + if ((filter & (1u << i)) && + (memProps.memoryTypes[i].propertyFlags & props) == props) + return i; + } + throw std::runtime_error("no suitable memory type"); + } + + static vk::SurfaceFormatKHR chooseFormat(std::vector const &formats) + { + assert(!formats.empty()); + // Prefer B8G8R8A8Unorm (non-sRGB) for accurate colour reproduction + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Unorm && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + // Fall back to sRGB if Unorm is unavailable + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Srgb && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + return formats[0]; + } + + static vk::PresentModeKHR chooseMode(std::vector const &modes) + { + // Mailbox drops old frames rather than queuing them – lowest latency for interactive use + for (auto m : modes) + if (m == vk::PresentModeKHR::eMailbox) + return m; + return vk::PresentModeKHR::eFifo; // always available + } + + vk::Extent2D chooseExtent(vk::SurfaceCapabilitiesKHR const &caps) + { + if (caps.currentExtent.width != std::numeric_limits::max()) + return caps.currentExtent; + int w, h; + glfwGetFramebufferSize(m_window, &w, &h); + return { + std::clamp(w, caps.minImageExtent.width, caps.maxImageExtent.width), + std::clamp(h, caps.minImageExtent.height, caps.maxImageExtent.height)}; + } + + [[nodiscard]] std::vector getRequiredInstanceExtensions() const + { + uint32_t count = 0; + auto raw = glfwGetRequiredInstanceExtensions(&count); + std::vector exts(raw, raw + count); + if (kEnableValidation) + exts.push_back(vk::EXTDebugUtilsExtensionName); + return exts; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + vk::DebugUtilsMessengerCallbackDataEXT const *pData, + void *) + { + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "validation [" << to_string(type) << "]: " << pData->pMessage << '\n'; + return vk::False; + } + + static std::vector readFile(std::string const &path) + { + std::ifstream file(path, std::ios::ate | std::ios::binary); + if (!file.is_open()) + throw std::runtime_error("failed to open: " + path); + std::vector buf(file.tellg()); + file.seekg(0); + file.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +// --------------------------------------------------------------------------- +int main() +{ + try + { + MandelbrotApp app; + app.run(); + } + catch (std::exception const &e) + { + std::cerr << e.what() << '\n'; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/02_compute_architecture.slang b/attachments/compute/02_compute_architecture.slang new file mode 100644 index 00000000..23061ef9 --- /dev/null +++ b/attachments/compute/02_compute_architecture.slang @@ -0,0 +1,259 @@ +// Chapter 2 – Compute Architecture: Mandelbrot Explorer +// +// Compiled with: slangc 02_compute_architecture.slang -o shaders/slang.spv \ +// -profile glsl_460 -target spirv -entry compMain +// +// Uses double-float (two-word float) arithmetic for the full Mandelbrot +// iteration, enabling zoom depths around 1e-13 without float64 hardware. +// The center is split into (hi, lo) float pairs on the CPU; each shader +// invocation reconstructs c with full double-float precision before iterating. + +// Storage image – rgba8 matches the R8G8B8A8Unorm storage image on the C++ side +[[vk::binding(0, 0)]] [[vk::image_format("rgba8")]] RWTexture2D outputImage; + +// Reference orbit (perturbation theory). Element n holds the reference point's +// orbit value X_n as TWO double-floats packed into a float4: +// .xy = X_n.real (hi, lo), .zw = X_n.imag (hi, lo) +// X_n is computed once per frame on the CPU at the view centre, in extended +// precision, then iterated per-pixel only as a small delta. See compMain. +[[vk::binding(1, 0)]] StructuredBuffer refOrbit; + +// Push constants – must be byte-identical to the C++ MandelbrotPush struct. +// +// The view CENTRE is no longer pushed: it IS the reference orbit, so the shader +// never needs its absolute coordinates. Only the per-pixel offset scale (zoom) +// and the iteration window are required. +struct MandelbrotPush +{ + float zoomHi; // zoom hi-word: float(zoom) + float zoomLo; // zoom lo-word: float(zoom - hi) — sub-ULP residual + uint width; + uint height; + uint minIter; // iteration window floor — coarser layers are above this + uint maxIter; // auto-scaled total iterations for this zoom depth + uint refLen; // valid length of refOrbit (where the reference escaped) + float colorPhase; // animated offset into palette cycle [0,1) +}; +[[vk::push_constant]] MandelbrotPush pc; + +// --------------------------------------------------------------------------- +// Double-float arithmetic +// +// A "double-float" (df) is a pair (hi, lo) satisfying |lo| <= 0.5*ulp(hi). +// hi + lo equals the intended value to ~48 bits of precision. +// +// All operations follow Shewchuk's exact arithmetic algorithms and rely on +// IEEE 754 round-to-nearest semantics, which Vulkan mandates for compute. +// --------------------------------------------------------------------------- + +// Quick two-sum: exact split of (a + b) when |a| >= |b|. +float2 df_quick_two_sum(float a, float b) +{ + float s = a + b; + float e = b - (s - a); + return float2(s, e); +} + +// General two-sum: exact split of (a + b) for arbitrary a, b. +float2 df_two_sum(float a, float b) +{ + float s = a + b; + float v = s - a; + float e = (a - (s - v)) + (b - v); + return float2(s, e); +} + +// Veltkamp split: split a 24-bit float into two exact 12-bit halves. +// Used by df_two_product. +float2 df_split(float a) +{ + float t = 4097.0f * a; // (2^12 + 1) * a + float hi = t - (t - a); + float lo = a - hi; + return float2(hi, lo); +} + +// Two-product: compute (a*b, err) such that a*b + err = exact product. +float2 df_two_product(float a, float b) +{ + float p = a * b; + float2 as = df_split(a); + float2 bs = df_split(b); + float e = ((as.x * bs.x - p) + as.x * bs.y + as.y * bs.x) + as.y * bs.y; + return float2(p, e); +} + +// Add a double-float and a single float. +float2 df_add_f(float2 a, float b) +{ + float2 t = df_two_sum(a.x, b); + t.y += a.y; + return df_quick_two_sum(t.x, t.y); +} + +// Add two double-floats. +float2 df_add(float2 a, float2 b) +{ + float2 s = df_two_sum(a.x, b.x); + s.y += a.y + b.y; + return df_quick_two_sum(s.x, s.y); +} + +// Subtract two double-floats. +float2 df_sub(float2 a, float2 b) +{ + return df_add(a, float2(-b.x, -b.y)); +} + +// Square a double-float (cheaper than general multiply). +float2 df_sqr(float2 a) +{ + float2 t = df_two_product(a.x, a.x); + t.y += 2.0f * a.x * a.y; + return df_quick_two_sum(t.x, t.y); +} + +// Multiply two double-floats. +float2 df_mul(float2 a, float2 b) +{ + float2 t = df_two_product(a.x, b.x); + t.y += a.x * b.y + a.y * b.x; + return df_quick_two_sum(t.x, t.y); +} + +// Scale a double-float by a power-of-2 scalar (exact, no rounding). +float2 df_scale2(float2 a, float s) +{ + return float2(a.x * s, a.y * s); +} + +// --------------------------------------------------------------------------- +// IQ cosine palette +// Inigo Quilez's palette function: a + b*cos(2π*(c*t + d)) +// --------------------------------------------------------------------------- +float3 palette(float t) +{ + float3 a = float3(0.5f, 0.5f, 0.5f); + float3 b = float3(0.5f, 0.5f, 0.5f); + float3 c = float3(1.0f, 1.0f, 1.0f); + float3 d = float3(0.0f, 0.33f, 0.67f); + return a + b * cos(6.28318530718f * (c * t + d)); +} + +[numthreads(16, 16, 1)] +[shader("compute")] +void compMain(uint3 dispatchID : SV_DispatchThreadID) +{ + uint px = dispatchID.x; + uint py = dispatchID.y; + + if (px >= pc.width || py >= pc.height) + return; + + // ----------------------------------------------------------------------- + // PERTURBATION THEORY — the key to "infinite" zoom. + // + // Direct iteration computes c = centre + pixelOffset. Once the zoom is so + // deep that pixelOffset is smaller than one ULP of `centre`, the addition + // throws the offset away: every pixel in a region collapses to the same c + // and the image degrades into flat rectangles. + // + // Instead we iterate one REFERENCE orbit X_m (the view centre, computed in + // extended precision on the CPU) and, per pixel, only the SMALL deviation + // δ = z − X_m, δc = pixelOffset · zoom + // via δ ← 2·X_m·δ + δ² + δc. δ never gets added to a large number, so it + // keeps full precision far past the centre's ULP — no more pixel rectangles. + // + // REBASING (Zhuoran's method) makes this robust: whenever the running orbit + // value z = X_m + δ becomes smaller than δ itself — or the stored reference + // runs out (it only spans until the centre escaped) — we "rebase", adopting + // z as the new δ and restarting the reference index m at 0. This is what + // prevents the whole screen collapsing to one colour when the view centre + // lies outside the set (a short reference): the orbit simply wraps around + // the reference instead of being capped. δ is carried in double-float. + // ----------------------------------------------------------------------- + float pxOff = (float)px - (float)pc.width * 0.5f; // exact: integer offset + float pyOff = (float)py - (float)pc.height * 0.5f; + + // δc = pixel offset · zoom, in double-float (pixel offset is exact). + float2 dcr = df_mul(float2(pxOff, 0.0f), float2(pc.zoomHi, pc.zoomLo)); + float2 dci = df_mul(float2(pyOff, 0.0f), float2(pc.zoomHi, pc.zoomLo)); + + float2 dr = float2(0.0f, 0.0f); // δ real (double-float) + float2 di = float2(0.0f, 0.0f); // δ imag + uint m = 0u; // reference index + uint iter = 0u; // true iteration count + float zr_h = 0.0f, zi_h = 0.0f; // hi parts of escaped z (for smooth colour) + + while (iter < pc.maxIter) + { + // δ ← 2·X_m·δ + δ² + δc (complex, double-float) + float4 X = refOrbit[m]; + float2 Xr = X.xy; + float2 Xi = X.zw; + float2 XrDr = df_mul(Xr, dr); + float2 XiDi = df_mul(Xi, di); + float2 XrDi = df_mul(Xr, di); + float2 XiDr = df_mul(Xi, dr); + float2 twoXd_r = df_scale2(df_sub(XrDr, XiDi), 2.0f); + float2 twoXd_i = df_scale2(df_add(XrDi, XiDr), 2.0f); + float2 dsq_r = df_sub(df_sqr(dr), df_sqr(di)); + float2 dsq_i = df_scale2(df_mul(dr, di), 2.0f); + dr = df_add(df_add(twoXd_r, dsq_r), dcr); + di = df_add(df_add(twoXd_i, dsq_i), dci); + ++m; + ++iter; + + // Full orbit value z = X_m + δ (hi parts are enough for the tests). + float4 Xm = refOrbit[m]; + float2 zr = df_add(Xm.xy, dr); + float2 zi = df_add(Xm.zw, di); + zr_h = zr.x; + zi_h = zi.x; + float z2 = zr_h * zr_h + zi_h * zi_h; + if (z2 > 4.0f) + break; // escaped at `iter` + + // Rebase when z is closer to the origin than δ, or the reference ran out. + float d2 = dr.x * dr.x + di.x * di.x; + if (m >= pc.refLen - 1u || z2 < d2) + { + dr = zr; + di = zi; + m = 0u; + } + } + + float4 color; + if (iter == pc.maxIter) + { + // Never escaped within the window: interior, draw black. + color = float4(0.0f, 0.0f, 0.0f, 1.0f); + } + else + { + // Smooth (continuous) iteration count from the escaped magnitude |z|. + float mag2 = max(zr_h * zr_h + zi_h * zi_h, 1.0f); + float smooth = (float)iter + 1.0f - log2(log2(mag2) * 0.5f); + + if (iter < pc.minIter) + { + // Escaped before the window floor: this pixel belongs to a coarser + // zoom layer that is "above" the current view. Dim it so it recedes + // into the background, leaving the window band as the visual focus. + float t = frac(smooth * 0.015f + pc.colorPhase); + color = float4(palette(t) * 0.18f, 1.0f); + } + else + { + // Escaped within [minIter, maxIter]: this is the detail layer for + // the current zoom. Map the window to the full colour cycle so the + // palette is always used at full contrast regardless of depth. + float windowSize = (float)(pc.maxIter - pc.minIter); + float t = frac((smooth - (float)pc.minIter) / windowSize + pc.colorPhase); + color = float4(palette(t), 1.0f); + } + } + + outputImage[uint2(px, py)] = color; +} diff --git a/attachments/compute/03_memory_models.cpp b/attachments/compute/03_memory_models.cpp new file mode 100644 index 00000000..fc46cff6 --- /dev/null +++ b/attachments/compute/03_memory_models.cpp @@ -0,0 +1,1344 @@ +// Chapter 3 – Memory Models: Interactive 2-D Navier–Stokes Fluid +// +// An Eulerian "Stable Fluids" (Jos Stam) solver. Drag the mouse to push the +// water and paint dye; the velocity field is advected and projected to be +// divergence-free every frame, so the dye swirls like ink in water. +// +// Demonstrates (the "Memory Models" teaching points): +// • Memory barriers between compute dispatches — the seven solver passes +// (splat → advect velocity → divergence → Jacobi×N → gradient → +// advect dye → render) are each separated by a buffer barrier. +// • The pressure Poisson solve is a JACOBI iteration: every dispatch reads the +// previous dispatch's results, so a barrier between each iteration is what +// makes the writes visible — the canonical inter-dispatch hazard. +// +// Controls: +// Left drag – push the fluid and inject dye +// Scroll up/down – stronger / weaker push +// R – reset (clear the water) +// Escape – quit +// +// Build: see CMakeLists.txt – add WINDOWED to add_compute_chapter() +// Shader: shaders/slang.spv (compiled from 03_memory_models.slang) + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr int kMaxFrames = 2; +constexpr int kAcquireSemas = kMaxFrames + 1; + +// Eulerian simulation grid (16:9 to match the window). The solver runs on this +// fixed grid and the result is upscaled to the swapchain in the render pass. +constexpr uint32_t kGridX = 320; +constexpr uint32_t kGridY = 180; +constexpr uint32_t kNumCells = kGridX * kGridY; +constexpr uint32_t kPressureIters = 40; // Jacobi iterations per frame + +constexpr float kDt = 1.0f; // velocity is in cells/step +constexpr float kDissipation = 0.997f; // dye fade per step +constexpr float kVelFade = 0.999f; // velocity damping per step +constexpr float kSplatRadius = 8.0f; // injection radius (cells) +constexpr float kDyeAmount = 0.45f; // dye added under the mouse + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// Push-constant layout – must be byte-identical to FluidPush in the shader +// --------------------------------------------------------------------------- +struct FluidPush +{ + uint32_t nx; + uint32_t ny; + float dt; + float dissipation; + float velFade; + float mouseX; // current mouse, grid coords + float mouseY; + float mousePx; // previous mouse, grid coords + float mousePy; + float splatRadius; + float forceScale; + float dyeAmount; + uint32_t mouseDown; + uint32_t jacobiSrc; // ping-pong selector / final-pressure selector + uint32_t imgWidth; + uint32_t imgHeight; +}; +static_assert(sizeof(FluidPush) == 64, "push constant size mismatch"); + +// --------------------------------------------------------------------------- +// SPHApp +// --------------------------------------------------------------------------- +class SPHApp +{ + public: + void run() + { + initWindow(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + // ----------------------------------------------------------------------- + // Window + sim state + // ----------------------------------------------------------------------- + GLFWwindow *m_window = nullptr; + bool m_resized = false; + bool m_dragging = false; + double m_mouseWinX = 0.0, m_mouseWinY = 0.0; // cursor in window pixels + float m_prevGridX = 0.0f, m_prevGridY = 0.0f; // last frame's mouse (grid) + bool m_haveMouse = false; // seed prev on first drag + float m_forceScale = 0.5f; // scroll adjusts push strength + bool m_resetField = false; // set by R to clear next frame + // (initial state comes from the seed) + + // ----------------------------------------------------------------------- + // Core Vulkan handles + // ----------------------------------------------------------------------- + vk::raii::Context m_ctx; + vk::raii::Instance m_instance = nullptr; + vk::raii::DebugUtilsMessengerEXT m_debugMessenger = nullptr; + vk::raii::SurfaceKHR m_surface = nullptr; + vk::raii::PhysicalDevice m_physDev = nullptr; + vk::raii::Device m_device = nullptr; + uint32_t m_queueFamily = ~0u; + vk::raii::Queue m_queue = nullptr; + + // ----------------------------------------------------------------------- + // Swapchain + // ----------------------------------------------------------------------- + vk::raii::SwapchainKHR m_swapchain = nullptr; + std::vector m_swapImages; + vk::SurfaceFormatKHR m_swapFormat{}; + vk::Extent2D m_swapExtent{}; + + // ----------------------------------------------------------------------- + // GPU fluid field buffers (persistent across frames – single copy). + // Memory declared before buffer so RAII destroys the buffer first. + // ----------------------------------------------------------------------- + struct FieldBuffer { vk::raii::DeviceMemory mem = nullptr; vk::raii::Buffer buf = nullptr; }; + FieldBuffer m_velA, m_velB; // velocity (float2) + scratch + FieldBuffer m_pres0, m_pres1; // pressure ping/pong (float) + FieldBuffer m_div; // divergence (float) + FieldBuffer m_dyeA, m_dyeB; // dye (float) + scratch + + // ----------------------------------------------------------------------- + // Pipelines / layouts — one per solver pass + // ----------------------------------------------------------------------- + vk::raii::DescriptorSetLayout m_dsLayout = nullptr; + vk::raii::PipelineLayout m_pipeLayout = nullptr; + vk::raii::Pipeline m_splatPipe = nullptr; + vk::raii::Pipeline m_advectVelPipe = nullptr; + vk::raii::Pipeline m_divergencePipe = nullptr; + vk::raii::Pipeline m_jacobiPipe = nullptr; + vk::raii::Pipeline m_gradientPipe = nullptr; + vk::raii::Pipeline m_advectDyePipe = nullptr; + vk::raii::Pipeline m_renderPipe = nullptr; + + vk::raii::CommandPool m_cmdPool = nullptr; + + // ----------------------------------------------------------------------- + // Per-frame resources + // ----------------------------------------------------------------------- + struct PerFrame + { + vk::raii::Image storImg = nullptr; + vk::raii::DeviceMemory storMem = nullptr; + vk::raii::ImageView storView = nullptr; + + vk::raii::DescriptorPool dsPool = nullptr; + vk::DescriptorSet dsSet = nullptr; + + vk::raii::CommandBuffer cmdBuf = nullptr; + vk::raii::Fence fence = nullptr; + }; + std::array m_frames; + + std::vector m_imageAvail; + int m_acquireIdx = 0; + + std::vector m_renderDone; + + uint32_t m_frameIdx = 0; + + std::vector m_devExts = {vk::KHRSwapchainExtensionName}; + + // ======================================================================= + // Window + // ======================================================================= + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + + m_window = glfwCreateWindow(kWidth, kHeight, + "Navier-Stokes Fluid | drag=push water scroll=strength R=reset Esc=quit", + nullptr, nullptr); + glfwSetWindowUserPointer(m_window, this); + glfwSetFramebufferSizeCallback(m_window, cbResize); + glfwSetScrollCallback(m_window, cbScroll); + glfwSetMouseButtonCallback(m_window, cbMouseButton); + glfwSetCursorPosCallback(m_window, cbCursorPos); + glfwSetKeyCallback(m_window, cbKey); + } + + // ----------------------------------------------------------------------- + // GLFW callbacks + // ----------------------------------------------------------------------- + static void cbResize(GLFWwindow *w, int, int) + { + static_cast(glfwGetWindowUserPointer(w))->m_resized = true; + } + + static void cbScroll(GLFWwindow *w, double /*dx*/, double dy) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + // Scroll adjusts how hard a drag pushes the water. + app->m_forceScale = std::clamp( + app->m_forceScale * (dy > 0.0 ? 1.25f : 0.8f), 0.05f, 5.0f); + } + + static void cbMouseButton(GLFWwindow *w, int button, int action, int /*mods*/) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (button == GLFW_MOUSE_BUTTON_LEFT) + { + app->m_dragging = (action == GLFW_PRESS); + if (action == GLFW_PRESS) + { + glfwGetCursorPos(w, &app->m_mouseWinX, &app->m_mouseWinY); + app->m_haveMouse = false; // reseed prev so the first step has no jump + } + } + } + + static void cbCursorPos(GLFWwindow *w, double mx, double my) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + app->m_mouseWinX = mx; + app->m_mouseWinY = my; + } + + static void cbKey(GLFWwindow *w, int key, int /*scancode*/, int action, int /*mods*/) + { + if (action != GLFW_PRESS) + return; + auto *app = static_cast(glfwGetWindowUserPointer(w)); + switch (key) + { + case GLFW_KEY_R: + app->m_resetField = true; // cleared at the start of the next frame + break; + case GLFW_KEY_ESCAPE: + glfwSetWindowShouldClose(w, GLFW_TRUE); + break; + default: break; + } + } + + // ======================================================================= + // Vulkan init sequence + // ======================================================================= + void initVulkan() + { + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createCommandPool(); + createSwapchain(); + createFluidBuffers(); + createDescriptorSetLayout(); + createPipelines(); + createPerFrameResources(); + } + + // ======================================================================= + // Main loop + // ======================================================================= + void mainLoop() + { + while (!glfwWindowShouldClose(m_window)) + { + glfwPollEvents(); + drawFrame(); + } + m_device.waitIdle(); + } + + void cleanup() + { + m_renderDone.clear(); + m_imageAvail.clear(); + for (auto &f : m_frames) + { + f.fence = nullptr; + f.cmdBuf = nullptr; + f.dsPool = nullptr; + f.storView = nullptr; + f.storMem = nullptr; + f.storImg = nullptr; + } + m_cmdPool = nullptr; + m_renderPipe = nullptr; + m_advectDyePipe = nullptr; + m_gradientPipe = nullptr; + m_jacobiPipe = nullptr; + m_divergencePipe = nullptr; + m_advectVelPipe = nullptr; + m_splatPipe = nullptr; + m_pipeLayout = nullptr; + m_dsLayout = nullptr; + for (FieldBuffer *fb : {&m_velA, &m_velB, &m_pres0, &m_pres1, + &m_div, &m_dyeA, &m_dyeB}) + { + fb->buf = nullptr; + fb->mem = nullptr; + } + m_swapchain = nullptr; + m_queue = nullptr; + m_device = nullptr; + m_surface = nullptr; + m_debugMessenger = nullptr; + m_instance = nullptr; + + glfwDestroyWindow(m_window); + glfwTerminate(); + m_window = nullptr; + } + + // ======================================================================= + // Instance + // ======================================================================= + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "SPH Fluid Simulation", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion13}; + + std::vector layers; + if (kEnableValidation) + layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto layerProps = m_ctx.enumerateInstanceLayerProperties(); + for (auto const *req : layers) + { + bool found = std::ranges::any_of(layerProps, [req](auto const &lp) { + return strcmp(lp.layerName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required layer not available: " + std::string(req)); + } + + auto exts = getRequiredInstanceExtensions(); + auto extProps = m_ctx.enumerateInstanceExtensionProperties(); + for (auto const *req : exts) + { + bool found = std::ranges::any_of(extProps, [req](auto const &ep) { + return strcmp(ep.extensionName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required extension not available: " + std::string(req)); + } + + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(exts.size()), + .ppEnabledExtensionNames = exts.data()}; + m_instance = vk::raii::Instance(m_ctx, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) + return; + vk::DebugUtilsMessageSeverityFlagsEXT sev( + vk::DebugUtilsMessageSeverityFlagBitsEXT::eVerbose | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError); + vk::DebugUtilsMessageTypeFlagsEXT type( + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation); + vk::DebugUtilsMessengerCreateInfoEXT ci{ + .messageSeverity = sev, + .messageType = type, + .pfnUserCallback = &debugCallback}; + m_debugMessenger = m_instance.createDebugUtilsMessengerEXT(ci); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*m_instance, m_window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface!"); + m_surface = vk::raii::SurfaceKHR(m_instance, raw); + } + + // ======================================================================= + // Physical device + // ======================================================================= + void pickPhysicalDevice() + { + // Prefer discrete GPU > integrated GPU > virtual GPU > anything else. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : m_instance.enumeratePhysicalDevices()) + { + auto qfps = pd.getQueueFamilyProperties(); + uint32_t qf = ~0u; + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + bool hasCompute = !!(qfps[i].queueFlags & vk::QueueFlagBits::eCompute); + bool hasPresent = pd.getSurfaceSupportKHR(i, *m_surface); + if (hasCompute && hasPresent) + { + qf = i; + break; + } + } + if (qf == ~0u) + continue; + + auto devExts = pd.enumerateDeviceExtensionProperties(); + bool hasSwapchain = std::ranges::any_of(devExts, [](auto const &e) { + return strcmp(e.extensionName, vk::KHRSwapchainExtensionName) == 0; + }); + if (!hasSwapchain) + continue; + + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; m_physDev = pd; m_queueFamily = qf; } + } + if (!*m_physDev) + throw std::runtime_error("No suitable GPU found!"); + } + + // ======================================================================= + // Logical device + // ======================================================================= + void createLogicalDevice() + { + vk::StructureChain< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features> + featureChain = { + {}, + {.scalarBlockLayout = true, .timelineSemaphore = true}, + {.synchronization2 = true, .dynamicRendering = true}}; + + float prio = 1.0f; + vk::DeviceQueueCreateInfo qci{ + .queueFamilyIndex = m_queueFamily, + .queueCount = 1, + .pQueuePriorities = &prio}; + vk::DeviceCreateInfo dci{ + .pNext = &featureChain.get(), + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qci, + .enabledExtensionCount = static_cast(m_devExts.size()), + .ppEnabledExtensionNames = m_devExts.data()}; + m_device = vk::raii::Device(m_physDev, dci); + m_queue = vk::raii::Queue(m_device, m_queueFamily, 0); + } + + // ======================================================================= + // Command pool + // ======================================================================= + void createCommandPool() + { + vk::CommandPoolCreateInfo ci{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = m_queueFamily}; + m_cmdPool = vk::raii::CommandPool(m_device, ci); + } + + // ======================================================================= + // Swapchain + // ======================================================================= + void createSwapchain(vk::SwapchainKHR oldSwapchain = nullptr) + { + auto caps = m_physDev.getSurfaceCapabilitiesKHR(*m_surface); + m_swapExtent = chooseExtent(caps); + + auto fmts = m_physDev.getSurfaceFormatsKHR(*m_surface); + m_swapFormat = chooseFormat(fmts); + + auto modes = m_physDev.getSurfacePresentModesKHR(*m_surface); + auto presentMode = chooseMode(modes); + + uint32_t imgCount = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0u) + imgCount = std::min(imgCount, caps.maxImageCount); + + vk::SwapchainCreateInfoKHR sci{ + .surface = *m_surface, + .minImageCount = imgCount, + .imageFormat = m_swapFormat.format, + .imageColorSpace = m_swapFormat.colorSpace, + .imageExtent = m_swapExtent, + .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eTransferDst, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = presentMode, + .clipped = true, + .oldSwapchain = oldSwapchain}; + m_swapchain = vk::raii::SwapchainKHR(m_device, sci); + m_swapImages = m_swapchain.getImages(); + } + + // ======================================================================= + // Fluid field GPU buffers — all device-local, cleared to zero via + // vkCmdFillBuffer (no host staging needed for an all-zero initial state). + // ======================================================================= + void createFluidBuffers() + { + auto deviceLocal = vk::MemoryPropertyFlagBits::eDeviceLocal; + // TransferSrc + TransferDst: fields are cleared/seeded via copies and the + // dye is promoted (dyeB → dyeA) by a buffer copy each frame. + auto storageTransfer = vk::BufferUsageFlagBits::eStorageBuffer | + vk::BufferUsageFlagBits::eTransferDst | + vk::BufferUsageFlagBits::eTransferSrc; + + const vk::DeviceSize vecSz = vk::DeviceSize(kNumCells) * 2u * sizeof(float); + const vk::DeviceSize sclSz = vk::DeviceSize(kNumCells) * sizeof(float); + + createBuffer(vecSz, storageTransfer, deviceLocal, m_velA.buf, m_velA.mem); + createBuffer(vecSz, storageTransfer, deviceLocal, m_velB.buf, m_velB.mem); + createBuffer(sclSz, storageTransfer, deviceLocal, m_pres0.buf, m_pres0.mem); + createBuffer(sclSz, storageTransfer, deviceLocal, m_pres1.buf, m_pres1.mem); + createBuffer(sclSz, storageTransfer, deviceLocal, m_div.buf, m_div.mem); + createBuffer(sclSz, storageTransfer, deviceLocal, m_dyeA.buf, m_dyeA.mem); + createBuffer(sclSz, storageTransfer, deviceLocal, m_dyeB.buf, m_dyeB.mem); + + clearFields(); + seedInitialState(); + } + + // Seed a horizontal shear layer (top flows right, bottom flows left) with a + // row of alternating vortices and a band of dye along the interface. The + // shear rolls the dye into a train of swirling billows (the Kelvin–Helmholtz + // instability), so the demo shows recognisable, correctly-behaving fluid + // motion the instant it opens — before the user touches the mouse. + void seedInitialState() + { + std::vector vel(kNumCells * 2, 0.0f); + std::vector dye(kNumCells, 0.0f); + + const float midY = kGridY * 0.5f; + const float layerH = kGridY * 0.06f; // shear-layer thickness + const float shearV = 2.2f; // base horizontal flow speed + + struct Vortex { float cx, cy, strength; }; + std::vector vortices; + const int nv = 6; + const float vR = kGridY * 0.10f; + for (int i = 0; i < nv; ++i) + { + float cx = kGridX * (0.12f + 0.76f * (i + 0.5f) / nv); + vortices.push_back({cx, midY, (i & 1) ? 2.4f : -2.4f}); + } + + for (uint32_t y = 0; y < kGridY; ++y) + { + for (uint32_t x = 0; x < kGridX; ++x) + { + uint32_t idx = y * kGridX + x; + float px = x + 0.5f, py = y + 0.5f; + + // Shear layer: smooth tanh-like profile through the interface. + float s = (py - midY) / layerH; + float flow = shearV * std::tanh(s); + vel[idx * 2 + 0] = flow; + + // Fill the whole domain with dye that varies in a soft large-scale + // pattern, plus a bright band on the shear interface. Because the + // screen is never empty, the flow always has something to swirl — + // the water stays full and lively instead of draining to one side. + float base = 0.45f + 0.30f * std::sin(px * 0.055f) * std::sin(py * 0.06f); + float band = 0.55f * std::exp(-(py - midY) * (py - midY) / + (2.0f * (layerH * 1.8f) * (layerH * 1.8f))); + dye[idx] = std::clamp(base + band, 0.0f, 1.0f); + + // Vortices kick off the rollup. + for (auto &v : vortices) + { + float dx = px - v.cx, dy = py - v.cy; + float r2 = dx * dx + dy * dy; + float fall = std::exp(-r2 / (2.0f * vR * vR)); + vel[idx * 2 + 0] += -dy * v.strength * fall * 0.05f; + vel[idx * 2 + 1] += dx * v.strength * fall * 0.05f; + } + } + } + + vk::DeviceSize velSz = vk::DeviceSize(kNumCells) * 2u * sizeof(float); + vk::DeviceSize dyeSz = vk::DeviceSize(kNumCells) * sizeof(float); + + vk::raii::Buffer stage = nullptr; + vk::raii::DeviceMemory stageMem = nullptr; + createBuffer(velSz + dyeSz, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | + vk::MemoryPropertyFlagBits::eHostCoherent, + stage, stageMem); + void *ptr = stageMem.mapMemory(0, velSz + dyeSz); + std::memcpy(ptr, vel.data(), velSz); + std::memcpy(static_cast(ptr) + velSz, dye.data(), dyeSz); + stageMem.unmapMemory(); + + auto cmdBufs = vk::raii::CommandBuffers(m_device, + vk::CommandBufferAllocateInfo{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}); + auto &cb = cmdBufs[0]; + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + cb.copyBuffer(*stage, *m_velA.buf, vk::BufferCopy{.srcOffset = 0, .size = velSz}); + cb.copyBuffer(*stage, *m_dyeA.buf, vk::BufferCopy{.srcOffset = velSz, .size = dyeSz}); + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // Zero every field buffer (initial state and the R-key reset). + void clearFields() + { + auto cmdBufs = vk::raii::CommandBuffers(m_device, + vk::CommandBufferAllocateInfo{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}); + auto &cb = cmdBufs[0]; + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + for (FieldBuffer *fb : {&m_velA, &m_velB, &m_pres0, &m_pres1, + &m_div, &m_dyeA, &m_dyeB}) + cb.fillBuffer(*fb->buf, 0, VK_WHOLE_SIZE, 0u); + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // ======================================================================= + // Descriptor set layout + // binding 0 = velA (storage buffer, float2) binding 1 = velB + // binding 2 = pres0 (float) binding 3 = pres1 + // binding 4 = divergence (float) + // binding 5 = dyeA (float) binding 6 = dyeB + // binding 7 = output storage image + // ======================================================================= + void createDescriptorSetLayout() + { + std::array bindings{}; + for (uint32_t i = 0; i < 7; ++i) + bindings[i] = vk::DescriptorSetLayoutBinding{ + .binding = i, .descriptorType = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1, .stageFlags = vk::ShaderStageFlagBits::eCompute}; + bindings[7] = vk::DescriptorSetLayoutBinding{ + .binding = 7, .descriptorType = vk::DescriptorType::eStorageImage, + .descriptorCount = 1, .stageFlags = vk::ShaderStageFlagBits::eCompute}; + + vk::DescriptorSetLayoutCreateInfo ci{ + .bindingCount = static_cast(bindings.size()), + .pBindings = bindings.data()}; + m_dsLayout = vk::raii::DescriptorSetLayout(m_device, ci); + } + + // ======================================================================= + // Pipelines — one compute pipeline per solver pass (all share the layout) + // ======================================================================= + void createPipelines() + { + auto code = readFile("shaders/slang.spv"); + vk::ShaderModuleCreateInfo smci{ + .codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}; + vk::raii::ShaderModule shaderModule(m_device, smci); + + vk::PushConstantRange pcRange{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(FluidPush)}; + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_dsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcRange}; + m_pipeLayout = vk::raii::PipelineLayout(m_device, plci); + + auto makePipeline = [&](char const *entry) { + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shaderModule, + .pName = entry}; + return vk::raii::Pipeline(m_device, nullptr, + vk::ComputePipelineCreateInfo{.stage = stage, .layout = *m_pipeLayout}); + }; + + m_splatPipe = makePipeline("splatPass"); + m_advectVelPipe = makePipeline("advectVelPass"); + m_divergencePipe = makePipeline("divergencePass"); + m_jacobiPipe = makePipeline("jacobiPass"); + m_gradientPipe = makePipeline("gradientPass"); + m_advectDyePipe = makePipeline("advectDyePass"); + m_renderPipe = makePipeline("renderPass"); + } + + // ======================================================================= + // Per-frame resources + // ======================================================================= + void createPerFrameResources() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = kMaxFrames}; + auto cmdBufs = vk::raii::CommandBuffers(m_device, cbai); + + for (int i = 0; i < kMaxFrames; ++i) + { + auto &f = m_frames[i]; + createStorageImage(f); + createFrameDescriptors(f); + f.cmdBuf = std::move(cmdBufs[i]); + f.fence = vk::raii::Fence(m_device, vk::FenceCreateInfo{ + .flags = vk::FenceCreateFlagBits::eSignaled}); + } + + m_imageAvail.clear(); + for (int i = 0; i < kAcquireSemas; ++i) + m_imageAvail.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + void createStorageImage(PerFrame &f) + { + vk::ImageCreateInfo ici{ + .imageType = vk::ImageType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .extent = {m_swapExtent.width, m_swapExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eStorage | + vk::ImageUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive, + .initialLayout = vk::ImageLayout::eUndefined}; + f.storImg = vk::raii::Image(m_device, ici); + + auto memReqs = f.storImg.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + f.storMem = vk::raii::DeviceMemory(m_device, mai); + f.storImg.bindMemory(*f.storMem, 0); + + vk::ImageViewCreateInfo ivci{ + .image = *f.storImg, + .viewType = vk::ImageViewType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + f.storView = vk::raii::ImageView(m_device, ivci); + } + + void createFrameDescriptors(PerFrame &f) + { + // Pool sizes: 7 storage buffers + 1 storage image + std::array poolSizes{{ + {.type = vk::DescriptorType::eStorageBuffer, .descriptorCount = 7}, + {.type = vk::DescriptorType::eStorageImage, .descriptorCount = 1}, + }}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = static_cast(poolSizes.size()), + .pPoolSizes = poolSizes.data()}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + // The seven field buffers map to bindings 0..6 in declaration order. + FieldBuffer *fields[7] = {&m_velA, &m_velB, &m_pres0, &m_pres1, + &m_div, &m_dyeA, &m_dyeB}; + std::array bufInfos{}; + for (uint32_t i = 0; i < 7; ++i) + bufInfos[i] = vk::DescriptorBufferInfo{ + .buffer = *fields[i]->buf, .offset = 0, .range = VK_WHOLE_SIZE}; + + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + + std::array writes{}; + for (uint32_t i = 0; i < 7; ++i) + writes[i] = vk::WriteDescriptorSet{ + .dstSet = f.dsSet, .dstBinding = i, .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &bufInfos[i]}; + writes[7] = vk::WriteDescriptorSet{ + .dstSet = f.dsSet, .dstBinding = 7, .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, + .pImageInfo = &imgInfo}; + m_device.updateDescriptorSets(writes, {}); + } + + void transitionStorageImagesToGeneral() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(m_device, cbai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + + for (auto &f : m_frames) + { + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = &barrier}); + } + + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // ======================================================================= + // Draw frame + // ======================================================================= + void drawFrame() + { + auto &f = m_frames[m_frameIdx]; + + auto waitRes = m_device.waitForFences(*f.fence, vk::True, UINT64_MAX); + if (waitRes != vk::Result::eSuccess) + throw std::runtime_error("waitForFences failed"); + + auto &acqSem = m_imageAvail[m_acquireIdx]; + m_acquireIdx = (m_acquireIdx + 1) % kAcquireSemas; + + uint32_t imageIndex; + { + auto [res, idx] = m_swapchain.acquireNextImage(UINT64_MAX, *acqSem, nullptr); + if (res == vk::Result::eErrorOutOfDateKHR) + { + recreateSwapchain(); + return; + } + imageIndex = idx; + } + + m_device.resetFences(*f.fence); + recordCommands(f, imageIndex); + + auto &rdSem = m_renderDone[imageIndex]; + + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eTransfer; + vk::SubmitInfo si{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*acqSem, + .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*f.cmdBuf, + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*rdSem}; + m_queue.submit(si, *f.fence); + + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*rdSem, + .swapchainCount = 1, + .pSwapchains = &*m_swapchain, + .pImageIndices = &imageIndex}; + auto pres = m_queue.presentKHR(pi); + if (pres == vk::Result::eSuboptimalKHR || + pres == vk::Result::eErrorOutOfDateKHR || + m_resized) + { + m_resized = false; + recreateSwapchain(); + } + + m_frameIdx = (m_frameIdx + 1) % kMaxFrames; + } + + // ======================================================================= + // Command recording – SPH simulation dispatches + render + blit + // ======================================================================= + void recordCommands(PerFrame &f, uint32_t imageIndex) + { + auto &cb = f.cmdBuf; + cb.reset(); + cb.begin({}); + + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, + *m_pipeLayout, 0, {f.dsSet}, {}); + + // Global compute↔compute barrier between solver passes. Each pass reads + // the field a previous pass wrote, so this barrier (the chapter's whole + // point) makes those storage writes visible before the next dispatch. + auto barrier = [&]() { + vk::MemoryBarrier2 mb{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead | + vk::AccessFlagBits2::eShaderStorageWrite}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .memoryBarrierCount = 1, .pMemoryBarriers = &mb}); + }; + + const uint32_t gGx = (kGridX + 15u) / 16u; + const uint32_t gGy = (kGridY + 15u) / 16u; + + // R-key reset: clear every field to zero, then make it visible to compute. + if (m_resetField) + { + m_resetField = false; + for (FieldBuffer *fb : {&m_velA, &m_velB, &m_pres0, &m_pres1, + &m_div, &m_dyeA, &m_dyeB}) + cb.fillBuffer(*fb->buf, 0, VK_WHOLE_SIZE, 0u); + vk::MemoryBarrier2 mb{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead | + vk::AccessFlagBits2::eShaderStorageWrite}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .memoryBarrierCount = 1, .pMemoryBarriers = &mb}); + } + + // Mouse in grid coordinates (cursor Y is top-down, matching the image). + float winW = static_cast(m_swapExtent.width); + float winH = static_cast(m_swapExtent.height); + float gxm = static_cast(m_mouseWinX / winW) * kGridX; + float gym = static_cast(m_mouseWinY / winH) * kGridY; + if (!m_haveMouse) { m_prevGridX = gxm; m_prevGridY = gym; m_haveMouse = true; } + + FluidPush push{ + .nx = kGridX, + .ny = kGridY, + .dt = kDt, + .dissipation = kDissipation, + .velFade = kVelFade, + .mouseX = gxm, + .mouseY = gym, + .mousePx = m_prevGridX, + .mousePy = m_prevGridY, + .splatRadius = kSplatRadius, + .forceScale = m_forceScale, + .dyeAmount = kDyeAmount, + .mouseDown = m_dragging ? 1u : 0u, + .jacobiSrc = 0u, + .imgWidth = m_swapExtent.width, + .imgHeight = m_swapExtent.height}; + m_prevGridX = gxm; + m_prevGridY = gym; + + auto setPush = [&]() { + cb.pushConstants(*m_pipeLayout, + vk::ShaderStageFlagBits::eCompute, 0, push); + }; + + // The fields persist across frames (single copy, shared by both in-flight + // frames). Make the previous frame's velocity write (compute) and dye + // promotion (transfer copy) visible before this frame's first pass reads + // them. On a single queue a barrier's source scope spans earlier submits. + { + vk::MemoryBarrier2 mb{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader | + vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite | + vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead | + vk::AccessFlagBits2::eShaderStorageWrite}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .memoryBarrierCount = 1, .pMemoryBarriers = &mb}); + } + + // PASS 1 – inject velocity + dye under the mouse (writes velA, dyeA). + setPush(); + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_splatPipe); + cb.dispatch(gGx, gGy, 1); + barrier(); + + // PASS 2 – advect velocity (velA → velB). + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_advectVelPipe); + cb.dispatch(gGx, gGy, 1); + barrier(); + + // PASS 3 – divergence of velB; clears the pressure field. + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_divergencePipe); + cb.dispatch(gGx, gGy, 1); + barrier(); + + // PASS 4 – Jacobi pressure solve. Ping-pong pres0/pres1 with a barrier + // between every iteration so each reads the previous iteration's result. + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_jacobiPipe); + for (uint32_t it = 0; it < kPressureIters; ++it) + { + push.jacobiSrc = it & 1u; // 0: read pres0/write pres1, 1: swap + setPush(); + cb.dispatch(gGx, gGy, 1); + barrier(); + } + // The final pressure lives in the buffer the last iteration wrote. + // jacobiSrc s writes pres1 when s==0, pres0 when s==1. For gradientPass, + // jacobiSrc selects which buffer to READ, so point it at that final one. + uint32_t lastS = (kPressureIters - 1u) & 1u; + push.jacobiSrc = (lastS == 0u) ? 1u : 0u; // final buffer holds the pressure + setPush(); + + // PASS 5 – subtract ∇pressure, enforce walls (velB → velA). + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_gradientPipe); + cb.dispatch(gGx, gGy, 1); + barrier(); + + // PASS 6 – advect dye by the divergence-free velocity (dyeA → dyeB). + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_advectDyePipe); + cb.dispatch(gGx, gGy, 1); + + // Make dyeB visible to both the render pass (compute) and the dye copy + // (transfer) below. + { + vk::MemoryBarrier2 mb{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader | + vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead | + vk::AccessFlagBits2::eTransferRead}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .memoryBarrierCount = 1, .pMemoryBarriers = &mb}); + } + + // PASS 7 – render the dye field (dyeB, velA) into the storage image. + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_renderPipe); + uint32_t gx = (m_swapExtent.width + 15u) / 16u; + uint32_t gy = (m_swapExtent.height + 15u) / 16u; + cb.dispatch(gx, gy, 1); + + // Promote dyeB → dyeA so the freshly-advected dye is the current field + // for the next frame. (velA already holds the projected velocity.) + cb.copyBuffer(*m_dyeB.buf, *m_dyeA.buf, + vk::BufferCopy{.size = vk::DeviceSize(kNumCells) * sizeof(float)}); + + // ----------------------------------------------------------------------- + // BARRIER 3: renderPass write → blit read (storage image) + // + swapchain UNDEFINED → TRANSFER_DST + // ----------------------------------------------------------------------- + vk::ImageMemoryBarrier2 storToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferRead, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + vk::ImageMemoryBarrier2 swapToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eTransferDstOptimal, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array preBlitBarriers{storToTransfer, swapToTransfer}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(preBlitBarriers.size()), + .pImageMemoryBarriers = preBlitBarriers.data()}); + + // Blit storage image → swapchain + vk::ImageSubresourceLayers subres{vk::ImageAspectFlagBits::eColor, 0, 0, 1}; + vk::Offset3D zero{0, 0, 0}; + vk::Offset3D ext{ + static_cast(m_swapExtent.width), + static_cast(m_swapExtent.height), 1}; + vk::ImageBlit2 region{ + .srcSubresource = subres, + .srcOffsets = std::array{zero, ext}, + .dstSubresource = subres, + .dstOffsets = std::array{zero, ext}}; + vk::BlitImageInfo2 blitInfo{ + .srcImage = *f.storImg, + .srcImageLayout = vk::ImageLayout::eGeneral, + .dstImage = m_swapImages[imageIndex], + .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, + .pRegions = ®ion, + .filter = vk::Filter::eNearest}; + cb.blitImage2(blitInfo); + + // Post-blit: swapchain → PRESENT_SRC, storage image release + vk::ImageMemoryBarrier2 swapToPresent{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eBottomOfPipe, + .dstAccessMask = vk::AccessFlagBits2::eNone, + .oldLayout = vk::ImageLayout::eTransferDstOptimal, + .newLayout = vk::ImageLayout::ePresentSrcKHR, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + vk::ImageMemoryBarrier2 storRelease{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferRead, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array postBlitBarriers{swapToPresent, storRelease}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(postBlitBarriers.size()), + .pImageMemoryBarriers = postBlitBarriers.data()}); + + cb.end(); + } + + // ======================================================================= + // Swapchain recreation + // ======================================================================= + void recreateSwapchain() + { + int w = 0, h = 0; + glfwGetFramebufferSize(m_window, &w, &h); + while (w == 0 || h == 0) + { + glfwGetFramebufferSize(m_window, &w, &h); + glfwWaitEvents(); + } + + m_device.waitIdle(); + + for (auto &f : m_frames) + { + f.storView = nullptr; + f.storImg = nullptr; + f.storMem = nullptr; + f.dsPool = nullptr; + f.dsSet = nullptr; + } + + vk::SwapchainKHR oldHandle = *m_swapchain; + createSwapchain(oldHandle); + + for (auto &f : m_frames) + { + createStorageImage(f); + createFrameDescriptors(f); + } + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + // ======================================================================= + // Buffer helper + // ======================================================================= + void createBuffer(vk::DeviceSize size, + vk::BufferUsageFlags usage, + vk::MemoryPropertyFlags memProps, + vk::raii::Buffer &outBuf, + vk::raii::DeviceMemory &outMem) + { + vk::BufferCreateInfo bci{ + .size = size, + .usage = usage, + .sharingMode = vk::SharingMode::eExclusive}; + outBuf = vk::raii::Buffer(m_device, bci); + + auto memReqs = outBuf.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType(memReqs.memoryTypeBits, memProps)}; + outMem = vk::raii::DeviceMemory(m_device, mai); + outBuf.bindMemory(*outMem, 0); + } + + // ======================================================================= + // Helpers + // ======================================================================= + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, vk::MemoryPropertyFlags props) const + { + auto memProps = m_physDev.getMemoryProperties(); + for (uint32_t i = 0; i < memProps.memoryTypeCount; ++i) + { + if ((filter & (1u << i)) && + (memProps.memoryTypes[i].propertyFlags & props) == props) + return i; + } + throw std::runtime_error("no suitable memory type"); + } + + static vk::SurfaceFormatKHR chooseFormat(std::vector const &formats) + { + assert(!formats.empty()); + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Unorm && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Srgb && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + return formats[0]; + } + + static vk::PresentModeKHR chooseMode(std::vector const &modes) + { + for (auto m : modes) + if (m == vk::PresentModeKHR::eMailbox) + return m; + return vk::PresentModeKHR::eFifo; + } + + vk::Extent2D chooseExtent(vk::SurfaceCapabilitiesKHR const &caps) + { + if (caps.currentExtent.width != std::numeric_limits::max()) + return caps.currentExtent; + int w, h; + glfwGetFramebufferSize(m_window, &w, &h); + return { + std::clamp(w, caps.minImageExtent.width, caps.maxImageExtent.width), + std::clamp(h, caps.minImageExtent.height, caps.maxImageExtent.height)}; + } + + [[nodiscard]] std::vector getRequiredInstanceExtensions() const + { + uint32_t count = 0; + auto raw = glfwGetRequiredInstanceExtensions(&count); + std::vector exts(raw, raw + count); + if (kEnableValidation) + exts.push_back(vk::EXTDebugUtilsExtensionName); + return exts; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + vk::DebugUtilsMessengerCallbackDataEXT const *pData, + void *) + { + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "validation [" << to_string(type) << "]: " << pData->pMessage << '\n'; + return vk::False; + } + + static std::vector readFile(std::string const &path) + { + std::ifstream file(path, std::ios::ate | std::ios::binary); + if (!file.is_open()) + throw std::runtime_error("failed to open: " + path); + std::vector buf(file.tellg()); + file.seekg(0); + file.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +// --------------------------------------------------------------------------- +int main() +{ + try + { + SPHApp app; + app.run(); + } + catch (std::exception const &e) + { + std::cerr << e.what() << '\n'; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/03_memory_models.slang b/attachments/compute/03_memory_models.slang new file mode 100644 index 00000000..1e887d53 --- /dev/null +++ b/attachments/compute/03_memory_models.slang @@ -0,0 +1,288 @@ +// Advanced Compute Tutorial – Chapter 3: Memory Models +// Interactive 2-D incompressible fluid — Stam's "Stable Fluids" (Navier–Stokes). +// +// This is an EULERIAN (grid-based) fluid solver. Each frame the velocity field +// is advected, made divergence-free by a pressure projection, and used to carry +// a coloured "dye" that you can paint by dragging the mouse. The result looks +// and behaves like ink swirling in water. +// +// Why this lives in the "Memory Models" chapter: +// The pressure projection solves a Poisson equation with a JACOBI iteration. +// Every iteration reads its neighbours' values from the PREVIOUS iteration, so +// the C++ driver places a memory barrier between each dispatch — a textbook +// demonstration of inter-dispatch visibility. Advection, divergence, and the +// gradient subtraction are likewise separate passes separated by barriers. +// +// Entry points (one SPIR-V module): +// splatPass – inject velocity + dye under the mouse +// advectVelPass – semi-Lagrangian advection of velocity (velA → velB) +// divergencePass– divergence of velB, clears pressure +// jacobiPass – one Jacobi pressure iteration (ping-ponged) +// gradientPass – subtract ∇pressure, enforce walls (velB → velA) +// advectDyePass – semi-Lagrangian advection of dye (dyeA → dyeB) +// renderPass – colour the dye field into the output image + +// =========================================================================== +// Bindings (set 0) +// =========================================================================== +[[vk::binding(0, 0)]] RWStructuredBuffer velA; // velocity (current) +[[vk::binding(1, 0)]] RWStructuredBuffer velB; // velocity (scratch) +[[vk::binding(2, 0)]] RWStructuredBuffer pres0; // pressure ping +[[vk::binding(3, 0)]] RWStructuredBuffer pres1; // pressure pong +[[vk::binding(4, 0)]] RWStructuredBuffer diverg; // velocity divergence +[[vk::binding(5, 0)]] RWStructuredBuffer dyeA; // dye (current) +[[vk::binding(6, 0)]] RWStructuredBuffer dyeB; // dye (scratch) +[[vk::binding(7, 0)]] [[vk::image_format("rgba8")]] RWTexture2D outImage; + +// =========================================================================== +// Push constants — byte-identical to FluidPush in the C++ driver +// =========================================================================== +struct FluidPush +{ + uint nx; // grid width (cells) + uint ny; // grid height (cells) + float dt; // time step + float dissipation; // dye fade per step (≈0.997) + float velFade; // velocity damping per step (≈0.999) + float mouseX; // current mouse, in grid coordinates + float mouseY; + float mousePx; // previous mouse, in grid coordinates + float mousePy; + float splatRadius; // injection radius (cells) + float forceScale; // velocity injected per unit mouse motion + float dyeAmount; // dye injected at the mouse + uint mouseDown; // 1 while dragging + uint jacobiSrc; // 0 → read pres0/write pres1, 1 → read pres1/write pres0 + uint imgWidth; + uint imgHeight; +}; +[[vk::push_constant]] FluidPush pc; + +// =========================================================================== +// Grid helpers +// =========================================================================== +int IX(int x, int y) +{ + x = clamp(x, 0, (int)pc.nx - 1); + y = clamp(y, 0, (int)pc.ny - 1); + return y * (int)pc.nx + x; +} + +bool onBoundary(int x, int y) +{ + return x == 0 || y == 0 || x == (int)pc.nx - 1 || y == (int)pc.ny - 1; +} + +// Bilinear sample of the velocity field at grid position p (cell units). +float2 sampleVel(float2 p) +{ + p = clamp(p, float2(0.0f, 0.0f), float2((float)pc.nx - 1.0f, (float)pc.ny - 1.0f)); + int x0 = (int)floor(p.x), y0 = (int)floor(p.y); + float fx = p.x - (float)x0, fy = p.y - (float)y0; + float2 v00 = velA[IX(x0, y0)]; + float2 v10 = velA[IX(x0 + 1, y0)]; + float2 v01 = velA[IX(x0, y0 + 1)]; + float2 v11 = velA[IX(x0 + 1, y0 + 1)]; + return lerp(lerp(v00, v10, fx), lerp(v01, v11, fx), fy); +} + +// Bilinear sample of the dye field. +float sampleDye(float2 p) +{ + p = clamp(p, float2(0.0f, 0.0f), float2((float)pc.nx - 1.0f, (float)pc.ny - 1.0f)); + int x0 = (int)floor(p.x), y0 = (int)floor(p.y); + float fx = p.x - (float)x0, fy = p.y - (float)y0; + float d00 = dyeA[IX(x0, y0)]; + float d10 = dyeA[IX(x0 + 1, y0)]; + float d01 = dyeA[IX(x0, y0 + 1)]; + float d11 = dyeA[IX(x0 + 1, y0 + 1)]; + return lerp(lerp(d00, d10, fx), lerp(d01, d11, fx), fy); +} + +// Distance from cell centre to the mouse drag segment (prev → current), +// used so a fast drag paints a continuous streak rather than dotted blobs. +float distToMouseSegment(float2 p) +{ + float2 a = float2(pc.mousePx, pc.mousePy); + float2 b = float2(pc.mouseX, pc.mouseY); + float2 ab = b - a; + float len2 = max(dot(ab, ab), 1e-6f); + float t = clamp(dot(p - a, ab) / len2, 0.0f, 1.0f); + return length(p - (a + t * ab)); +} + +// =========================================================================== +// PASS 1 – splat: inject velocity + dye under the mouse +// =========================================================================== +[numthreads(16, 16, 1)] +[shader("compute")] +void splatPass(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.nx || id.y >= pc.ny) return; + int idx = (int)id.y * (int)pc.nx + (int)id.x; + + if (pc.mouseDown != 0u) + { + float2 p = float2((float)id.x + 0.5f, (float)id.y + 0.5f); + float d = distToMouseSegment(p); + float w = exp(-(d * d) / (pc.splatRadius * pc.splatRadius)); + + float2 drag = float2(pc.mouseX - pc.mousePx, pc.mouseY - pc.mousePy); + velA[idx] += drag * (pc.forceScale * w); + dyeA[idx] = min(dyeA[idx] + pc.dyeAmount * w, 1.5f); + } +} + +// =========================================================================== +// PASS 2 – advect velocity (semi-Lagrangian back-trace). velA → velB +// =========================================================================== +[numthreads(16, 16, 1)] +[shader("compute")] +void advectVelPass(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.nx || id.y >= pc.ny) return; + int idx = (int)id.y * (int)pc.nx + (int)id.x; + + float2 p = float2((float)id.x + 0.5f, (float)id.y + 0.5f); + float2 vel = velA[idx]; + float2 src = p - vel * pc.dt; // trace backwards + velB[idx] = sampleVel(src) * pc.velFade; +} + +// =========================================================================== +// PASS 3 – divergence of velB; clear the pressure field to zero. +// =========================================================================== +[numthreads(16, 16, 1)] +[shader("compute")] +void divergencePass(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.nx || id.y >= pc.ny) return; + int x = (int)id.x, y = (int)id.y; + int idx = y * (int)pc.nx + x; + + float l = velB[IX(x - 1, y)].x; + float r = velB[IX(x + 1, y)].x; + float b = velB[IX(x, y - 1)].y; + float t = velB[IX(x, y + 1)].y; + + diverg[idx] = 0.5f * ((r - l) + (t - b)); + pres0[idx] = 0.0f; + pres1[idx] = 0.0f; +} + +// =========================================================================== +// PASS 4 – one Jacobi iteration of the pressure Poisson solve. +// ∇²p = divergence → p_new = (Σ neighbours − divergence) / 4 +// Ping-ponged between pres0 and pres1 by pc.jacobiSrc; the C++ driver issues a +// memory barrier between every invocation so each reads the previous result. +// =========================================================================== +[numthreads(16, 16, 1)] +[shader("compute")] +void jacobiPass(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.nx || id.y >= pc.ny) return; + int x = (int)id.x, y = (int)id.y; + int idx = y * (int)pc.nx + x; + + float l, r, b, t, c; + if (pc.jacobiSrc == 0u) + { + l = pres0[IX(x - 1, y)]; r = pres0[IX(x + 1, y)]; + b = pres0[IX(x, y - 1)]; t = pres0[IX(x, y + 1)]; + } + else + { + l = pres1[IX(x - 1, y)]; r = pres1[IX(x + 1, y)]; + b = pres1[IX(x, y - 1)]; t = pres1[IX(x, y + 1)]; + } + c = (l + r + b + t - diverg[idx]) * 0.25f; + + if (pc.jacobiSrc == 0u) pres1[idx] = c; + else pres0[idx] = c; +} + +// =========================================================================== +// PASS 5 – subtract the pressure gradient to project velocity to be +// divergence-free, and enforce no-slip walls. velB → velA +// pc.jacobiSrc here names the buffer holding the FINAL pressure. +// =========================================================================== +[numthreads(16, 16, 1)] +[shader("compute")] +void gradientPass(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.nx || id.y >= pc.ny) return; + int x = (int)id.x, y = (int)id.y; + int idx = y * (int)pc.nx + x; + + float pl, pr, pb, pt; + if (pc.jacobiSrc == 0u) + { + pl = pres0[IX(x - 1, y)]; pr = pres0[IX(x + 1, y)]; + pb = pres0[IX(x, y - 1)]; pt = pres0[IX(x, y + 1)]; + } + else + { + pl = pres1[IX(x - 1, y)]; pr = pres1[IX(x + 1, y)]; + pb = pres1[IX(x, y - 1)]; pt = pres1[IX(x, y + 1)]; + } + + float2 v = velB[idx] - 0.5f * float2(pr - pl, pt - pb); + if (onBoundary(x, y)) v = float2(0.0f, 0.0f); // no-slip walls keep fluid in + velA[idx] = v; +} + +// =========================================================================== +// PASS 6 – advect dye by the (now divergence-free) velocity. dyeA → dyeB +// =========================================================================== +[numthreads(16, 16, 1)] +[shader("compute")] +void advectDyePass(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.nx || id.y >= pc.ny) return; + int idx = (int)id.y * (int)pc.nx + (int)id.x; + + float2 p = float2((float)id.x + 0.5f, (float)id.y + 0.5f); + float2 vel = velA[idx]; + float2 src = p - vel * pc.dt; + dyeB[idx] = sampleDye(src) * pc.dissipation; +} + +// =========================================================================== +// PASS 7 – render the dye field to the screen as illuminated water. +// =========================================================================== +[numthreads(16, 16, 1)] +[shader("compute")] +void renderPass(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.imgWidth || id.y >= pc.imgHeight) return; + + // Pixel → grid coordinate (bilinear). dyeB holds the freshest dye. + float gx = ((float)id.x + 0.5f) / (float)pc.imgWidth * (float)pc.nx - 0.5f; + float gy = ((float)id.y + 0.5f) / (float)pc.imgHeight * (float)pc.ny - 0.5f; + float2 g = clamp(float2(gx, gy), float2(0.0f, 0.0f), + float2((float)pc.nx - 1.0f, (float)pc.ny - 1.0f)); + + int x0 = (int)floor(g.x), y0 = (int)floor(g.y); + float fx = g.x - (float)x0, fy = g.y - (float)y0; + float d00 = dyeB[IX(x0, y0)], d10 = dyeB[IX(x0 + 1, y0)]; + float d01 = dyeB[IX(x0, y0 + 1)], d11 = dyeB[IX(x0 + 1, y0 + 1)]; + float dye = lerp(lerp(d00, d10, fx), lerp(d01, d11, fx), fy); + + float2 v00 = velA[IX(x0, y0)], v10 = velA[IX(x0 + 1, y0)]; + float2 v01 = velA[IX(x0, y0 + 1)], v11 = velA[IX(x0 + 1, y0 + 1)]; + float2 vel = lerp(lerp(v00, v10, fx), lerp(v01, v11, fx), fy); + float speed = length(vel); + + // Water look: dark teal base → bright cyan/white where dye is dense or fast. + float amt = clamp(dye, 0.0f, 1.0f); + float3 deep = float3(0.01f, 0.05f, 0.10f); // dark water + float3 body = float3(0.05f, 0.45f, 0.75f); // lit water blue + float3 bright = float3(0.75f, 0.95f, 1.00f); // foam / highlight + float3 col = lerp(deep, body, smoothstep(0.0f, 0.5f, amt)); + col = lerp(col, bright, smoothstep(0.5f, 1.0f, amt)); + + // Speed adds a subtle bright sheen so motion reads as flowing water. + col += float3(0.10f, 0.20f, 0.30f) * clamp(speed * 0.05f, 0.0f, 1.0f) * amt; + + outImage[uint2(id.x, id.y)] = float4(col, 1.0f); +} diff --git a/attachments/compute/04_subgroup_operations.cpp b/attachments/compute/04_subgroup_operations.cpp new file mode 100644 index 00000000..2c0afb98 --- /dev/null +++ b/attachments/compute/04_subgroup_operations.cpp @@ -0,0 +1,1045 @@ +// Chapter 4 – Subgroup / Wave Operations: Hair Strands on a Sphere in Wind +// +// Demonstrates Vulkan subgroup (wave) operations in an interactive windowed app: +// • WaveActiveSum – per-strand wind force aggregation within a wave +// • WavePrefixSum – strand-segment chain propagation (prefix scan) +// • WaveActiveBallot – cull strands in the wind shadow +// • Atomic slot counter – safe wave-index assignment on Intel Arc ARL +// (variable SIMD8/16/32 within a single workgroup) +// +// Two dispatches per frame: +// 1. physicsMain (256,1,1) – one thread per strand, computes tip displacement +// 2. renderMain (16,16,1) – one thread per pixel, ray-marches the scene +// +// Based on the windowed template from 02_compute_architecture.cpp. + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr int kMaxFrames = 2; +constexpr int kAcquireSemas = kMaxFrames + 1; + +constexpr uint32_t kNumStrands = 512; // hair strands around the sphere +constexpr uint32_t kPhysicsGroupSize = 256; + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// Push-constant layout – must match PushConst in the shader exactly +// --------------------------------------------------------------------------- +struct HairPush +{ + uint32_t width; + uint32_t height; + uint32_t numStrands; + float time; + float windStrength; +}; +static_assert(sizeof(HairPush) == 20, "push constant size mismatch"); + +// --------------------------------------------------------------------------- +// HairApp +// --------------------------------------------------------------------------- +class HairApp +{ + public: + void run() + { + initWindow(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + // ----------------------------------------------------------------------- + // Window state + // ----------------------------------------------------------------------- + GLFWwindow *m_window = nullptr; + bool m_resized = false; + + float m_windStrength = 1.0f; // controlled by +/- keys + + // ----------------------------------------------------------------------- + // Core Vulkan handles + // ----------------------------------------------------------------------- + vk::raii::Context m_ctx; + vk::raii::Instance m_instance = nullptr; + vk::raii::DebugUtilsMessengerEXT m_debugMessenger = nullptr; + vk::raii::SurfaceKHR m_surface = nullptr; + vk::raii::PhysicalDevice m_physDev = nullptr; + vk::raii::Device m_device = nullptr; + uint32_t m_queueFamily = ~0u; + vk::raii::Queue m_queue = nullptr; + + // ----------------------------------------------------------------------- + // Swapchain + // ----------------------------------------------------------------------- + vk::raii::SwapchainKHR m_swapchain = nullptr; + std::vector m_swapImages; + vk::SurfaceFormatKHR m_swapFormat{}; + vk::Extent2D m_swapExtent{}; + + // ----------------------------------------------------------------------- + // Strand tip displacement buffer (device-local storage) + // ----------------------------------------------------------------------- + vk::raii::Buffer m_strandBuf = nullptr; + vk::raii::DeviceMemory m_strandMem = nullptr; + + // ----------------------------------------------------------------------- + // Descriptor set layout and pipeline layout (shared by both pipelines) + // ----------------------------------------------------------------------- + vk::raii::DescriptorSetLayout m_dsLayout = nullptr; + vk::raii::PipelineLayout m_pipeLayout = nullptr; + + // Two compute pipelines – physics and render + vk::raii::Pipeline m_physPipeline = nullptr; + vk::raii::Pipeline m_renderPipeline = nullptr; + + // Command pool (declared before m_frames so it outlives per-frame bufs) + vk::raii::CommandPool m_cmdPool = nullptr; + + // ----------------------------------------------------------------------- + // Per-frame resources + // ----------------------------------------------------------------------- + struct PerFrame + { + vk::raii::Image storImg = nullptr; + vk::raii::DeviceMemory storMem = nullptr; + vk::raii::ImageView storView = nullptr; + + vk::raii::DescriptorPool dsPool = nullptr; + vk::DescriptorSet dsSet = nullptr; // raw handle, pool-owned + + vk::raii::CommandBuffer cmdBuf = nullptr; + vk::raii::Fence fence = nullptr; + }; + std::array m_frames; + + std::vector m_imageAvail; + int m_acquireIdx = 0; + std::vector m_renderDone; + + uint32_t m_frameIdx = 0; + + std::vector m_devExts = {vk::KHRSwapchainExtensionName}; + + // ======================================================================= + // Window + // ======================================================================= + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + m_window = glfwCreateWindow(kWidth, kHeight, + "Hair Strands in Wind | Subgroup/Wave ops | +/- wind ESC=quit", + nullptr, nullptr); + glfwSetWindowUserPointer(m_window, this); + glfwSetFramebufferSizeCallback(m_window, cbResize); + glfwSetKeyCallback(m_window, cbKey); + } + + static void cbResize(GLFWwindow *w, int, int) + { + static_cast(glfwGetWindowUserPointer(w))->m_resized = true; + } + + static void cbKey(GLFWwindow *w, int key, int /*sc*/, int action, int /*mods*/) + { + if (action != GLFW_PRESS) return; + auto *app = static_cast(glfwGetWindowUserPointer(w)); + switch (key) + { + case GLFW_KEY_EQUAL: app->m_windStrength = std::min(app->m_windStrength + 0.2f, 3.0f); break; + case GLFW_KEY_MINUS: app->m_windStrength = std::max(app->m_windStrength - 0.2f, 0.0f); break; + case GLFW_KEY_R: app->m_windStrength = 1.0f; break; + case GLFW_KEY_ESCAPE: glfwSetWindowShouldClose(w, GLFW_TRUE); break; + default: break; + } + } + + // ======================================================================= + // Vulkan init + // ======================================================================= + void initVulkan() + { + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createCommandPool(); + createStrandBuffer(); + createSwapchain(); + createDescriptorSetLayout(); + createPipelines(); + createPerFrameResources(); + } + + // ======================================================================= + // Main loop + // ======================================================================= + void mainLoop() + { + auto startTime = std::chrono::steady_clock::now(); + while (!glfwWindowShouldClose(m_window)) + { + glfwPollEvents(); + auto now = std::chrono::steady_clock::now(); + float elapsed = std::chrono::duration(now - startTime).count(); + drawFrame(elapsed); + } + m_device.waitIdle(); + } + + void cleanup() + { + m_renderDone.clear(); + m_imageAvail.clear(); + for (auto &f : m_frames) + { + f.fence = nullptr; + f.cmdBuf = nullptr; + f.dsPool = nullptr; + f.storView = nullptr; + f.storMem = nullptr; + f.storImg = nullptr; + } + m_cmdPool = nullptr; + m_renderPipeline = nullptr; + m_physPipeline = nullptr; + m_pipeLayout = nullptr; + m_dsLayout = nullptr; + m_strandBuf = nullptr; + m_strandMem = nullptr; + m_swapchain = nullptr; + m_queue = nullptr; + m_device = nullptr; + m_surface = nullptr; + m_debugMessenger = nullptr; + m_instance = nullptr; + + glfwDestroyWindow(m_window); + glfwTerminate(); + m_window = nullptr; + } + + // ======================================================================= + // Instance + // ======================================================================= + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "Hair Strands in Wind", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion13}; + + std::vector layers; + if (kEnableValidation) + layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto layerProps = m_ctx.enumerateInstanceLayerProperties(); + for (auto const *req : layers) + { + bool found = std::ranges::any_of(layerProps, [req](auto const &lp) { + return strcmp(lp.layerName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required layer not available: " + std::string(req)); + } + + auto exts = getRequiredInstanceExtensions(); + auto extProps = m_ctx.enumerateInstanceExtensionProperties(); + for (auto const *req : exts) + { + bool found = std::ranges::any_of(extProps, [req](auto const &ep) { + return strcmp(ep.extensionName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required extension not available: " + std::string(req)); + } + + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(exts.size()), + .ppEnabledExtensionNames = exts.data()}; + m_instance = vk::raii::Instance(m_ctx, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) return; + vk::DebugUtilsMessageSeverityFlagsEXT sev( + vk::DebugUtilsMessageSeverityFlagBitsEXT::eVerbose | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError); + vk::DebugUtilsMessageTypeFlagsEXT type( + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation); + vk::DebugUtilsMessengerCreateInfoEXT ci{ + .messageSeverity = sev, + .messageType = type, + .pfnUserCallback = &debugCallback}; + m_debugMessenger = m_instance.createDebugUtilsMessengerEXT(ci); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*m_instance, m_window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface!"); + m_surface = vk::raii::SurfaceKHR(m_instance, raw); + } + + // ======================================================================= + // Physical device + // ======================================================================= + void pickPhysicalDevice() + { + // Prefer discrete GPU > integrated GPU > virtual GPU > anything else. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : m_instance.enumeratePhysicalDevices()) + { + auto qfps = pd.getQueueFamilyProperties(); + uint32_t qf = ~0u; + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + bool hasCompute = !!(qfps[i].queueFlags & vk::QueueFlagBits::eCompute); + bool hasPresent = pd.getSurfaceSupportKHR(i, *m_surface); + if (hasCompute && hasPresent) { qf = i; break; } + } + if (qf == ~0u) continue; + + auto devExts = pd.enumerateDeviceExtensionProperties(); + bool hasSwapchain = std::ranges::any_of(devExts, [](auto const &e) { + return strcmp(e.extensionName, vk::KHRSwapchainExtensionName) == 0; + }); + if (!hasSwapchain) continue; + + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; m_physDev = pd; m_queueFamily = qf; } + } + if (!*m_physDev) + throw std::runtime_error("No suitable GPU found!"); + + // Print subgroup properties — the educational content for this chapter + vk::PhysicalDeviceSubgroupProperties sgProps{}; + vk::PhysicalDeviceProperties2 props2{.pNext = &sgProps}; + m_physDev.getProperties2(&props2); + + std::cout << "=== Subgroup / Wave Operations ===\n"; + std::cout << " Device : " << props2.properties.deviceName.data() << '\n'; + std::cout << " Subgroup size : " << sgProps.subgroupSize << '\n'; + std::cout << " Supported stages : " << vk::to_string(sgProps.supportedStages) << '\n'; + std::cout << " Supported ops : " << vk::to_string(sgProps.supportedOperations) << '\n'; + std::cout << " (Intel Arc ARL may use SIMD8/16/32 variable subgroup sizes)\n"; + std::cout << " (Shader uses atomic slot counter pattern for safe wave indexing)\n"; + std::cout << "==================================\n"; + } + + // ======================================================================= + // Logical device + // ======================================================================= + void createLogicalDevice() + { + vk::StructureChain< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features> + featureChain = { + {}, + {.scalarBlockLayout = true, .timelineSemaphore = true}, + {.synchronization2 = true, .dynamicRendering = true}}; + + float prio = 1.0f; + vk::DeviceQueueCreateInfo qci{ + .queueFamilyIndex = m_queueFamily, + .queueCount = 1, + .pQueuePriorities = &prio}; + vk::DeviceCreateInfo dci{ + .pNext = &featureChain.get(), + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qci, + .enabledExtensionCount = static_cast(m_devExts.size()), + .ppEnabledExtensionNames = m_devExts.data()}; + m_device = vk::raii::Device(m_physDev, dci); + m_queue = vk::raii::Queue(m_device, m_queueFamily, 0); + } + + // ======================================================================= + // Command pool + // ======================================================================= + void createCommandPool() + { + vk::CommandPoolCreateInfo ci{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = m_queueFamily}; + m_cmdPool = vk::raii::CommandPool(m_device, ci); + } + + // ======================================================================= + // Strand tip displacement buffer + // One float per strand; physics dispatch writes here, render dispatch reads. + // ======================================================================= + void createStrandBuffer() + { + vk::DeviceSize sz = kNumStrands * sizeof(float); + vk::BufferCreateInfo bci{ + .size = sz, + .usage = vk::BufferUsageFlagBits::eStorageBuffer, + .sharingMode = vk::SharingMode::eExclusive}; + m_strandBuf = vk::raii::Buffer(m_device, bci); + + auto memReqs = m_strandBuf.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + m_strandMem = vk::raii::DeviceMemory(m_device, mai); + m_strandBuf.bindMemory(*m_strandMem, 0); + } + + // ======================================================================= + // Swapchain + // ======================================================================= + void createSwapchain(vk::SwapchainKHR oldSwapchain = nullptr) + { + auto caps = m_physDev.getSurfaceCapabilitiesKHR(*m_surface); + m_swapExtent = chooseExtent(caps); + auto fmts = m_physDev.getSurfaceFormatsKHR(*m_surface); + m_swapFormat = chooseFormat(fmts); + auto modes = m_physDev.getSurfacePresentModesKHR(*m_surface); + auto presentMode = chooseMode(modes); + + uint32_t imgCount = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0u) + imgCount = std::min(imgCount, caps.maxImageCount); + + vk::SwapchainCreateInfoKHR sci{ + .surface = *m_surface, + .minImageCount = imgCount, + .imageFormat = m_swapFormat.format, + .imageColorSpace = m_swapFormat.colorSpace, + .imageExtent = m_swapExtent, + .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eTransferDst, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = presentMode, + .clipped = true, + .oldSwapchain = oldSwapchain}; + m_swapchain = vk::raii::SwapchainKHR(m_device, sci); + m_swapImages = m_swapchain.getImages(); + } + + // ======================================================================= + // Descriptor set layout + // binding 0 = storage image (render output) + // binding 1 = storage buffer (strand tip displacements) + // ======================================================================= + void createDescriptorSetLayout() + { + std::array bindings{{ + { + .binding = 0, + .descriptorType = vk::DescriptorType::eStorageImage, + .descriptorCount = 1, + .stageFlags = vk::ShaderStageFlagBits::eCompute}, + { + .binding = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1, + .stageFlags = vk::ShaderStageFlagBits::eCompute} + }}; + vk::DescriptorSetLayoutCreateInfo ci{ + .bindingCount = static_cast(bindings.size()), + .pBindings = bindings.data()}; + m_dsLayout = vk::raii::DescriptorSetLayout(m_device, ci); + } + + // ======================================================================= + // Compute pipelines (physics + render) + // ======================================================================= + void createPipelines() + { + auto code = readFile("shaders/slang.spv"); + vk::ShaderModuleCreateInfo smci{ + .codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}; + vk::raii::ShaderModule shaderModule(m_device, smci); + + vk::PushConstantRange pcRange{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(HairPush)}; + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_dsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcRange}; + m_pipeLayout = vk::raii::PipelineLayout(m_device, plci); + + auto makePipeline = [&](const char *entry) { + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shaderModule, + .pName = entry}; + vk::ComputePipelineCreateInfo pci{.stage = stage, .layout = *m_pipeLayout}; + return vk::raii::Pipeline(m_device, nullptr, pci); + }; + + m_physPipeline = makePipeline("physicsMain"); + m_renderPipeline = makePipeline("renderMain"); + } + + // ======================================================================= + // Per-frame resources + // ======================================================================= + void createPerFrameResources() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = kMaxFrames}; + auto cmdBufs = vk::raii::CommandBuffers(m_device, cbai); + + for (int i = 0; i < kMaxFrames; ++i) + { + auto &f = m_frames[i]; + createStorageImage(f); + + // Descriptor pool: 1 storage image + 1 storage buffer + std::array poolSizes{{ + {.type = vk::DescriptorType::eStorageImage, .descriptorCount = 1}, + {.type = vk::DescriptorType::eStorageBuffer, .descriptorCount = 1} + }}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = static_cast(poolSizes.size()), + .pPoolSizes = poolSizes.data()}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + // Descriptor set + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + // Bind storage image (binding 0) and strand buffer (binding 1) + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + vk::DescriptorBufferInfo bufInfo{ + .buffer = *m_strandBuf, + .offset = 0, + .range = kNumStrands * sizeof(float)}; + std::array writes{{ + { + .dstSet = f.dsSet, + .dstBinding = 0, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, + .pImageInfo = &imgInfo}, + { + .dstSet = f.dsSet, + .dstBinding = 1, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &bufInfo} + }}; + m_device.updateDescriptorSets(writes, {}); + + f.cmdBuf = std::move(cmdBufs[i]); + f.fence = vk::raii::Fence(m_device, vk::FenceCreateInfo{ + .flags = vk::FenceCreateFlagBits::eSignaled}); + } + + // Acquire semaphores: rotating pool of kAcquireSemas + m_imageAvail.clear(); + for (int i = 0; i < kAcquireSemas; ++i) + m_imageAvail.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + // renderDone semaphores: indexed by swapchain image index + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + void createStorageImage(PerFrame &f) + { + vk::ImageCreateInfo ici{ + .imageType = vk::ImageType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .extent = {m_swapExtent.width, m_swapExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eStorage | + vk::ImageUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive, + .initialLayout = vk::ImageLayout::eUndefined}; + f.storImg = vk::raii::Image(m_device, ici); + + auto memReqs = f.storImg.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + f.storMem = vk::raii::DeviceMemory(m_device, mai); + f.storImg.bindMemory(*f.storMem, 0); + + vk::ImageViewCreateInfo ivci{ + .image = *f.storImg, + .viewType = vk::ImageViewType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + f.storView = vk::raii::ImageView(m_device, ivci); + } + + void transitionStorageImagesToGeneral() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(m_device, cbai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + + for (auto &f : m_frames) + { + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = &barrier}); + } + + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // ======================================================================= + // Draw frame + // ======================================================================= + void drawFrame(float elapsed) + { + auto &f = m_frames[m_frameIdx]; + + auto waitRes = m_device.waitForFences(*f.fence, vk::True, UINT64_MAX); + if (waitRes != vk::Result::eSuccess) + throw std::runtime_error("waitForFences failed"); + + auto &acqSem = m_imageAvail[m_acquireIdx]; + m_acquireIdx = (m_acquireIdx + 1) % kAcquireSemas; + + uint32_t imageIndex; + { + auto [res, idx] = m_swapchain.acquireNextImage(UINT64_MAX, *acqSem, nullptr); + if (res == vk::Result::eErrorOutOfDateKHR) + { + recreateSwapchain(); + return; + } + imageIndex = idx; + } + + m_device.resetFences(*f.fence); + recordCommands(f, imageIndex, elapsed); + + auto &rdSem = m_renderDone[imageIndex]; + + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eTransfer; + vk::SubmitInfo si{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*acqSem, + .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*f.cmdBuf, + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*rdSem}; + m_queue.submit(si, *f.fence); + + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*rdSem, + .swapchainCount = 1, + .pSwapchains = &*m_swapchain, + .pImageIndices = &imageIndex}; + auto pres = m_queue.presentKHR(pi); + if (pres == vk::Result::eSuboptimalKHR || + pres == vk::Result::eErrorOutOfDateKHR || + m_resized) + { + m_resized = false; + recreateSwapchain(); + } + + m_frameIdx = (m_frameIdx + 1) % kMaxFrames; + } + + void recordCommands(PerFrame &f, uint32_t imageIndex, float elapsed) + { + auto &cb = f.cmdBuf; + cb.reset(); + cb.begin({}); + + HairPush push{ + .width = m_swapExtent.width, + .height = m_swapExtent.height, + .numStrands = kNumStrands, + .time = elapsed, + .windStrength = m_windStrength}; + + // ---- Dispatch 1: physics (WaveActiveSum + WavePrefixSum) ---- + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_physPipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, *m_pipeLayout, + 0, {f.dsSet}, {}); + cb.pushConstants(*m_pipeLayout, + vk::ShaderStageFlagBits::eCompute, 0, push); + + // Dispatch enough groups to cover all strands (up to 256 per group) + uint32_t physGroups = (kNumStrands + kPhysicsGroupSize - 1u) / kPhysicsGroupSize; + cb.dispatch(physGroups, 1, 1); + + // Barrier: physics writes strandTip → render reads strandTip + vk::MemoryBarrier2 bufBarrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .memoryBarrierCount = 1, + .pMemoryBarriers = &bufBarrier}); + + // ---- Dispatch 2: render (WaveActiveBallot for culling) ---- + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_renderPipeline); + // descriptor set + push constants already bound; re-bind for completeness + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, *m_pipeLayout, + 0, {f.dsSet}, {}); + cb.pushConstants(*m_pipeLayout, + vk::ShaderStageFlagBits::eCompute, 0, push); + + uint32_t gx = (m_swapExtent.width + 15u) / 16u; + uint32_t gy = (m_swapExtent.height + 15u) / 16u; + cb.dispatch(gx, gy, 1); + + // ---- Barriers: storImg compute→transfer, swapchain →TRANSFER_DST ---- + vk::ImageMemoryBarrier2 storToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferRead, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + vk::ImageMemoryBarrier2 swapToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eTransferDstOptimal, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array preBlitBarriers{storToTransfer, swapToTransfer}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(preBlitBarriers.size()), + .pImageMemoryBarriers = preBlitBarriers.data()}); + + // ---- Blit storage image → swapchain ---- + vk::ImageSubresourceLayers subres{vk::ImageAspectFlagBits::eColor, 0, 0, 1}; + vk::Offset3D zero{0, 0, 0}; + vk::Offset3D ext{ + static_cast(m_swapExtent.width), + static_cast(m_swapExtent.height), 1}; + vk::ImageBlit2 region{ + .srcSubresource = subres, + .srcOffsets = std::array{zero, ext}, + .dstSubresource = subres, + .dstOffsets = std::array{zero, ext}}; + vk::BlitImageInfo2 blitInfo{ + .srcImage = *f.storImg, + .srcImageLayout = vk::ImageLayout::eGeneral, + .dstImage = m_swapImages[imageIndex], + .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, + .pRegions = ®ion, + .filter = vk::Filter::eNearest}; + cb.blitImage2(blitInfo); + + // ---- Post-blit barriers ---- + vk::ImageMemoryBarrier2 swapToPresent{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eBottomOfPipe, + .dstAccessMask = vk::AccessFlagBits2::eNone, + .oldLayout = vk::ImageLayout::eTransferDstOptimal, + .newLayout = vk::ImageLayout::ePresentSrcKHR, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + vk::ImageMemoryBarrier2 storRelease{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferRead, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array postBlitBarriers{swapToPresent, storRelease}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(postBlitBarriers.size()), + .pImageMemoryBarriers = postBlitBarriers.data()}); + + cb.end(); + } + + // ======================================================================= + // Swapchain recreation + // ======================================================================= + void recreateSwapchain() + { + int w = 0, h = 0; + glfwGetFramebufferSize(m_window, &w, &h); + while (w == 0 || h == 0) + { + glfwGetFramebufferSize(m_window, &w, &h); + glfwWaitEvents(); + } + m_device.waitIdle(); + + for (auto &f : m_frames) + { + f.storView = nullptr; + f.storImg = nullptr; + f.storMem = nullptr; + f.dsPool = nullptr; + f.dsSet = nullptr; + } + + vk::SwapchainKHR oldHandle = *m_swapchain; + createSwapchain(oldHandle); + + for (auto &f : m_frames) + createStorageImage(f); + + for (auto &f : m_frames) + { + std::array poolSizes{{ + {.type = vk::DescriptorType::eStorageImage, .descriptorCount = 1}, + {.type = vk::DescriptorType::eStorageBuffer, .descriptorCount = 1} + }}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = static_cast(poolSizes.size()), + .pPoolSizes = poolSizes.data()}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + vk::DescriptorBufferInfo bufInfo{ + .buffer = *m_strandBuf, + .offset = 0, + .range = kNumStrands * sizeof(float)}; + std::array writes{{ + { + .dstSet = f.dsSet, + .dstBinding = 0, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, + .pImageInfo = &imgInfo}, + { + .dstSet = f.dsSet, + .dstBinding = 1, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &bufInfo} + }}; + m_device.updateDescriptorSets(writes, {}); + } + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + // ======================================================================= + // Helpers + // ======================================================================= + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, vk::MemoryPropertyFlags props) const + { + auto memProps = m_physDev.getMemoryProperties(); + for (uint32_t i = 0; i < memProps.memoryTypeCount; ++i) + { + if ((filter & (1u << i)) && + (memProps.memoryTypes[i].propertyFlags & props) == props) + return i; + } + throw std::runtime_error("no suitable memory type"); + } + + static vk::SurfaceFormatKHR chooseFormat(std::vector const &formats) + { + assert(!formats.empty()); + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Unorm && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Srgb && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + return formats[0]; + } + + static vk::PresentModeKHR chooseMode(std::vector const &modes) + { + for (auto m : modes) + if (m == vk::PresentModeKHR::eMailbox) + return m; + return vk::PresentModeKHR::eFifo; + } + + vk::Extent2D chooseExtent(vk::SurfaceCapabilitiesKHR const &caps) + { + if (caps.currentExtent.width != std::numeric_limits::max()) + return caps.currentExtent; + int w, h; + glfwGetFramebufferSize(m_window, &w, &h); + return { + std::clamp(w, caps.minImageExtent.width, caps.maxImageExtent.width), + std::clamp(h, caps.minImageExtent.height, caps.maxImageExtent.height)}; + } + + [[nodiscard]] std::vector getRequiredInstanceExtensions() const + { + uint32_t count = 0; + auto raw = glfwGetRequiredInstanceExtensions(&count); + std::vector exts(raw, raw + count); + if (kEnableValidation) + exts.push_back(vk::EXTDebugUtilsExtensionName); + return exts; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + vk::DebugUtilsMessengerCallbackDataEXT const *pData, + void *) + { + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "validation [" << to_string(type) << "]: " << pData->pMessage << '\n'; + return vk::False; + } + + static std::vector readFile(std::string const &path) + { + std::ifstream file(path, std::ios::ate | std::ios::binary); + if (!file.is_open()) + throw std::runtime_error("failed to open shader: " + path); + std::vector buf(file.tellg()); + file.seekg(0); + file.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +// --------------------------------------------------------------------------- +int main() +{ + try + { + HairApp app; + app.run(); + } + catch (std::exception const &e) + { + std::cerr << e.what() << '\n'; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/04_subgroup_operations.slang b/attachments/compute/04_subgroup_operations.slang new file mode 100644 index 00000000..af954248 --- /dev/null +++ b/attachments/compute/04_subgroup_operations.slang @@ -0,0 +1,319 @@ +// Chapter 4 – Subgroup/Wave Operations: Hair Strands on a Sphere in Wind +// +// Two compute entry points: +// physicsMain – one thread per strand; uses WaveActiveSum + WavePrefixSum +// (with the atomic slot counter pattern for Intel Arc ARL +// variable-subgroup-size safety) to compute strand tip +// displacement from animated wind forces. +// renderMain – one thread per pixel; 2D view of strands radiating from +// a centre circle, blown by wind. Uses WaveActiveBallot +// to cull strands facing away from wind. +// +// Design note (Intel Arc ARL / variable subgroup sizes): +// Intel Arc ARL (Alchemist) may use SIMD8 / SIMD16 / SIMD32 within the +// same workgroup. Therefore groupIndex / WaveGetLaneCount() gives a +// WRONG wave index. Instead we use an atomic slot counter: the first +// lane of each wave claims a slot via InterlockedAdd, then stores its +// groupIndex in waveScanFirstLanes[slot]. Thread 0 can sort/use the +// per-wave data after a GroupMemoryBarrierWithGroupSync(). + +// --------------------------------------------------------------------------- +// Bindings +// --------------------------------------------------------------------------- +// Binding 0: render output (RGBA8 storage image) +[[vk::binding(0, 0)]] [[vk::image_format("rgba8")]] RWTexture2D outImage; + +// Binding 1: strand tip displacement array (one float per strand, physics output) +[[vk::binding(1, 0)]] RWStructuredBuffer strandTip; + +// --------------------------------------------------------------------------- +// Push constants +// --------------------------------------------------------------------------- +struct PushConst +{ + uint width; // image width (pixels) + uint height; // image height (pixels) + uint numStrands; // total number of strands (must be <= 1024) + float time; // animation time in seconds + float windStrength; // base wind strength +}; +[[vk::push_constant]] PushConst pc; + +// --------------------------------------------------------------------------- +// Module-scope groupshared (groupshared is illegal inside function bodies) +// --------------------------------------------------------------------------- +static const uint kMaxWaves = 64u; // 256 threads / min-wave-size-4 + +// physicsMain groupshared +groupshared uint physSlotCtr; +groupshared uint physFirstLane[kMaxWaves]; +groupshared float physWaveForce[kMaxWaves]; // per-wave WaveActiveSum result +groupshared float physWaveOffset[kMaxWaves]; // exclusive scan of wave totals +groupshared float physGroupWindSum; // total wind force in this group + +// --------------------------------------------------------------------------- +// Entry 1: physicsMain +// +// Workgroup = (256, 1, 1). Each thread corresponds to one strand index. +// We demonstrate: +// WaveActiveSum – aggregate per-strand wind forces across the wave +// WavePrefixSum – chain propagation: each strand's "inherited" force +// from all strands before it in the wave +// Atomic slot counter – safe wave-index assignment on variable-SIMD GPUs +// --------------------------------------------------------------------------- +[numthreads(256, 1, 1)] +[shader("compute")] +void physicsMain(uint3 gid : SV_DispatchThreadID, + uint gIdx : SV_GroupIndex) +{ + // Initialise slot counter once per group + if (gIdx == 0u) + { + physSlotCtr = 0u; + physGroupWindSum = 0.0f; + } + GroupMemoryBarrierWithGroupSync(); + + uint strandIdx = gid.x; + bool active = (strandIdx < pc.numStrands); + + // ---- Per-strand wind force ---- + // Strands are distributed around a circle; the wind force is a sinusoidal + // function of the strand's angular position and time. + float angle = (float(strandIdx) / float(pc.numStrands)) * 6.28318f; + float windForce = active + ? (0.5f + 0.5f * sin(angle * 2.0f + pc.time * 1.5f)) * pc.windStrength + : 0.0f; + + // ---- WaveActiveSum: aggregate wind forces within this wave ---- + float waveForceSum = WaveActiveSum(windForce); + + // ---- WavePrefixSum: how much force precedes this strand in its wave ---- + float wavePrefix = WavePrefixSum(windForce); + + // ---- Atomic slot counter pattern (Intel Arc ARL safe) ---- + uint mySlot = 0u; + if (WaveIsFirstLane()) + { + InterlockedAdd(physSlotCtr, 1u, mySlot); + physFirstLane[mySlot] = gIdx; // first-lane groupIndex for sorting + physWaveForce[mySlot] = waveForceSum; + } + GroupMemoryBarrierWithGroupSync(); + + // ---- Thread 0: insertion-sort slots by firstLane, then exclusive scan ---- + if (gIdx == 0u) + { + uint n = physSlotCtr; + + // Insertion sort: sort (physFirstLane[], physWaveForce[]) by firstLane + for (uint i = 1u; i < n; ++i) + { + uint fl = physFirstLane[i]; + float wf = physWaveForce[i]; + int j = int(i) - 1; + while (j >= 0 && physFirstLane[j] > fl) + { + physFirstLane[j + 1] = physFirstLane[j]; + physWaveForce[j + 1] = physWaveForce[j]; + j--; + } + physFirstLane[j + 1] = fl; + physWaveForce[j + 1] = wf; + } + + // Exclusive scan of wave force totals → physWaveOffset + physWaveOffset[0] = 0.0f; + for (uint w = 1u; w < n; ++w) + physWaveOffset[w] = physWaveOffset[w - 1u] + physWaveForce[w - 1u]; + + // Group total + float total = physWaveOffset[n - 1u] + physWaveForce[n - 1u]; + physGroupWindSum = total; + } + GroupMemoryBarrierWithGroupSync(); + + // ---- Each first lane finds its sorted position ---- + uint mySortedIdx = 0u; + if (WaveIsFirstLane()) + { + uint fl = gIdx; + uint n = physSlotCtr; + for (uint k = 0u; k < n; ++k) + { + if (physFirstLane[k] == fl) { mySortedIdx = k; break; } + } + } + uint waveIdx = WaveReadLaneFirst(mySortedIdx); + + // ---- Final displacement = wave prefix offset + intra-wave prefix ---- + float displacement = physWaveOffset[waveIdx] + wavePrefix; + + // Normalise by group total so displacement stays in [0, 1] range + float norm = physGroupWindSum > 0.0f ? displacement / physGroupWindSum : 0.0f; + + // Write result: strand tip displacement in [-1, 1] with a sinusoidal modulation + if (active) + strandTip[strandIdx] = norm * pc.windStrength + * (0.8f + 0.2f * sin(pc.time * 3.0f + angle)); +} + +// --------------------------------------------------------------------------- +// Entry 2: renderMain +// +// Workgroup = (16, 16, 1). One thread per pixel. +// Renders a 2D "top view": +// - A circle (sphere cross-section) in the centre with gradient shading +// - Thick hair strands radiating outward from the circle, blown by wind +// drawn via SDF distance-to-segment for visible thickness +// Demonstrates WaveActiveBallot to cull strands that are in the "wind shadow" +// (dot(strandDir, windDir) < 0 → the strand is facing away from the wind). +// --------------------------------------------------------------------------- + +// SDF helper: distance from point p to line segment [a, b] +float distToSegment(float2 p, float2 a, float2 b) +{ + float2 ab = b - a; + float2 ap = p - a; + float t = clamp(dot(ap, ab) / (dot(ab, ab) + 1e-8f), 0.0f, 1.0f); + return length(ap - t * ab); +} + +[numthreads(16, 16, 1)] +[shader("compute")] +void renderMain(uint3 gid : SV_DispatchThreadID) +{ + uint px = gid.x; + uint py = gid.y; + if (px >= pc.width || py >= pc.height) + return; + + // Normalised pixel coordinate in [-1, 1] with correct aspect ratio + float aspect = float(pc.width) / float(pc.height); + float2 uv = float2( + (float(px) / float(pc.width) - 0.5f) * 2.0f * aspect, + (float(py) / float(pc.height) - 0.5f) * 2.0f); + + // Pixel size in UV space — used to convert pixel thickness to UV units + float pixelSizeUV = 2.0f / float(pc.height); + + // Background: deep dark blue-grey with a subtle vignette + float vignette = 1.0f - 0.4f * saturate((uv.x * uv.x + uv.y * uv.y) * 0.5f); + float4 color = float4(0.04f * vignette, 0.05f * vignette, 0.10f * vignette, 1.0f); + + // Sphere circle with solid grey/silver shading + specular highlight + const float sphereR = 0.30f; + float distSphere = length(uv); + if (distSphere < sphereR) + { + float nx = uv.x / sphereR; + float ny = uv.y / sphereR; + float nz = sqrt(max(0.0f, 1.0f - nx*nx - ny*ny)); + float3 lightDir = normalize(float3(0.6f + 0.2f*sin(pc.time), 0.4f, 0.8f)); + float3 norm = float3(nx, ny, nz); + float diffuse = max(0.15f, dot(norm, lightDir)); + // Specular: Blinn-Phong + float3 viewDir = float3(0.0f, 0.0f, 1.0f); + float3 halfVec = normalize(lightDir + viewDir); + float spec = pow(max(0.0f, dot(norm, halfVec)), 40.0f); + float3 baseCol = float3(0.55f, 0.58f, 0.62f); // silver-grey + color = float4(baseCol * diffuse + float3(0.6f, 0.6f, 0.7f) * spec, 1.0f); + } + // Thin edge ring to make sphere boundary crisp + else if (distSphere < sphereR + pixelSizeUV * 1.5f) + { + color = float4(0.5f, 0.52f, 0.55f, 1.0f); + } + + // Wind direction (animated sinusoidal — slowly rotating) + float windAngle = pc.time * 0.4f; + float2 windDir = normalize(float2(cos(windAngle), sin(windAngle * 0.6f))); + + // Strand thickness: 2.5 pixels expressed in UV units + const float strandThickness = pixelSizeUV * 2.5f; + const int numSeg = 8; + + // Track closest strand hit for smooth alpha blending + float minDist = 1e10f; + float3 hairColor = float3(0.0f, 0.0f, 0.0f); + + for (uint s = 0u; s < pc.numStrands; ++s) + { + float angle = (float(s) / float(pc.numStrands)) * 6.28318f; + float2 rootDir = float2(cos(angle), sin(angle)); + + // ---- WaveActiveBallot: cull strands facing away from wind ---- + // A strand "in wind shadow" points significantly away from the wind. + // We use a softer threshold (-0.3) so more strands are visible, but + // strands strongly facing away from wind are still culled for realism. + bool inWindShadow = (dot(rootDir, windDir) < -0.3f); + uint4 ballot = WaveActiveBallot(inWindShadow); + // ballot is used for potential subgroup-wide culling decisions; + // here we act per-strand on the individual boolean. + if (inWindShadow) + continue; + + // Root sits just outside the sphere + float2 root = rootDir * (sphereR + pixelSizeUV); + + // Wind deflection: strands on windward side bend more dramatically + float windDot = dot(rootDir, windDir); // in [-1, 1], positive = windward + float tipDisp = strandTip[s]; // [0,1]-ish from physics + // Exaggerate the bend: windward strands (windDot > 0) get strong bend, + // cross-wind strands get moderate bend, and we use tipDisp as modulation. + float bendAmount = (0.4f + windDot * 0.5f) * (0.8f + 0.4f * tipDisp) + * pc.windStrength; + + // Build strand tip via quadratic Bezier-like approach: + // strand grows in rootDir, then curves toward wind + // Total strand length = 2.2 × sphereR (well beyond the sphere) + float strandLen = sphereR * 2.2f; + + float2 prevPt = root; + for (int seg = 0; seg < numSeg; ++seg) + { + float t = float(seg + 1) / float(numSeg); + float blend = t * t; // quadratic bend — tip bends more + // Direction evolves: starts radially outward, curves toward wind at tip + float2 segDir = normalize(rootDir + windDir * (bendAmount * blend)); + // Slight wave motion along the strand + float wave = 0.04f * sin(pc.time * 2.5f + angle + t * 6.28318f); + float2 perpDir = float2(-segDir.y, segDir.x); + float2 nextPt = root + segDir * (strandLen * t) + + perpDir * (wave * strandLen); + + // SDF: distance from this pixel to segment [prevPt, nextPt] + float dist = distToSegment(uv, prevPt, nextPt); + + if (dist < minDist) + { + minDist = dist; + // Warm golden-amber at root, cooler at tip + float hairT = t; + float r = lerp(0.95f, 0.70f, hairT); + float g = lerp(0.75f, 0.50f, hairT); + float b = lerp(0.15f, 0.05f, hairT); + hairColor = float3(r, g, b); + } + + prevPt = nextPt; + } + } + + // Blend hair onto background/sphere using smooth anti-aliased coverage + if (minDist < strandThickness && distSphere >= sphereR) + { + // Smooth falloff for anti-aliasing: full opaque in centre, fade at edge + float alpha = 1.0f - smoothstep(strandThickness * 0.5f, strandThickness, minDist); + color.rgb = lerp(color.rgb, hairColor, alpha); + } + + // Grid overlay: subtle dot pattern visualising subgroup lanes on Intel Arc ARL + // One faint dot per wave-first-lane position (8×8 pixel grid) + if (px % 8u == 0u && py % 8u == 0u) + { + color.rgb += float3(0.03f, 0.04f, 0.05f); + } + + outImage[int2(int(px), int(py))] = color; +} diff --git a/attachments/compute/05_opencl_on_vulkan.cl b/attachments/compute/05_opencl_on_vulkan.cl new file mode 100644 index 00000000..c3545d9d --- /dev/null +++ b/attachments/compute/05_opencl_on_vulkan.cl @@ -0,0 +1,197 @@ +// =========================================================================== +// 05_opencl_on_vulkan.cl — Instanced forest renderer in OpenCL C +// =========================================================================== +// This is the ONE kernel that drives the entire Chapter 05 demo. The exact +// same source file is fed onto Vulkan two different ways: +// +// 1. clspv (AOT): the build system compiles this file to `forest.spv`, which +// the host loads into a *raw Vulkan compute pipeline*. +// 2. clvk (layer): the host hands this source to the OpenCL 3.0 runtime at +// run time; clvk uses clspv internally to produce SPIR-V and +// dispatches it on the Vulkan driver. +// +// Both paths must produce a byte-for-byte identical image — that is the whole +// point of the demo, and it is what "OpenCL on Vulkan" guarantees. +// +// The scene is a forest grown by *instancing a single tree*: one tree SDF is +// repeated across an infinite grid using domain repetition (round(p/cell)), and +// a per-cell hash gives each instance its own height, canopy size, colour, and +// the occasional clearing. This is the SDF analogue of instanced rendering — one +// primitive, drawn thousands of times with per-instance variation. +// +// Portability rules followed here (see "Kernel Portability" in the chapter): +// * Only __global *buffer* arguments are used (no scalar/POD kernel args), so +// clspv's descriptor mapping is fully deterministic: +// arg 0 (params) -> set 0, binding 0 (storage buffer) +// arg 1 (output) -> set 0, binding 1 (storage buffer) +// * The output is a __global uint* (one packed RGBA8 word per pixel), so only +// 32-bit storage access is needed — no 8-bit storage Vulkan feature. +// * reqd_work_group_size pins the local size at compile time, and the host +// rounds the global size up to a multiple of it, so the NDRange stays +// uniform (required by the clspv default path). +// * Every invocation computes one pixel independently — no atomics, no shared +// state, no cross-invocation races — so the result is bit-deterministic and +// the two compile paths agree exactly. +// =========================================================================== + +// Layout MUST match the C++ `Params` struct on the host. All members are 4-byte +// scalars, so std430 / scalar layout places them at offsets 0,4,8,12,16,20. +typedef struct { + int width; + int height; + float camX; // camera position (for fly-through navigation) + float camY; + float camZ; + float camYaw; // camera heading (radians) + float camPitch; // camera pitch (radians) + float fog; // exponential fog density +} Params; + +#define CELL 2.2f // grid spacing of the instanced forest +// Fixed raymarch step budget. NOTE: this is a compile-time constant on purpose — +// clspv miscompiles a raymarch loop whose bound is loaded from a storage buffer +// (the structured-control-flow pass cannot bound it), so do NOT make this dynamic. +#define MAX_STEPS 128 + +static float frac1(float x) { return x - floor(x); } +static float hash21(float2 id) { return frac1(sin(id.x * 127.1f + id.y * 311.7f) * 43758.5453f); } + +// --- Signed distance primitives ------------------------------------------- +static float sdEllipsoid(float3 p, float3 r) { + float k0 = length(p / r); + float k1 = length(p / (r * r)); + return k0 * (k0 - 1.0f) / k1; // good approximation; under-relax marching +} +static float sdCappedCylinder(float3 p, float h, float r) { // axis = y + float2 d = (float2)(length(p.xz) - r, fabs(p.y) - h); + return fmin(fmax(d.x, d.y), 0.0f) + length(fmax(d, (float2)(0.0f))); +} + +// --- Scene: ground plane + one tree instanced across a grid ---------------- +// Returns (distance, materialId): 0 = ground, 1 = trunk, 2 = canopy. +static float2 map(float3 p) { + float2 res = (float2)(p.y, 0.0f); // ground plane y = 0 + + float2 id = round(p.xz / CELL); // which grid cell + float2 lp = p.xz - CELL * id; // position within the cell + float h = hash21(id); // per-instance random + + if (h > 0.12f) { // ~12% of cells are clearings + float3 q = (float3)(lp.x, p.y, lp.y); + float th = 0.9f + h * 0.9f; // trunk height varies per instance + + float trunk = sdCappedCylinder(q - (float3)(0.0f, th * 0.5f, 0.0f), + th * 0.5f, 0.06f + 0.03f * h); + if (trunk < res.x) res = (float2)(trunk, 1.0f); + + float cr = 0.55f + 0.35f * frac1(h * 7.3f); // canopy radius (< half a cell) + float3 cc = q - (float3)(0.0f, th + cr * 0.55f, 0.0f); + float canopy = sdEllipsoid(cc, (float3)(cr, cr * 1.3f, cr)); + if (canopy < res.x) res = (float2)(canopy, 2.0f); + } + return res; +} + +static float3 calcNormal(float3 p) { + float2 e = (float2)(0.0015f, 0.0f); + float d = map(p).x; + float3 n = (float3)(map(p + e.xyy).x - d, + map(p + e.yxy).x - d, + map(p + e.yyx).x - d); + return normalize(n); +} + +static float softShadow(float3 ro, float3 rd) { + float res = 1.0f, t = 0.05f; + for (int i = 0; i < 24 && t < 12.0f; ++i) { + float h = map(ro + rd * t).x; + if (h < 0.001f) return 0.0f; + res = fmin(res, 10.0f * h / t); + t += clamp(h, 0.02f, 0.35f); + } + return clamp(res, 0.0f, 1.0f); +} + +static float3 skyColor(float3 rd) { + float t = clamp(rd.y * 0.5f + 0.5f, 0.0f, 1.0f); + return mix((float3)(0.70f, 0.78f, 0.86f), (float3)(0.22f, 0.40f, 0.72f), t); +} + +__attribute__((reqd_work_group_size(16, 16, 1))) +__kernel void render(__global const Params* P, __global uint* outRGBA) { + const int x = get_global_id(0); + const int y = get_global_id(1); + if (x >= P->width || y >= P->height) + return; // guard the padding lanes from the rounded-up global size + + // Pixel -> normalised camera-plane coordinates (y up). + float2 uv = (2.0f * (float2)((float)x, (float)y) - (float2)((float)P->width, (float)P->height)) + / (float)P->height; + uv.y = -uv.y; + + // Free-fly camera: the host feeds position + yaw/pitch so the scene can be + // navigated interactively. The forest grid is infinite, so you can fly forever. + const float cy = cos(P->camYaw), sy = sin(P->camYaw); + const float cp = cos(P->camPitch), sp = sin(P->camPitch); + float3 ro = (float3)(P->camX, P->camY, P->camZ); + float3 fwd = (float3)(sy * cp, sp, cy * cp); + float3 rgt = normalize(cross(fwd, (float3)(0.0f, 1.0f, 0.0f))); + float3 up = cross(rgt, fwd); + float3 rd = normalize(uv.x * rgt + uv.y * up + 1.35f * fwd); // ~73° wide FOV + + const float3 sun = normalize((float3)(0.55f, 0.70f, 0.40f)); + + // March the primary ray. + float t = 0.0f, mat = -1.0f; + for (int i = 0; i < MAX_STEPS; ++i) { + float3 p = ro + rd * t; + float2 h = map(p); + if (h.x < 0.0015f * t) { mat = h.y; break; } + if (t > 60.0f) break; + t += h.x * 0.8f; // under-relax for the approximate ellipsoid SDF + } + + float3 col; + if (mat < 0.0f) { + col = skyColor(rd); // missed everything + } else { + float3 p = ro + rd * t; + float3 n = calcNormal(p); + + // Per-material albedo. Canopy hue varies per instance (some autumn trees). + float3 albedo; + if (mat < 0.5f) { // ground + float g = hash21(round(p.xz / CELL)); + albedo = mix((float3)(0.12f, 0.17f, 0.08f), (float3)(0.20f, 0.24f, 0.10f), g); + } else if (mat < 1.5f) { // trunk + albedo = (float3)(0.23f, 0.15f, 0.09f); + } else { // canopy + float a = frac1(hash21(round(p.xz / CELL)) * 3.7f); + albedo = mix((float3)(0.13f, 0.38f, 0.12f), (float3)(0.62f, 0.36f, 0.07f), + smoothstep(0.6f, 0.95f, a)); + } + + float sh = softShadow(p + n * 0.02f, sun); + float diff = max(dot(n, sun), 0.0f) * sh; + float sky = 0.5f + 0.5f * n.y; // hemispheric ambient + float bnc = max(dot(n, (float3)(-sun.x, 0.0f, -sun.z)), 0.0f) * 0.3f; // ground bounce fill + col = albedo * ((float3)(1.35f, 1.25f, 1.0f) * diff + + (float3)(0.38f, 0.44f, 0.55f) * sky + + (float3)(0.30f, 0.28f, 0.20f) * bnc); + + // Distance fog blends toward the sky colour. + float f = 1.0f - exp(-P->fog * t); + col = mix(col, skyColor(rd), f); + } + + // Tone-map + gamma. + col = col / (col + (float3)(1.0f)); + col = pow(col, (float3)(1.0f / 2.2f)); + + const uint r = (uint)(clamp(col.x, 0.0f, 1.0f) * 255.0f); + const uint g = (uint)(clamp(col.y, 0.0f, 1.0f) * 255.0f); + const uint b = (uint)(clamp(col.z, 0.0f, 1.0f) * 255.0f); + + // Packed little-endian RGBA: R in the low byte, A=0xFF in the high byte. + outRGBA[y * P->width + x] = r | (g << 8) | (b << 16) | (0xFFu << 24); +} diff --git a/attachments/compute/05_opencl_on_vulkan.cpp b/attachments/compute/05_opencl_on_vulkan.cpp new file mode 100644 index 00000000..2271b53f --- /dev/null +++ b/attachments/compute/05_opencl_on_vulkan.cpp @@ -0,0 +1,776 @@ +// =========================================================================== +// 05_opencl_on_vulkan.cpp — Vulkan rendering powered by an OpenCL kernel +// =========================================================================== +// A normal *Vulkan* application — window, swapchain, present loop, free-fly +// camera — that draws its scene with an OpenCL C kernel instead of a hand-written +// Vulkan shader. This is the real value of the OpenCL-on-Vulkan toolchain: a +// Vulkan engine can reuse the huge body of existing OpenCL kernels. +// +// The scene is a raymarched, instanced forest (05_opencl_on_vulkan.cl): one tree +// SDF repeated across an infinite grid, with per-instance variation. You fly +// through it in real time. +// +// Two compute backends can drive the kernel, selected at startup: +// +// * clspv AOT (preferred, zero-copy): the OpenCL C kernel is compiled by clspv +// to forest.spv at build time and runs as the Vulkan engine's OWN compute +// shader, writing straight into the buffer that is presented. The OpenCL +// kernel becomes "just another shader" in the Vulkan pipeline — no copies, +// no interop layer. This is Vulkan taking advantage of OpenCL, directly. +// +// * clvk runtime (alternative): the SAME .cl is compiled at run time by clvk +// (OpenCL 3.0 layered on Vulkan). clvk does not expose cl_khr_external_memory, +// so its result is bridged into the Vulkan buffer with a per-frame readback. +// It demonstrates the runtime-layering tool at the cost of one copy/frame. +// +// We deliberately refuse to use an unrelated OpenCL platform (e.g. a vendor's +// native CUDA/ROCm driver): the point is the Vulkan layer, so only a platform +// whose name contains "clvk" is accepted for the runtime path. +// +// Controls: W/A/S/D move, E/Q up/down, mouse-drag look, Shift boost, R reset, +// ESC quit. Force a backend with: --backend=aot | --backend=clvk +// +// See the chapter docs under en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/. +// =========================================================================== + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +#ifdef HAVE_OPENCL +# define CL_TARGET_OPENCL_VERSION 300 +# include +#endif + +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr int kLocal = 16; // must match reqd_work_group_size in .cl +constexpr int kAcquireSemas = 3; + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// Byte-compatible with the `Params` struct in the .cl file (8 packed 4-byte scalars). +// (The raymarch step count is a compile-time constant in the kernel — see MAX_STEPS.) +struct Params { + int32_t width; + int32_t height; + float camX, camY, camZ; + float camYaw, camPitch; + float fog; +}; + +static uint32_t roundUp(uint32_t v, uint32_t m) { return (v + m - 1) / m * m; } + +// =========================================================================== +// clvk runtime backend: compile the .cl at run time, dispatch, and bridge the +// result into a host pointer (clvk has no external-memory sharing). +// =========================================================================== +#ifdef HAVE_OPENCL +struct ClvkBackend { + cl_platform_id platform = nullptr; + cl_device_id device = nullptr; + cl_context context = nullptr; + cl_command_queue queue = nullptr; + cl_program program = nullptr; + cl_kernel kernel = nullptr; + cl_mem paramsMem = nullptr; + cl_mem outMem = nullptr; + + // Find the clvk platform (and ONLY clvk — never a CUDA/ROCm fallback). + static bool probe(ClvkBackend& out) { + cl_uint nplat = 0; + if (clGetPlatformIDs(0, nullptr, &nplat) != CL_SUCCESS || nplat == 0) return false; + std::vector plats(nplat); + clGetPlatformIDs(nplat, plats.data(), nullptr); + for (auto p : plats) { + char name[256] = {}; + clGetPlatformInfo(p, CL_PLATFORM_NAME, sizeof(name), name, nullptr); + std::string lower(name); + for (auto& c : lower) c = char(std::tolower((unsigned char)c)); + std::cout << "[clvk] OpenCL platform: " << name << '\n'; + if (lower.find("clvk") == std::string::npos) continue; + cl_device_id dev = nullptr; + if (clGetDeviceIDs(p, CL_DEVICE_TYPE_DEFAULT, 1, &dev, nullptr) != CL_SUCCESS) continue; + char dname[256] = {}; + clGetDeviceInfo(dev, CL_DEVICE_NAME, sizeof(dname), dname, nullptr); + std::cout << "[clvk] clvk device: " << dname << '\n'; + out.platform = p; out.device = dev; + return true; + } + std::cout << "[clvk] no clvk platform found.\n"; + return false; + } + + bool init(const std::string& source, size_t outBytes) { + cl_int err = CL_SUCCESS; + context = clCreateContext(nullptr, 1, &device, nullptr, nullptr, &err); + if (err) { std::cerr << "[clvk] clCreateContext " << err << '\n'; return false; } + queue = clCreateCommandQueueWithProperties(context, device, nullptr, &err); + if (err) { std::cerr << "[clvk] queue " << err << '\n'; return false; } + + const char* src = source.c_str(); + const size_t len = source.size(); + program = clCreateProgramWithSource(context, 1, &src, &len, &err); + if (err) { std::cerr << "[clvk] program " << err << '\n'; return false; } + if (clBuildProgram(program, 1, &device, "", nullptr, nullptr) != CL_SUCCESS) { + size_t ls = 0; + clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, 0, nullptr, &ls); + std::string log(ls, '\0'); + clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, ls, log.data(), nullptr); + std::cerr << "[clvk] build failed:\n" << log << '\n'; + return false; + } + kernel = clCreateKernel(program, "render", &err); + if (err) { std::cerr << "[clvk] clCreateKernel " << err << '\n'; return false; } + + paramsMem = clCreateBuffer(context, CL_MEM_READ_ONLY, sizeof(Params), nullptr, &err); + if (err) { std::cerr << "[clvk] params buffer " << err << '\n'; return false; } + outMem = clCreateBuffer(context, CL_MEM_WRITE_ONLY, outBytes, nullptr, &err); + if (err) { std::cerr << "[clvk] output buffer " << err << '\n'; return false; } + clSetKernelArg(kernel, 0, sizeof(cl_mem), ¶msMem); + clSetKernelArg(kernel, 1, sizeof(cl_mem), &outMem); + return true; + } + + // Render one frame and copy the result into the Vulkan-visible host pointer. + void compute(const Params& p, void* hostDst, size_t bytes) { + clEnqueueWriteBuffer(queue, paramsMem, CL_FALSE, 0, sizeof(Params), &p, 0, nullptr, nullptr); + const size_t global[2] = {roundUp(p.width, kLocal), roundUp(p.height, kLocal)}; + const size_t local[2] = {kLocal, kLocal}; + clEnqueueNDRangeKernel(queue, kernel, 2, nullptr, global, local, 0, nullptr, nullptr); + clEnqueueReadBuffer(queue, outMem, CL_TRUE, 0, bytes, hostDst, 0, nullptr, nullptr); + } + + void destroy() { + if (outMem) clReleaseMemObject(outMem); + if (paramsMem) clReleaseMemObject(paramsMem); + if (kernel) clReleaseKernel(kernel); + if (program) clReleaseProgram(program); + if (queue) clReleaseCommandQueue(queue); + if (context) clReleaseContext(context); + *this = ClvkBackend{}; + } +}; +#endif // HAVE_OPENCL + +// =========================================================================== +class ForestApp { +public: + explicit ForestApp(const std::string& forced) : m_forced(forced) {} + + void run() { + initWindow(); + selectBackend(); + createInstance(); + setupDebug(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createCommandPool(); + createSwapchain(); + createIntermediateImage(); + createSharedBuffer(); + initComputeBackend(); + createSyncAndCmd(); + mainLoop(); + cleanup(); + } + +private: + enum class Backend { ClspvAot, ClvkRuntime }; + Backend m_backend = Backend::ClspvAot; + std::string m_forced; // "aot", "clvk", or "" + + // ---- window / camera ---- + GLFWwindow* m_window = nullptr; + bool m_dragging = false; + double m_lastMx = 0, m_lastMy = 0; + float m_camX = 0.0f, m_camY = 3.1f, m_camZ = 0.0f; + float m_yaw = 0.45f, m_pitch = -0.40f; + double m_lastTime = 0.0; + + // ---- Vulkan core ---- + vk::raii::Context m_ctx; + vk::raii::Instance m_instance = nullptr; + vk::raii::DebugUtilsMessengerEXT m_debug = nullptr; + vk::raii::SurfaceKHR m_surface = nullptr; + vk::raii::PhysicalDevice m_phys = nullptr; + vk::raii::Device m_device = nullptr; + uint32_t m_queueFamily = ~0u; + vk::raii::Queue m_queue = nullptr; + vk::raii::CommandPool m_cmdPool = nullptr; + + // ---- swapchain ---- + vk::raii::SwapchainKHR m_swapchain = nullptr; + std::vector m_swapImages; + vk::SurfaceFormatKHR m_swapFormat{}; + vk::Extent2D m_extent{}; + + // ---- intermediate RGBA image (blit converts RGBA->BGRA) ---- + vk::raii::Image m_interImg = nullptr; + vk::raii::DeviceMemory m_interMem = nullptr; + + // ---- shared output buffer (compute writes it; present copies it) ---- + // Host-visible so the AOT compute shader writes it on the GPU and the clvk + // backend can drop its readback straight into the same memory. + vk::raii::Buffer m_sharedBuf = nullptr; + vk::raii::DeviceMemory m_sharedMem = nullptr; + void* m_sharedMapped = nullptr; + vk::DeviceSize m_sharedBytes = 0; + + // ---- AOT compute pipeline ---- + vk::raii::DescriptorSetLayout m_dsLayout = nullptr; + vk::raii::PipelineLayout m_pipeLayout = nullptr; + vk::raii::Pipeline m_pipeline = nullptr; + vk::raii::DescriptorPool m_dsPool = nullptr; + vk::DescriptorSet m_dsSet = nullptr; + vk::raii::Buffer m_paramsBuf = nullptr; + vk::raii::DeviceMemory m_paramsMem = nullptr; + void* m_paramsMapped = nullptr; + +#ifdef HAVE_OPENCL + ClvkBackend m_clvk; + bool m_clvkLive = false; +#endif + + // ---- per-frame sync ---- + std::vector m_imageAvail; + std::vector m_renderDone; + int m_acquireIdx = 0; + vk::raii::CommandBuffer m_cmd = nullptr; + vk::raii::Fence m_fence = nullptr; + + std::string m_kernelSource; + + // ======================================================================= + void initWindow() { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_FALSE); + m_window = glfwCreateWindow(kWidth, kHeight, + "OpenCL-on-Vulkan Forest | WASD+EQ move drag=look Shift=boost R=reset ESC=quit", + nullptr, nullptr); + glfwSetWindowUserPointer(m_window, this); + glfwSetMouseButtonCallback(m_window, cbMouseButton); + glfwSetCursorPosCallback(m_window, cbCursorPos); + glfwSetKeyCallback(m_window, cbKey); + } + + static void cbMouseButton(GLFWwindow* w, int button, int action, int) { + auto* a = static_cast(glfwGetWindowUserPointer(w)); + if (button == GLFW_MOUSE_BUTTON_LEFT) { + a->m_dragging = (action == GLFW_PRESS); + glfwGetCursorPos(w, &a->m_lastMx, &a->m_lastMy); + } + } + static void cbCursorPos(GLFWwindow* w, double mx, double my) { + auto* a = static_cast(glfwGetWindowUserPointer(w)); + if (a->m_dragging) { + a->m_yaw -= float(mx - a->m_lastMx) * 0.0040f; + a->m_pitch -= float(my - a->m_lastMy) * 0.0040f; + a->m_pitch = std::clamp(a->m_pitch, -1.5f, 1.5f); + } + a->m_lastMx = mx; a->m_lastMy = my; + } + static void cbKey(GLFWwindow* w, int key, int, int action, int) { + if (action != GLFW_PRESS) return; + auto* a = static_cast(glfwGetWindowUserPointer(w)); + if (key == GLFW_KEY_ESCAPE) glfwSetWindowShouldClose(w, GLFW_TRUE); + if (key == GLFW_KEY_R) { a->m_camX = 0; a->m_camY = 3.1f; a->m_camZ = 0; + a->m_yaw = 0.45f; a->m_pitch = -0.40f; } + } + + void updateCamera() { + double now = glfwGetTime(); + float dt = std::min(float(now - m_lastTime), 0.05f); + m_lastTime = now; + float speed = 6.0f * dt; + if (glfwGetKey(m_window, GLFW_KEY_LEFT_SHIFT) == GLFW_PRESS) speed *= 4.0f; + const float fx = std::sin(m_yaw), fz = std::cos(m_yaw); + const float rx = std::cos(m_yaw), rz = -std::sin(m_yaw); + auto mv = [&](float dx, float dy, float dz){ m_camX += dx; m_camY += dy; m_camZ += dz; }; + if (glfwGetKey(m_window, GLFW_KEY_W) == GLFW_PRESS) mv(fx*speed, 0, fz*speed); + if (glfwGetKey(m_window, GLFW_KEY_S) == GLFW_PRESS) mv(-fx*speed, 0, -fz*speed); + if (glfwGetKey(m_window, GLFW_KEY_D) == GLFW_PRESS) mv(rx*speed, 0, rz*speed); + if (glfwGetKey(m_window, GLFW_KEY_A) == GLFW_PRESS) mv(-rx*speed, 0, -rz*speed); + if (glfwGetKey(m_window, GLFW_KEY_E) == GLFW_PRESS) mv(0, speed, 0); + if (glfwGetKey(m_window, GLFW_KEY_Q) == GLFW_PRESS) mv(0, -speed, 0); + m_camY = std::max(m_camY, 0.3f); + } + + Params currentParams() const { + return Params{ + .width = int32_t(kWidth), .height = int32_t(kHeight), + .camX = m_camX, .camY = m_camY, .camZ = m_camZ, + .camYaw = m_yaw, .camPitch = m_pitch, .fog = 0.05f}; + } + + // ======================================================================= + bool aotAvailable() const { + return bool(std::ifstream("shaders/forest.spv", std::ios::binary)); + } + + void selectBackend() { + m_kernelSource = readText("05_opencl_on_vulkan.cl"); + const bool wantClvk = (m_forced == "clvk"); + const bool wantAot = (m_forced == "aot"); + +#ifdef HAVE_OPENCL + if (!wantAot && !m_kernelSource.empty() && ClvkBackend::probe(m_clvk)) { + if (wantClvk || !aotAvailable()) { // prefer the zero-copy AOT path by default + m_backend = Backend::ClvkRuntime; + std::cout << "[backend] clvk runtime: OpenCL compiled at run time, " + "result bridged into the Vulkan buffer\n"; + return; + } + } +#endif + if (wantClvk) + throw std::runtime_error("--backend=clvk requested but no clvk platform / kernel source found."); + if (!aotAvailable()) + throw std::runtime_error( + "No compute backend: shaders/forest.spv missing AND no clvk platform.\n" + "Install clspv (preferred) or clvk, then rebuild. See install_dependencies_*."); + m_backend = Backend::ClspvAot; + std::cout << "[backend] clspv AOT: the OpenCL kernel runs as the Vulkan compute shader " + "(zero-copy)\n"; + } + + // ======================================================================= + void createInstance() { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "OpenCL-on-Vulkan Forest", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion13}; + std::vector layers; + if (kEnableValidation) layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + uint32_t gc = 0; + auto gexts = glfwGetRequiredInstanceExtensions(&gc); + std::vector exts(gexts, gexts + gc); + if (kEnableValidation) exts.push_back(vk::EXTDebugUtilsExtensionName); + m_instance = vk::raii::Instance(m_ctx, vk::InstanceCreateInfo{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = uint32_t(layers.size()), .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = uint32_t(exts.size()), .ppEnabledExtensionNames = exts.data()}); + } + + void setupDebug() { + if (!kEnableValidation) return; + m_debug = m_instance.createDebugUtilsMessengerEXT(vk::DebugUtilsMessengerCreateInfoEXT{ + .messageSeverity = vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError, + .messageType = vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance, + .pfnUserCallback = &debugCallback}); + } + + void createSurface() { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*m_instance, m_window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("glfwCreateWindowSurface failed"); + m_surface = vk::raii::SurfaceKHR(m_instance, raw); + } + + void pickPhysicalDevice() { + auto typeScore = [](vk::PhysicalDeviceType t) { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + default: return 1; + } + }; + int best = 0; + for (auto& pd : m_instance.enumeratePhysicalDevices()) { + auto qfps = pd.getQueueFamilyProperties(); + uint32_t qf = ~0u; + for (uint32_t i = 0; i < qfps.size(); ++i) + if ((qfps[i].queueFlags & vk::QueueFlagBits::eCompute) && + pd.getSurfaceSupportKHR(i, *m_surface)) { qf = i; break; } + if (qf == ~0u) continue; + auto de = pd.enumerateDeviceExtensionProperties(); + if (!std::any_of(de.begin(), de.end(), [](auto& e){ + return strcmp(e.extensionName, vk::KHRSwapchainExtensionName) == 0; })) + continue; + int s = typeScore(pd.getProperties().deviceType); + if (s > best) { best = s; m_phys = pd; m_queueFamily = qf; } + } + if (!*m_phys) throw std::runtime_error("No suitable GPU found"); + std::cout << "[vulkan] device: " << m_phys.getProperties().deviceName.data() << '\n'; + } + + void createLogicalDevice() { + std::vector exts = {vk::KHRSwapchainExtensionName}; + // variablePointers* are required by clspv-generated SPIR-V (AOT path). + vk::StructureChain chain = { + {}, + {.variablePointersStorageBuffer = true, .variablePointers = true}, + {.synchronization2 = true}}; + float prio = 1.0f; + vk::DeviceQueueCreateInfo qci{ + .queueFamilyIndex = m_queueFamily, .queueCount = 1, .pQueuePriorities = &prio}; + m_device = vk::raii::Device(m_phys, vk::DeviceCreateInfo{ + .pNext = &chain.get(), + .queueCreateInfoCount = 1, .pQueueCreateInfos = &qci, + .enabledExtensionCount = uint32_t(exts.size()), .ppEnabledExtensionNames = exts.data()}); + m_queue = vk::raii::Queue(m_device, m_queueFamily, 0); + } + + void createCommandPool() { + m_cmdPool = vk::raii::CommandPool(m_device, vk::CommandPoolCreateInfo{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = m_queueFamily}); + } + + void createSwapchain() { + auto caps = m_phys.getSurfaceCapabilitiesKHR(*m_surface); + m_extent = (caps.currentExtent.width != UINT32_MAX) + ? caps.currentExtent : vk::Extent2D{kWidth, kHeight}; + auto fmts = m_phys.getSurfaceFormatsKHR(*m_surface); + m_swapFormat = fmts[0]; + for (auto& f : fmts) + if (f.format == vk::Format::eB8G8R8A8Unorm && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) { m_swapFormat = f; break; } + auto modes = m_phys.getSurfacePresentModesKHR(*m_surface); + auto mode = vk::PresentModeKHR::eFifo; + for (auto m : modes) if (m == vk::PresentModeKHR::eMailbox) mode = m; + uint32_t imgCount = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0) imgCount = std::min(imgCount, caps.maxImageCount); + m_swapchain = vk::raii::SwapchainKHR(m_device, vk::SwapchainCreateInfoKHR{ + .surface = *m_surface, .minImageCount = imgCount, + .imageFormat = m_swapFormat.format, .imageColorSpace = m_swapFormat.colorSpace, + .imageExtent = m_extent, .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eTransferDst, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = mode, .clipped = true}); + m_swapImages = m_swapchain.getImages(); + } + + void createIntermediateImage() { + m_interImg = vk::raii::Image(m_device, vk::ImageCreateInfo{ + .imageType = vk::ImageType::e2D, .format = vk::Format::eR8G8B8A8Unorm, + .extent = {m_extent.width, m_extent.height, 1}, .mipLevels = 1, .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eTransferDst | vk::ImageUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive, .initialLayout = vk::ImageLayout::eUndefined}); + auto req = m_interImg.getMemoryRequirements(); + m_interMem = vk::raii::DeviceMemory(m_device, vk::MemoryAllocateInfo{ + .allocationSize = req.size, + .memoryTypeIndex = findMemoryType(req.memoryTypeBits, + vk::MemoryPropertyFlagBits::eDeviceLocal)}); + m_interImg.bindMemory(*m_interMem, 0); + } + + void createSharedBuffer() { + m_sharedBytes = vk::DeviceSize(m_extent.width) * m_extent.height * sizeof(uint32_t); + m_sharedBuf = vk::raii::Buffer(m_device, vk::BufferCreateInfo{ + .size = m_sharedBytes, + .usage = vk::BufferUsageFlagBits::eStorageBuffer | vk::BufferUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive}); + auto req = m_sharedBuf.getMemoryRequirements(); + m_sharedMem = vk::raii::DeviceMemory(m_device, vk::MemoryAllocateInfo{ + .allocationSize = req.size, + .memoryTypeIndex = findMemoryType(req.memoryTypeBits, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent)}); + m_sharedBuf.bindMemory(*m_sharedMem, 0); + m_sharedMapped = m_sharedMem.mapMemory(0, m_sharedBytes); + } + + void initComputeBackend() { + if (m_backend == Backend::ClspvAot) { initAot(); return; } +#ifdef HAVE_OPENCL + if (!m_clvk.init(m_kernelSource, size_t(m_sharedBytes))) { + m_clvk.destroy(); + std::cerr << "[backend] clvk init failed; falling back to clspv AOT.\n"; + if (!aotAvailable()) + throw std::runtime_error("clvk failed and no forest.spv fallback present."); + m_backend = Backend::ClspvAot; + initAot(); + return; + } + m_clvkLive = true; +#endif + } + + void initAot() { + m_paramsBuf = vk::raii::Buffer(m_device, vk::BufferCreateInfo{ + .size = sizeof(Params), .usage = vk::BufferUsageFlagBits::eStorageBuffer, + .sharingMode = vk::SharingMode::eExclusive}); + auto preq = m_paramsBuf.getMemoryRequirements(); + m_paramsMem = vk::raii::DeviceMemory(m_device, vk::MemoryAllocateInfo{ + .allocationSize = preq.size, + .memoryTypeIndex = findMemoryType(preq.memoryTypeBits, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent)}); + m_paramsBuf.bindMemory(*m_paramsMem, 0); + m_paramsMapped = m_paramsMem.mapMemory(0, sizeof(Params)); + + std::array bindings{{ + {.binding = 0, .descriptorType = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1, .stageFlags = vk::ShaderStageFlagBits::eCompute}, + {.binding = 1, .descriptorType = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1, .stageFlags = vk::ShaderStageFlagBits::eCompute}}}; + m_dsLayout = vk::raii::DescriptorSetLayout(m_device, vk::DescriptorSetLayoutCreateInfo{ + .bindingCount = 2, .pBindings = bindings.data()}); + m_pipeLayout = vk::raii::PipelineLayout(m_device, vk::PipelineLayoutCreateInfo{ + .setLayoutCount = 1, .pSetLayouts = &*m_dsLayout}); + + auto code = readBinary("shaders/forest.spv"); + vk::raii::ShaderModule sm(m_device, vk::ShaderModuleCreateInfo{ + .codeSize = code.size(), .pCode = reinterpret_cast(code.data())}); + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, .module = *sm, .pName = "render"}; + m_pipeline = vk::raii::Pipeline(m_device, nullptr, + vk::ComputePipelineCreateInfo{.stage = stage, .layout = *m_pipeLayout}); + + std::array ps{{ + {.type = vk::DescriptorType::eStorageBuffer, .descriptorCount = 2}}}; + m_dsPool = vk::raii::DescriptorPool(m_device, vk::DescriptorPoolCreateInfo{ + .flags = vk::DescriptorPoolCreateFlagBits::eFreeDescriptorSet, + .maxSets = 1, .poolSizeCount = 1, .pPoolSizes = ps.data()}); + m_dsSet = vk::raii::DescriptorSets(m_device, vk::DescriptorSetAllocateInfo{ + .descriptorPool = *m_dsPool, .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout})[0].release(); + + vk::DescriptorBufferInfo pInfo{.buffer = *m_paramsBuf, .offset = 0, .range = sizeof(Params)}; + vk::DescriptorBufferInfo oInfo{.buffer = *m_sharedBuf, .offset = 0, .range = m_sharedBytes}; + std::array w{{ + {.dstSet = m_dsSet, .dstBinding = 0, .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, .pBufferInfo = &pInfo}, + {.dstSet = m_dsSet, .dstBinding = 1, .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, .pBufferInfo = &oInfo}}}; + m_device.updateDescriptorSets(w, {}); + } + + void createSyncAndCmd() { + for (int i = 0; i < kAcquireSemas; ++i) + m_imageAvail.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + m_cmd = std::move(vk::raii::CommandBuffers(m_device, vk::CommandBufferAllocateInfo{ + .commandPool = *m_cmdPool, .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}).front()); + m_fence = vk::raii::Fence(m_device, vk::FenceCreateInfo{ + .flags = vk::FenceCreateFlagBits::eSignaled}); + } + + // ======================================================================= + void mainLoop() { + m_lastTime = glfwGetTime(); + while (!glfwWindowShouldClose(m_window)) { + glfwPollEvents(); + updateCamera(); + drawFrame(); + } + m_device.waitIdle(); + } + + void drawFrame() { + auto _ = m_device.waitForFences(*m_fence, vk::True, UINT64_MAX); + m_device.resetFences(*m_fence); + + const Params params = currentParams(); + if (m_backend == Backend::ClspvAot) + std::memcpy(m_paramsMapped, ¶ms, sizeof(Params)); +#ifdef HAVE_OPENCL + if (m_backend == Backend::ClvkRuntime) + m_clvk.compute(params, m_sharedMapped, size_t(m_sharedBytes)); // fills the shared buffer +#endif + + auto& acq = m_imageAvail[m_acquireIdx]; + m_acquireIdx = (m_acquireIdx + 1) % kAcquireSemas; + uint32_t imageIndex; + { + auto [res, idx] = m_swapchain.acquireNextImage(UINT64_MAX, *acq, nullptr); + if (res == vk::Result::eErrorOutOfDateKHR) { m_device.waitIdle(); return; } + imageIndex = idx; + } + recordCommands(imageIndex); + + auto& rd = m_renderDone[imageIndex]; + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eTransfer; + m_queue.submit(vk::SubmitInfo{ + .waitSemaphoreCount = 1, .pWaitSemaphores = &*acq, .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, .pCommandBuffers = &*m_cmd, + .signalSemaphoreCount = 1, .pSignalSemaphores = &*rd}, *m_fence); + + auto pres = m_queue.presentKHR(vk::PresentInfoKHR{ + .waitSemaphoreCount = 1, .pWaitSemaphores = &*rd, + .swapchainCount = 1, .pSwapchains = &*m_swapchain, .pImageIndices = &imageIndex}); + if (pres == vk::Result::eErrorOutOfDateKHR) m_device.waitIdle(); + } + + void recordCommands(uint32_t imageIndex) { + auto& cb = m_cmd; + cb.reset(); + cb.begin({}); + + if (m_backend == Backend::ClspvAot) { + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_pipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, *m_pipeLayout, 0, {m_dsSet}, {}); + cb.dispatch((m_extent.width + 15) / 16, (m_extent.height + 15) / 16, 1); + } + + // Make the buffer writes visible to the transfer read. AOT writes via the + // compute shader; clvk writes via the host (clEnqueueReadBuffer above). + const bool aot = (m_backend == Backend::ClspvAot); + vk::BufferMemoryBarrier2 bufBar{ + .srcStageMask = aot ? vk::PipelineStageFlagBits2::eComputeShader + : vk::PipelineStageFlagBits2::eHost, + .srcAccessMask = aot ? vk::AccessFlagBits2::eShaderWrite + : vk::AccessFlagBits2::eHostWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferRead, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .buffer = *m_sharedBuf, .offset = 0, .size = m_sharedBytes}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .bufferMemoryBarrierCount = 1, .pBufferMemoryBarriers = &bufBar, + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = imgBar(*m_interImg, + vk::ImageLayout::eUndefined, vk::ImageLayout::eTransferDstOptimal, + vk::PipelineStageFlagBits2::eNone, vk::AccessFlagBits2::eNone, + vk::PipelineStageFlagBits2::eTransfer, vk::AccessFlagBits2::eTransferWrite)}); + + vk::BufferImageCopy2 copy{ + .bufferOffset = 0, .bufferRowLength = 0, .bufferImageHeight = 0, + .imageSubresource = {vk::ImageAspectFlagBits::eColor, 0, 0, 1}, + .imageOffset = {0, 0, 0}, .imageExtent = {m_extent.width, m_extent.height, 1}}; + cb.copyBufferToImage2(vk::CopyBufferToImageInfo2{ + .srcBuffer = *m_sharedBuf, .dstImage = *m_interImg, + .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, .pRegions = ©}); + + std::array pre{ + *imgBar(*m_interImg, vk::ImageLayout::eTransferDstOptimal, vk::ImageLayout::eTransferSrcOptimal, + vk::PipelineStageFlagBits2::eTransfer, vk::AccessFlagBits2::eTransferWrite, + vk::PipelineStageFlagBits2::eTransfer, vk::AccessFlagBits2::eTransferRead), + *imgBar(m_swapImages[imageIndex], vk::ImageLayout::eUndefined, vk::ImageLayout::eTransferDstOptimal, + vk::PipelineStageFlagBits2::eNone, vk::AccessFlagBits2::eNone, + vk::PipelineStageFlagBits2::eTransfer, vk::AccessFlagBits2::eTransferWrite)}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 2, .pImageMemoryBarriers = pre.data()}); + + vk::ImageSubresourceLayers sub{vk::ImageAspectFlagBits::eColor, 0, 0, 1}; + vk::Offset3D ext{int32_t(m_extent.width), int32_t(m_extent.height), 1}; + vk::ImageBlit2 region{ + .srcSubresource = sub, .srcOffsets = std::array{vk::Offset3D{0,0,0}, ext}, + .dstSubresource = sub, .dstOffsets = std::array{vk::Offset3D{0,0,0}, ext}}; + cb.blitImage2(vk::BlitImageInfo2{ + .srcImage = *m_interImg, .srcImageLayout = vk::ImageLayout::eTransferSrcOptimal, + .dstImage = m_swapImages[imageIndex], .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, .pRegions = ®ion, .filter = vk::Filter::eNearest}); + + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = imgBar(m_swapImages[imageIndex], + vk::ImageLayout::eTransferDstOptimal, vk::ImageLayout::ePresentSrcKHR, + vk::PipelineStageFlagBits2::eTransfer, vk::AccessFlagBits2::eTransferWrite, + vk::PipelineStageFlagBits2::eBottomOfPipe, vk::AccessFlagBits2::eNone)}); + cb.end(); + } + + vk::ImageMemoryBarrier2* imgBar(vk::Image img, vk::ImageLayout o, vk::ImageLayout n, + vk::PipelineStageFlags2 ss, vk::AccessFlags2 sa, + vk::PipelineStageFlags2 ds, vk::AccessFlags2 da) { + static thread_local std::array ring; + static thread_local int idx = 0; + auto& b = ring[idx]; idx = (idx + 1) % int(ring.size()); + b = vk::ImageMemoryBarrier2{ + .srcStageMask = ss, .srcAccessMask = sa, .dstStageMask = ds, .dstAccessMask = da, + .oldLayout = o, .newLayout = n, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = img, .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + return &b; + } + + void cleanup() { +#ifdef HAVE_OPENCL + if (m_clvkLive) m_clvk.destroy(); +#endif + m_device.waitIdle(); + m_renderDone.clear(); m_imageAvail.clear(); + m_fence = nullptr; m_cmd = nullptr; + m_dsPool = nullptr; m_pipeline = nullptr; m_pipeLayout = nullptr; m_dsLayout = nullptr; + m_paramsBuf = nullptr; m_paramsMem = nullptr; + m_sharedBuf = nullptr; m_sharedMem = nullptr; + m_interImg = nullptr; m_interMem = nullptr; + m_cmdPool = nullptr; m_swapchain = nullptr; m_queue = nullptr; + m_device = nullptr; m_surface = nullptr; m_debug = nullptr; m_instance = nullptr; + glfwDestroyWindow(m_window); + glfwTerminate(); + } + + uint32_t findMemoryType(uint32_t bits, vk::MemoryPropertyFlags props) const { + auto mp = m_phys.getMemoryProperties(); + for (uint32_t i = 0; i < mp.memoryTypeCount; ++i) + if ((bits & (1u << i)) && (mp.memoryTypes[i].propertyFlags & props) == props) return i; + throw std::runtime_error("no suitable memory type"); + } + static std::string readText(const std::string& p) { + std::ifstream f(p, std::ios::binary); + if (!f) return {}; + return std::string(std::istreambuf_iterator(f), std::istreambuf_iterator()); + } + static std::vector readBinary(const std::string& p) { + std::ifstream f(p, std::ios::ate | std::ios::binary); + if (!f) throw std::runtime_error("cannot open " + p); + std::vector b(f.tellg()); + f.seekg(0); f.read(b.data(), std::streamsize(b.size())); + return b; + } + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT sev, vk::DebugUtilsMessageTypeFlagsEXT, + const vk::DebugUtilsMessengerCallbackDataEXT* d, void*) { + if (sev >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "[VK] " << d->pMessage << '\n'; + return vk::False; + } +}; + +// --------------------------------------------------------------------------- +int main(int argc, char** argv) { + std::cout << "=====================================================\n" + " Chapter 05 — Vulkan rendering powered by OpenCL/clvk\n" + "=====================================================\n"; + std::string forced; + for (int i = 1; i < argc; ++i) { + std::string a = argv[i]; + if (a.rfind("--backend=", 0) == 0) forced = a.substr(10); + } + try { + ForestApp app(forced); + app.run(); + } catch (const std::exception& e) { + std::cerr << "Fatal: " << e.what() << '\n'; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/06_advanced_data_structures.cpp b/attachments/compute/06_advanced_data_structures.cpp new file mode 100644 index 00000000..1a40f971 --- /dev/null +++ b/attachments/compute/06_advanced_data_structures.cpp @@ -0,0 +1,1439 @@ +// Chapter 6 – Advanced Data Structures: BVH Ray Tracer +// +// Demonstrates: +// • Buffer Device Address (BDA): BVH nodes and triangle data are stored in +// device-local buffers with VK_BUFFER_USAGE_SHADER_DEVICE_ADDRESS_BIT. +// The GPU receives their raw 64-bit addresses as push constants and +// traverses them entirely via pointer arithmetic — no descriptor bindings. +// • GPU Work Queue with atomic counter: each primary-ray hit spawns a shadow +// ray job into a shared atomic-indexed queue (RWStructuredBuffer + InterlockedAdd). +// A second dispatch processes the shadow queue. +// • Interactive windowed rendering of a Cornell-box scene. +// +// Scene: Cornell box (5 walls) + 2 colored boxes = ~34 triangles, tiny BVH. +// +// Controls: +// Mouse drag – orbit camera +// Scroll – zoom +// R – reset camera +// ESC – quit +// +// Build: see CMakeLists.txt — uses WINDOWED flag +// Shader: shaders/slang.spv (compiled from 06_advanced_data_structures.slang) + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +#define GLM_FORCE_RADIANS +#include +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr int kMaxFrames = 2; +constexpr int kAcquireSemas = kMaxFrames + 1; + +// Shadow queue capacity (max shadow rays per frame) +constexpr uint32_t kShadowQueueCap = 8192u; + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// CPU-side data structures (must match shader) +// --------------------------------------------------------------------------- +struct alignas(16) BVHNode +{ + float aabbMin[3]; + int32_t leftChild; // -1 if leaf + float aabbMax[3]; + int32_t rightChild; // -1 if leaf + int32_t triOffset; // first triangle index (leaf only) + int32_t triCount; // triangle count (leaf only) + int32_t _pad[2]; // keep 48-byte struct aligned to 16 +}; +static_assert(sizeof(BVHNode) == 48, "BVHNode size mismatch"); + +// Compact layout — no per-field padding — so the struct is exactly 64 bytes. +// Offsets: v0=0, v1=12, v2=24, normal=36, color=48 +struct Triangle +{ + float v0[3]; // offset 0 (12 bytes) + float v1[3]; // offset 12 (12 bytes) + float v2[3]; // offset 24 (12 bytes) + float normal[3]; // offset 36 (12 bytes) + float color[4]; // offset 48 (16 bytes) +}; +static_assert(sizeof(Triangle) == 64, "Triangle size mismatch"); + +// Push constants: must be byte-identical to the Slang struct +struct RayTracePush +{ + uint64_t bvhAddr; // device address of BVHNode array + uint64_t triAddr; // device address of Triangle array + uint64_t shadowQueueAddr; // device address of ShadowJob array + uint64_t counterAddr; // device address of atomic counter (uint) + float camPos[3]; + uint32_t frameWidth; + float camTarget[3]; + uint32_t frameHeight; + float camUp[3]; + float fovY; // vertical FoV in radians + uint32_t nodeCount; + uint32_t triCount; + uint32_t queueCapacity; + uint32_t _pad; +}; +static_assert(sizeof(RayTracePush) == 96, "RayTracePush size mismatch"); + +// Shadow pass push constants +struct ShadowPush +{ + uint64_t bvhAddr; + uint64_t triAddr; + uint64_t shadowQueueAddr; + uint64_t counterAddr; + uint64_t outputImageAddr; // unused — output image is in descriptor set + uint32_t frameWidth; + uint32_t frameHeight; + uint32_t queueCapacity; + uint32_t _pad; +}; + +// --------------------------------------------------------------------------- +// BVH builder (CPU) +// --------------------------------------------------------------------------- +// Builds a simple flat two-level BVH from a triangle soup. +// Node 0 is the root; leaves directly reference ranges of triangles. + +static void computeAABB(const std::vector& tris, + int offset, int count, + float outMin[3], float outMax[3]) +{ + outMin[0] = outMin[1] = outMin[2] = 1e30f; + outMax[0] = outMax[1] = outMax[2] = -1e30f; + for (int i = offset; i < offset + count; ++i) + { + for (int v = 0; v < 3; ++v) + { + const float* verts[3] = {tris[i].v0, tris[i].v1, tris[i].v2}; + for (int c = 0; c < 3; ++c) + { + outMin[c] = std::min(outMin[c], verts[v][c]); + outMax[c] = std::max(outMax[c], verts[v][c]); + } + } + } +} + +// Build a simple binary BVH splitting on the longest axis at the midpoint. +// Returns the number of nodes created (written into `nodes`). +static int buildBVH(std::vector& nodes, + std::vector& tris, + int offset, int count, int depth = 0) +{ + int nodeIdx = static_cast(nodes.size()); + nodes.push_back({}); + BVHNode& node = nodes.back(); + + computeAABB(tris, offset, count, node.aabbMin, node.aabbMax); + + if (count <= 4 || depth >= 8) + { + // Leaf + node.leftChild = -1; + node.rightChild = -1; + node.triOffset = offset; + node.triCount = count; + return nodeIdx; + } + + // Find longest axis + float extents[3] = { + node.aabbMax[0] - node.aabbMin[0], + node.aabbMax[1] - node.aabbMin[1], + node.aabbMax[2] - node.aabbMin[2] + }; + int axis = 0; + if (extents[1] > extents[axis]) axis = 1; + if (extents[2] > extents[axis]) axis = 2; + + float mid = (node.aabbMin[axis] + node.aabbMax[axis]) * 0.5f; + + // Partition triangles by centroid on axis + auto midIt = std::partition( + tris.begin() + offset, + tris.begin() + offset + count, + [axis, mid](const Triangle& t) { + float centroid = (t.v0[axis] + t.v1[axis] + t.v2[axis]) / 3.0f; + return centroid < mid; + }); + + int leftCount = static_cast(midIt - (tris.begin() + offset)); + int rightCount = count - leftCount; + + // Degenerate: all on one side → make leaf + if (leftCount == 0 || rightCount == 0) + { + node.leftChild = -1; + node.rightChild = -1; + node.triOffset = offset; + node.triCount = count; + return nodeIdx; + } + + // Reserve this node's slot, recurse for children + // Children must be created after this node, so indices are nodeIdx+1... etc. + node.leftChild = buildBVH(nodes, tris, offset, leftCount, depth + 1); + // Re-fetch reference since nodes may have been reallocated: + nodes[nodeIdx].rightChild = buildBVH(nodes, tris, offset + leftCount, rightCount, depth + 1); + nodes[nodeIdx].triOffset = -1; + nodes[nodeIdx].triCount = 0; + + return nodeIdx; +} + +// --------------------------------------------------------------------------- +// Scene construction — Cornell box +// --------------------------------------------------------------------------- +static void pushQuad(std::vector& tris, + glm::vec3 v0, glm::vec3 v1, glm::vec3 v2, glm::vec3 v3, + glm::vec3 color) +{ + // Two triangles per quad, compute face normal + glm::vec3 n = glm::normalize(glm::cross(v1 - v0, v2 - v0)); + // Flip if pointing wrong way (for Cornell box normals should face inward) + + auto fillTri = [&](glm::vec3 a, glm::vec3 b, glm::vec3 c) { + Triangle t{}; + t.v0[0] = a.x; t.v0[1] = a.y; t.v0[2] = a.z; + t.v1[0] = b.x; t.v1[1] = b.y; t.v1[2] = b.z; + t.v2[0] = c.x; t.v2[1] = c.y; t.v2[2] = c.z; + t.normal[0] = n.x; t.normal[1] = n.y; t.normal[2] = n.z; + t.color[0] = color.r; t.color[1] = color.g; + t.color[2] = color.b; t.color[3] = 1.0f; + tris.push_back(t); + }; + fillTri(v0, v1, v2); + fillTri(v0, v2, v3); +} + +static void buildCornellBox(std::vector& tris) +{ + // Cornell box dimensions: [-1,1] × [0,2] × [-1,1] + // Walls: floor, ceiling, back, left(red), right(green) + const glm::vec3 white = {0.73f, 0.73f, 0.73f}; + const glm::vec3 red = {0.65f, 0.05f, 0.05f}; + const glm::vec3 green = {0.12f, 0.45f, 0.15f}; + + // Floor (y=0, normal up) + pushQuad(tris, {-1,0,-1}, {1,0,-1}, {1,0,1}, {-1,0,1}, white); + // Ceiling (y=2, normal down) + pushQuad(tris, {-1,2,1}, {1,2,1}, {1,2,-1}, {-1,2,-1}, white); + // Back wall (z=-1, normal +z) + pushQuad(tris, {-1,0,-1}, {-1,2,-1}, {1,2,-1}, {1,0,-1}, white); + // Left wall (x=-1, normal +x) — red + pushQuad(tris, {-1,0,1}, {-1,2,1}, {-1,2,-1}, {-1,0,-1}, red); + // Right wall (x=1, normal -x) — green + pushQuad(tris, {1,0,-1}, {1,2,-1}, {1,2,1}, {1,0,1}, green); + + // Tall box (5 quads: top + 4 sides), centered around (-0.35, 0, -0.35) + const glm::vec3 boxColor = {0.73f, 0.73f, 0.73f}; + float bx = -0.35f, bz = -0.35f, bw = 0.3f, bh = 1.2f; + // Top + pushQuad(tris, {bx-bw,bh,bz-bw},{bx+bw,bh,bz-bw},{bx+bw,bh,bz+bw},{bx-bw,bh,bz+bw}, boxColor); + // Front (+z) + pushQuad(tris, {bx-bw,0,bz+bw},{bx+bw,0,bz+bw},{bx+bw,bh,bz+bw},{bx-bw,bh,bz+bw}, boxColor); + // Back (-z) + pushQuad(tris, {bx+bw,0,bz-bw},{bx-bw,0,bz-bw},{bx-bw,bh,bz-bw},{bx+bw,bh,bz-bw}, boxColor); + // Left (-x) + pushQuad(tris, {bx-bw,0,bz-bw},{bx-bw,0,bz+bw},{bx-bw,bh,bz+bw},{bx-bw,bh,bz-bw}, boxColor); + // Right (+x) + pushQuad(tris, {bx+bw,0,bz+bw},{bx+bw,0,bz-bw},{bx+bw,bh,bz-bw},{bx+bw,bh,bz+bw}, boxColor); + + // Area light patch on ceiling (y≈2, centred, slightly inset from the ceiling quad). + // The shader identifies it by color.a == 2.0 and returns emission directly, + // making it appear as a bright white patch — the canonical Cornell box light. + { + const glm::vec3 lightEmit = {6.0f, 6.0f, 5.5f}; // bright warm white (clamped in shader) + // y=1.96 keeps the light patch clearly separated from the ceiling quad at y=2.0 + // to avoid floating-point precision issues in the BVH AABB slab test + glm::vec3 lv0 = {-0.3f, 1.96f, 0.3f}; + glm::vec3 lv1 = { 0.3f, 1.96f, 0.3f}; + glm::vec3 lv2 = { 0.3f, 1.96f, -0.3f}; + glm::vec3 lv3 = {-0.3f, 1.96f, -0.3f}; + size_t before = tris.size(); + pushQuad(tris, lv0, lv1, lv2, lv3, lightEmit); + // Mark emission: color.a = 2.0 distinguishes this from ordinary triangles (a=1.0) + for (size_t ti = before; ti < tris.size(); ++ti) + tris[ti].color[3] = 2.0f; + } + + // Short box, centered around (0.35, 0, 0.2) + float sx = 0.35f, sz = 0.2f, sw = 0.3f, sh = 0.6f; + // Top + pushQuad(tris, {sx-sw,sh,sz-sw},{sx+sw,sh,sz-sw},{sx+sw,sh,sz+sw},{sx-sw,sh,sz+sw}, boxColor); + // Front (+z) + pushQuad(tris, {sx-sw,0,sz+sw},{sx+sw,0,sz+sw},{sx+sw,sh,sz+sw},{sx-sw,sh,sz+sw}, boxColor); + // Back (-z) + pushQuad(tris, {sx+sw,0,sz-sw},{sx-sw,0,sz-sw},{sx-sw,sh,sz-sw},{sx+sw,sh,sz-sw}, boxColor); + // Left (-x) + pushQuad(tris, {sx-sw,0,sz-sw},{sx-sw,0,sz+sw},{sx-sw,sh,sz+sw},{sx-sw,sh,sz-sw}, boxColor); + // Right (+x) + pushQuad(tris, {sx+sw,0,sz+sw},{sx+sw,0,sz-sw},{sx+sw,sh,sz-sw},{sx+sw,sh,sz+sw}, boxColor); +} + +// --------------------------------------------------------------------------- +// BVH Ray Tracer App +// --------------------------------------------------------------------------- +class BVHRayTracerApp +{ + public: + void run() + { + initWindow(); + buildScene(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + // ----------------------------------------------------------------------- + // Window + camera state + // ----------------------------------------------------------------------- + GLFWwindow *m_window = nullptr; + bool m_resized = false; + bool m_dragging = false; + double m_lastMx = 0.0, m_lastMy = 0.0; + + // Spherical camera — start from the front (+Z side) looking into the open box + float m_theta = 0.0f; // horizontal angle (radians): 0 = front (+Z axis) + float m_phi = 0.1f; // vertical angle (radians): slight downward tilt shows floor+ceiling + float m_radius = 3.0f; // distance from target (closer reveals full floor/ceiling) + glm::vec3 m_target = {0.0f, 1.0f, 0.0f}; + + // ----------------------------------------------------------------------- + // Scene data + // ----------------------------------------------------------------------- + std::vector m_triangles; + std::vector m_bvhNodes; + + // ----------------------------------------------------------------------- + // Core Vulkan handles + // ----------------------------------------------------------------------- + vk::raii::Context m_ctx; + vk::raii::Instance m_instance = nullptr; + vk::raii::DebugUtilsMessengerEXT m_debugMessenger = nullptr; + vk::raii::SurfaceKHR m_surface = nullptr; + vk::raii::PhysicalDevice m_physDev = nullptr; + vk::raii::Device m_device = nullptr; + uint32_t m_queueFamily = ~0u; + vk::raii::Queue m_queue = nullptr; + + // ----------------------------------------------------------------------- + // Swapchain + // ----------------------------------------------------------------------- + vk::raii::SwapchainKHR m_swapchain = nullptr; + std::vector m_swapImages; + vk::SurfaceFormatKHR m_swapFormat{}; + vk::Extent2D m_swapExtent{}; + + // ----------------------------------------------------------------------- + // BDA buffers (persistent across frames) + // ----------------------------------------------------------------------- + vk::raii::Buffer m_bvhBuf = nullptr; + vk::raii::DeviceMemory m_bvhMem = nullptr; + vk::raii::Buffer m_triBuf = nullptr; + vk::raii::DeviceMemory m_triMem = nullptr; + vk::raii::Buffer m_shadowBuf = nullptr; // shadow job queue + vk::raii::DeviceMemory m_shadowMem = nullptr; + vk::raii::Buffer m_counterBuf = nullptr; // atomic counter for shadow queue + vk::raii::DeviceMemory m_counterMem = nullptr; + + // Device addresses + uint64_t m_bvhAddr = 0; + uint64_t m_triAddr = 0; + uint64_t m_shadowAddr = 0; + uint64_t m_counterAddr = 0; + + // ----------------------------------------------------------------------- + // Pipelines / layouts + // ----------------------------------------------------------------------- + vk::raii::DescriptorSetLayout m_dsLayout = nullptr; + vk::raii::PipelineLayout m_primaryLayout = nullptr; + vk::raii::PipelineLayout m_shadowLayout = nullptr; + vk::raii::Pipeline m_primaryPipeline = nullptr; + vk::raii::Pipeline m_shadowPipeline = nullptr; + + vk::raii::CommandPool m_cmdPool = nullptr; + + // ----------------------------------------------------------------------- + // Per-frame resources + // ----------------------------------------------------------------------- + struct PerFrame + { + vk::raii::Image storImg = nullptr; + vk::raii::DeviceMemory storMem = nullptr; + vk::raii::ImageView storView = nullptr; + + vk::raii::DescriptorPool dsPool = nullptr; + vk::DescriptorSet dsSet = nullptr; + + vk::raii::CommandBuffer cmdBuf = nullptr; + vk::raii::Fence fence = nullptr; + }; + std::array m_frames; + + std::vector m_imageAvail; + int m_acquireIdx = 0; + std::vector m_renderDone; + uint32_t m_frameIdx = 0; + + std::vector m_devExts = {vk::KHRSwapchainExtensionName}; + + // ======================================================================= + // Window + // ======================================================================= + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + + m_window = glfwCreateWindow(kWidth, kHeight, + "BVH Ray Tracer | drag=orbit scroll=zoom R=reset ESC=quit", + nullptr, nullptr); + glfwSetWindowUserPointer(m_window, this); + glfwSetFramebufferSizeCallback(m_window, cbResize); + glfwSetScrollCallback(m_window, cbScroll); + glfwSetMouseButtonCallback(m_window, cbMouseButton); + glfwSetCursorPosCallback(m_window, cbCursorPos); + glfwSetKeyCallback(m_window, cbKey); + } + + // ----------------------------------------------------------------------- + // GLFW callbacks + // ----------------------------------------------------------------------- + static void cbResize(GLFWwindow *w, int, int) + { + static_cast(glfwGetWindowUserPointer(w))->m_resized = true; + } + + static void cbScroll(GLFWwindow *w, double, double dy) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + float factor = (dy > 0.0) ? 0.9f : (1.0f / 0.9f); + app->m_radius = std::clamp(app->m_radius * factor, 0.5f, 20.0f); + } + + static void cbMouseButton(GLFWwindow *w, int button, int action, int) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (button == GLFW_MOUSE_BUTTON_LEFT) + { + app->m_dragging = (action == GLFW_PRESS); + glfwGetCursorPos(w, &app->m_lastMx, &app->m_lastMy); + } + } + + static void cbCursorPos(GLFWwindow *w, double mx, double my) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (app->m_dragging) + { + float dx = static_cast(mx - app->m_lastMx) * 0.005f; + float dy = static_cast(my - app->m_lastMy) * 0.005f; + app->m_theta += dx; + app->m_phi = std::clamp(app->m_phi + dy, -1.5f, 1.5f); + } + app->m_lastMx = mx; + app->m_lastMy = my; + } + + static void cbKey(GLFWwindow *w, int key, int, int action, int) + { + if (action != GLFW_PRESS) + return; + auto *app = static_cast(glfwGetWindowUserPointer(w)); + switch (key) + { + case GLFW_KEY_R: + app->m_theta = 0.0f; + app->m_phi = 0.1f; + app->m_radius = 3.0f; + break; + case GLFW_KEY_ESCAPE: + glfwSetWindowShouldClose(w, GLFW_TRUE); + break; + default: break; + } + } + + // ======================================================================= + // Scene + BVH construction + // ======================================================================= + void buildScene() + { + buildCornellBox(m_triangles); + + buildBVH(m_bvhNodes, m_triangles, 0, + static_cast(m_triangles.size())); + + std::cout << "=== BVH Ray Tracer Scene ===\n"; + std::cout << " Triangles : " << m_triangles.size() << '\n'; + std::cout << " BVH nodes : " << m_bvhNodes.size() << '\n'; + std::cout << "============================\n"; + } + + // ======================================================================= + // Vulkan init + // ======================================================================= + void initVulkan() + { + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createCommandPool(); + createSwapchain(); + uploadSceneBuffers(); + createDescriptorSetLayout(); + createPipelines(); + createPerFrameResources(); + } + + // ======================================================================= + // Main loop + // ======================================================================= + void mainLoop() + { + while (!glfwWindowShouldClose(m_window)) + { + glfwPollEvents(); + drawFrame(); + } + m_device.waitIdle(); + } + + void cleanup() + { + m_renderDone.clear(); + m_imageAvail.clear(); + for (auto &f : m_frames) + { + f.fence = nullptr; + f.cmdBuf = nullptr; + f.dsPool = nullptr; + f.storView = nullptr; + f.storMem = nullptr; + f.storImg = nullptr; + } + m_cmdPool = nullptr; + m_shadowPipeline = nullptr; + m_primaryPipeline = nullptr; + m_shadowLayout = nullptr; + m_primaryLayout = nullptr; + m_dsLayout = nullptr; + m_counterBuf = nullptr; + m_counterMem = nullptr; + m_shadowBuf = nullptr; + m_shadowMem = nullptr; + m_triBuf = nullptr; + m_triMem = nullptr; + m_bvhBuf = nullptr; + m_bvhMem = nullptr; + m_swapchain = nullptr; + m_queue = nullptr; + m_device = nullptr; + m_surface = nullptr; + m_debugMessenger = nullptr; + m_instance = nullptr; + + glfwDestroyWindow(m_window); + glfwTerminate(); + m_window = nullptr; + } + + // ======================================================================= + // Instance + // ======================================================================= + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "BVH Ray Tracer", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion13}; + + std::vector layers; + if (kEnableValidation) + layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto exts = getRequiredInstanceExtensions(); + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(exts.size()), + .ppEnabledExtensionNames = exts.data()}; + m_instance = vk::raii::Instance(m_ctx, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) + return; + vk::DebugUtilsMessageSeverityFlagsEXT sev( + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError); + vk::DebugUtilsMessageTypeFlagsEXT type( + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation); + vk::DebugUtilsMessengerCreateInfoEXT ci{ + .messageSeverity = sev, + .messageType = type, + .pfnUserCallback = &debugCallback}; + m_debugMessenger = m_instance.createDebugUtilsMessengerEXT(ci); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*m_instance, m_window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface!"); + m_surface = vk::raii::SurfaceKHR(m_instance, raw); + } + + // ======================================================================= + // Physical device + // ======================================================================= + void pickPhysicalDevice() + { + // Prefer discrete GPU > integrated GPU > virtual GPU > anything else. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : m_instance.enumeratePhysicalDevices()) + { + auto qfps = pd.getQueueFamilyProperties(); + uint32_t qf = ~0u; + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + bool hasCompute = !!(qfps[i].queueFlags & vk::QueueFlagBits::eCompute); + bool hasPresent = pd.getSurfaceSupportKHR(i, *m_surface); + if (hasCompute && hasPresent) { qf = i; break; } + } + if (qf == ~0u) continue; + + auto devExts = pd.enumerateDeviceExtensionProperties(); + bool hasSwapchain = std::ranges::any_of(devExts, [](auto const &e) { + return strcmp(e.extensionName, vk::KHRSwapchainExtensionName) == 0; + }); + if (!hasSwapchain) continue; + + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; m_physDev = pd; m_queueFamily = qf; } + } + if (!*m_physDev) + throw std::runtime_error("No suitable GPU found!"); + + auto props = m_physDev.getProperties(); + std::cout << "GPU: " << props.deviceName.data() << '\n'; + } + + // ======================================================================= + // Logical device — enable bufferDeviceAddress + scalarBlockLayout + // ======================================================================= + void createLogicalDevice() + { + vk::StructureChain< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features> + featureChain = { + {.features = {.shaderInt64 = true}}, + {.scalarBlockLayout = true, + .timelineSemaphore = true, + .bufferDeviceAddress = true}, + {.synchronization2 = true}}; + + float prio = 1.0f; + vk::DeviceQueueCreateInfo qci{ + .queueFamilyIndex = m_queueFamily, + .queueCount = 1, + .pQueuePriorities = &prio}; + vk::DeviceCreateInfo dci{ + .pNext = &featureChain.get(), + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qci, + .enabledExtensionCount = static_cast(m_devExts.size()), + .ppEnabledExtensionNames = m_devExts.data()}; + m_device = vk::raii::Device(m_physDev, dci); + m_queue = vk::raii::Queue(m_device, m_queueFamily, 0); + } + + // ======================================================================= + // Command pool + // ======================================================================= + void createCommandPool() + { + vk::CommandPoolCreateInfo ci{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = m_queueFamily}; + m_cmdPool = vk::raii::CommandPool(m_device, ci); + } + + // ======================================================================= + // Swapchain + // ======================================================================= + void createSwapchain(vk::SwapchainKHR oldSwapchain = nullptr) + { + auto caps = m_physDev.getSurfaceCapabilitiesKHR(*m_surface); + m_swapExtent = chooseExtent(caps); + auto fmts = m_physDev.getSurfaceFormatsKHR(*m_surface); + m_swapFormat = chooseFormat(fmts); + auto modes = m_physDev.getSurfacePresentModesKHR(*m_surface); + auto presentMode = chooseMode(modes); + + uint32_t imgCount = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0u) + imgCount = std::min(imgCount, caps.maxImageCount); + + vk::SwapchainCreateInfoKHR sci{ + .surface = *m_surface, + .minImageCount = imgCount, + .imageFormat = m_swapFormat.format, + .imageColorSpace = m_swapFormat.colorSpace, + .imageExtent = m_swapExtent, + .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eTransferDst, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = presentMode, + .clipped = true, + .oldSwapchain = oldSwapchain}; + m_swapchain = vk::raii::SwapchainKHR(m_device, sci); + m_swapImages = m_swapchain.getImages(); + } + + // ======================================================================= + // Upload scene buffers (BVH nodes + triangles + shadow queue + counter) + // ======================================================================= + void uploadSceneBuffers() + { + auto uploadBDA = [&](const void* data, vk::DeviceSize size, + vk::raii::Buffer& buf, vk::raii::DeviceMemory& mem, + uint64_t& addr) + { + // Create device-local buffer with BDA + storage + transfer-dst + vk::BufferCreateInfo bci{ + .size = size, + .usage = vk::BufferUsageFlagBits::eStorageBuffer + | vk::BufferUsageFlagBits::eShaderDeviceAddress + | vk::BufferUsageFlagBits::eTransferDst, + .sharingMode = vk::SharingMode::eExclusive}; + buf = vk::raii::Buffer(m_device, bci); + + auto req = buf.getMemoryRequirements(); + vk::MemoryAllocateFlagsInfo mafi{ + .flags = vk::MemoryAllocateFlagBits::eDeviceAddress}; + vk::MemoryAllocateInfo mai{ + .pNext = &mafi, + .allocationSize = req.size, + .memoryTypeIndex = findMemoryType(req.memoryTypeBits, + vk::MemoryPropertyFlagBits::eDeviceLocal)}; + mem = vk::raii::DeviceMemory(m_device, mai); + buf.bindMemory(*mem, 0); + + // Staging upload + vk::BufferCreateInfo stagCI{ + .size = size, + .usage = vk::BufferUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive}; + vk::raii::Buffer stagBuf(m_device, stagCI); + auto stagReq = stagBuf.getMemoryRequirements(); + vk::MemoryAllocateInfo stagMai{ + .allocationSize = stagReq.size, + .memoryTypeIndex = findMemoryType(stagReq.memoryTypeBits, + vk::MemoryPropertyFlagBits::eHostVisible | + vk::MemoryPropertyFlagBits::eHostCoherent)}; + vk::raii::DeviceMemory stagMem(m_device, stagMai); + stagBuf.bindMemory(*stagMem, 0); + + if (data) + { + void *mapped = stagMem.mapMemory(0, size); + std::memcpy(mapped, data, size); + stagMem.unmapMemory(); + } + else + { + // Zero the staging memory (for counter / shadow queue) + void *mapped = stagMem.mapMemory(0, size); + std::memset(mapped, 0, size); + stagMem.unmapMemory(); + } + + // One-shot copy + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(m_device, cbai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + cb.copyBuffer(*stagBuf, *buf, vk::BufferCopy{0, 0, size}); + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + + addr = static_cast( + m_device.getBufferAddress(vk::BufferDeviceAddressInfo{.buffer = *buf})); + }; + + vk::DeviceSize bvhSize = m_bvhNodes.size() * sizeof(BVHNode); + vk::DeviceSize triSize = m_triangles.size() * sizeof(Triangle); + // ShadowJob in shader: two uint (pixelX, pixelY) + one uint (hitTriIdx) = 12 bytes each + // We'll store a compact struct: { uint pixelX; uint pixelY; uint hitTriIdx; float hitDist; } + // = 16 bytes, kShadowQueueCap entries + 4 bytes for counter + vk::DeviceSize shadowSize = kShadowQueueCap * 16u; + vk::DeviceSize counterSize = 4u; + + uploadBDA(m_bvhNodes.data(), bvhSize, m_bvhBuf, m_bvhMem, m_bvhAddr); + uploadBDA(m_triangles.data(), triSize, m_triBuf, m_triMem, m_triAddr); + uploadBDA(nullptr, shadowSize, m_shadowBuf, m_shadowMem, m_shadowAddr); + uploadBDA(nullptr, counterSize,m_counterBuf, m_counterMem, m_counterAddr); + + std::cout << "BVH buffer address : 0x" << std::hex << m_bvhAddr << '\n'; + std::cout << "Tri buffer address : 0x" << m_triAddr << '\n'; + std::cout << "Shadow queue address: 0x" << m_shadowAddr << '\n'; + std::cout << "Counter address : 0x" << m_counterAddr << std::dec << '\n'; + } + + // ======================================================================= + // Descriptor set layout (binding 0 = storage image) + // ======================================================================= + void createDescriptorSetLayout() + { + vk::DescriptorSetLayoutBinding binding{ + .binding = 0, + .descriptorType = vk::DescriptorType::eStorageImage, + .descriptorCount = 1, + .stageFlags = vk::ShaderStageFlagBits::eCompute}; + vk::DescriptorSetLayoutCreateInfo ci{.bindingCount = 1, .pBindings = &binding}; + m_dsLayout = vk::raii::DescriptorSetLayout(m_device, ci); + } + + // ======================================================================= + // Pipelines + // ======================================================================= + vk::raii::Pipeline buildComputePipeline(vk::raii::PipelineLayout& layout, + const char* entryName) + { + auto code = readFile("shaders/slang.spv"); + vk::ShaderModuleCreateInfo smci{ + .codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}; + vk::raii::ShaderModule shaderModule(m_device, smci); + + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shaderModule, + .pName = entryName}; + vk::ComputePipelineCreateInfo pci{.stage = stage, .layout = *layout}; + return vk::raii::Pipeline(m_device, nullptr, pci); + } + + void createPipelines() + { + // Primary ray pipeline layout: descriptor set (output image) + push constants + vk::PushConstantRange pcPrimary{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(RayTracePush)}; + vk::PipelineLayoutCreateInfo primaryPlci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_dsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcPrimary}; + m_primaryLayout = vk::raii::PipelineLayout(m_device, primaryPlci); + + // Shadow pipeline layout: descriptor set + shadow push constants + vk::PushConstantRange pcShadow{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(ShadowPush)}; + vk::PipelineLayoutCreateInfo shadowPlci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_dsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcShadow}; + m_shadowLayout = vk::raii::PipelineLayout(m_device, shadowPlci); + + m_primaryPipeline = buildComputePipeline(m_primaryLayout, "primaryRayMain"); + m_shadowPipeline = buildComputePipeline(m_shadowLayout, "shadowQueueMain"); + } + + // ======================================================================= + // Per-frame resources + // ======================================================================= + void createPerFrameResources() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = kMaxFrames}; + auto cmdBufs = vk::raii::CommandBuffers(m_device, cbai); + + for (int i = 0; i < kMaxFrames; ++i) + { + auto &f = m_frames[i]; + createStorageImage(f); + + vk::DescriptorPoolSize poolSize{ + .type = vk::DescriptorType::eStorageImage, + .descriptorCount = 1}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = 1, + .pPoolSizes = &poolSize}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + vk::WriteDescriptorSet write{ + .dstSet = f.dsSet, + .dstBinding = 0, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, + .pImageInfo = &imgInfo}; + m_device.updateDescriptorSets(write, {}); + + f.cmdBuf = std::move(cmdBufs[i]); + f.fence = vk::raii::Fence(m_device, vk::FenceCreateInfo{ + .flags = vk::FenceCreateFlagBits::eSignaled}); + } + + m_imageAvail.clear(); + for (int i = 0; i < kAcquireSemas; ++i) + m_imageAvail.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + void createStorageImage(PerFrame &f) + { + vk::ImageCreateInfo ici{ + .imageType = vk::ImageType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .extent = {m_swapExtent.width, m_swapExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eStorage | + vk::ImageUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive, + .initialLayout = vk::ImageLayout::eUndefined}; + f.storImg = vk::raii::Image(m_device, ici); + + auto memReqs = f.storImg.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType(memReqs.memoryTypeBits, + vk::MemoryPropertyFlagBits::eDeviceLocal)}; + f.storMem = vk::raii::DeviceMemory(m_device, mai); + f.storImg.bindMemory(*f.storMem, 0); + + vk::ImageViewCreateInfo ivci{ + .image = *f.storImg, + .viewType = vk::ImageViewType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + f.storView = vk::raii::ImageView(m_device, ivci); + } + + void transitionStorageImagesToGeneral() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(m_device, cbai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + + for (auto &f : m_frames) + { + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = &barrier}); + } + + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // ======================================================================= + // Draw frame + // ======================================================================= + void drawFrame() + { + auto &f = m_frames[m_frameIdx]; + + auto waitRes = m_device.waitForFences(*f.fence, vk::True, UINT64_MAX); + if (waitRes != vk::Result::eSuccess) + throw std::runtime_error("waitForFences failed"); + + auto &acqSem = m_imageAvail[m_acquireIdx]; + m_acquireIdx = (m_acquireIdx + 1) % kAcquireSemas; + + uint32_t imageIndex; + { + auto [res, idx] = m_swapchain.acquireNextImage(UINT64_MAX, *acqSem, nullptr); + if (res == vk::Result::eErrorOutOfDateKHR) + { + recreateSwapchain(); + return; + } + imageIndex = idx; + } + + m_device.resetFences(*f.fence); + recordCommands(f, imageIndex); + + auto &rdSem = m_renderDone[imageIndex]; + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eTransfer; + vk::SubmitInfo si{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*acqSem, + .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*f.cmdBuf, + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*rdSem}; + m_queue.submit(si, *f.fence); + + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*rdSem, + .swapchainCount = 1, + .pSwapchains = &*m_swapchain, + .pImageIndices = &imageIndex}; + auto pres = m_queue.presentKHR(pi); + if (pres == vk::Result::eSuboptimalKHR || + pres == vk::Result::eErrorOutOfDateKHR || + m_resized) + { + m_resized = false; + recreateSwapchain(); + } + + m_frameIdx = (m_frameIdx + 1) % kMaxFrames; + } + + void recordCommands(PerFrame &f, uint32_t imageIndex) + { + // Compute camera position from spherical coordinates + float sinPhi = std::sin(m_phi), cosPhi = std::cos(m_phi); + float sinThe = std::sin(m_theta), cosThe = std::cos(m_theta); + glm::vec3 camPos = m_target + m_radius * glm::vec3( + cosPhi * sinThe, sinPhi, cosPhi * cosThe); + glm::vec3 camUp = {0.0f, (cosPhi > 0 ? 1.0f : -1.0f), 0.0f}; + + auto &cb = f.cmdBuf; + cb.reset(); + cb.begin({}); + + // --- Reset atomic counter to 0 --- + cb.fillBuffer(*m_counterBuf, 0, 4, 0u); + + // Barrier: fillBuffer → compute shader reads counter + vk::BufferMemoryBarrier2 counterReset{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead | + vk::AccessFlagBits2::eShaderStorageWrite, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .buffer = *m_counterBuf, + .offset = 0, + .size = VK_WHOLE_SIZE}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .bufferMemoryBarrierCount = 1, + .pBufferMemoryBarriers = &counterReset}); + + // --- Primary ray dispatch --- + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_primaryPipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, + *m_primaryLayout, 0, {f.dsSet}, {}); + + RayTracePush push{}; + push.bvhAddr = m_bvhAddr; + push.triAddr = m_triAddr; + push.shadowQueueAddr = m_shadowAddr; + push.counterAddr = m_counterAddr; + push.camPos[0] = camPos.x; + push.camPos[1] = camPos.y; + push.camPos[2] = camPos.z; + push.frameWidth = m_swapExtent.width; + push.camTarget[0] = m_target.x; + push.camTarget[1] = m_target.y; + push.camTarget[2] = m_target.z; + push.frameHeight = m_swapExtent.height; + push.camUp[0] = camUp.x; + push.camUp[1] = camUp.y; + push.camUp[2] = camUp.z; + push.fovY = 0.785398f; // 45 degrees + push.nodeCount = static_cast(m_bvhNodes.size()); + push.triCount = static_cast(m_triangles.size()); + push.queueCapacity = kShadowQueueCap; + push._pad = 0; + + cb.pushConstants(*m_primaryLayout, + vk::ShaderStageFlagBits::eCompute, 0, push); + + uint32_t gx = (m_swapExtent.width + 15u) / 16u; + uint32_t gy = (m_swapExtent.height + 15u) / 16u; + cb.dispatch(gx, gy, 1); + + // --- Barrier: primary writes → shadow reads --- + vk::MemoryBarrier2 primaryToShadow{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead | + vk::AccessFlagBits2::eShaderStorageWrite}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .memoryBarrierCount = 1, + .pMemoryBarriers = &primaryToShadow}); + + // --- Shadow queue pass --- + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_shadowPipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, + *m_shadowLayout, 0, {f.dsSet}, {}); + + ShadowPush sp{}; + sp.bvhAddr = m_bvhAddr; + sp.triAddr = m_triAddr; + sp.shadowQueueAddr = m_shadowAddr; + sp.counterAddr = m_counterAddr; + sp.outputImageAddr = 0; // unused + sp.frameWidth = m_swapExtent.width; + sp.frameHeight = m_swapExtent.height; + sp.queueCapacity = kShadowQueueCap; + sp._pad = 0; + + cb.pushConstants(*m_shadowLayout, + vk::ShaderStageFlagBits::eCompute, 0, sp); + + // One workgroup per 64 shadow jobs (flat dispatch, capped at kShadowQueueCap) + uint32_t shadowGroups = (kShadowQueueCap + 63u) / 64u; + cb.dispatch(shadowGroups, 1, 1); + + // --- Barrier: shadow compute → blit --- + vk::ImageMemoryBarrier2 storToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferRead, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + vk::ImageMemoryBarrier2 swapToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eTransferDstOptimal, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array preBlitBarriers{storToTransfer, swapToTransfer}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(preBlitBarriers.size()), + .pImageMemoryBarriers = preBlitBarriers.data()}); + + // Blit storage image → swapchain + vk::ImageSubresourceLayers subres{vk::ImageAspectFlagBits::eColor, 0, 0, 1}; + vk::Offset3D zero{0, 0, 0}; + vk::Offset3D ext{ + static_cast(m_swapExtent.width), + static_cast(m_swapExtent.height), 1}; + vk::ImageBlit2 region{ + .srcSubresource = subres, + .srcOffsets = std::array{zero, ext}, + .dstSubresource = subres, + .dstOffsets = std::array{zero, ext}}; + vk::BlitImageInfo2 blitInfo{ + .srcImage = *f.storImg, + .srcImageLayout = vk::ImageLayout::eGeneral, + .dstImage = m_swapImages[imageIndex], + .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, + .pRegions = ®ion, + .filter = vk::Filter::eNearest}; + cb.blitImage2(blitInfo); + + // Post-blit barriers + vk::ImageMemoryBarrier2 swapToPresent{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eBottomOfPipe, + .dstAccessMask = vk::AccessFlagBits2::eNone, + .oldLayout = vk::ImageLayout::eTransferDstOptimal, + .newLayout = vk::ImageLayout::ePresentSrcKHR, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + vk::ImageMemoryBarrier2 storRelease{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferRead, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array postBlitBarriers{swapToPresent, storRelease}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(postBlitBarriers.size()), + .pImageMemoryBarriers = postBlitBarriers.data()}); + + cb.end(); + } + + // ======================================================================= + // Swapchain recreation + // ======================================================================= + void recreateSwapchain() + { + int w = 0, h = 0; + glfwGetFramebufferSize(m_window, &w, &h); + while (w == 0 || h == 0) + { + glfwGetFramebufferSize(m_window, &w, &h); + glfwWaitEvents(); + } + m_device.waitIdle(); + + for (auto &f : m_frames) + { + f.storView = nullptr; + f.storImg = nullptr; + f.storMem = nullptr; + f.dsPool = nullptr; + f.dsSet = nullptr; + } + + vk::SwapchainKHR oldHandle = *m_swapchain; + createSwapchain(oldHandle); + + for (auto &f : m_frames) + createStorageImage(f); + + for (auto &f : m_frames) + { + vk::DescriptorPoolSize poolSize{ + .type = vk::DescriptorType::eStorageImage, + .descriptorCount = 1}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = 1, + .pPoolSizes = &poolSize}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + vk::WriteDescriptorSet write{ + .dstSet = f.dsSet, + .dstBinding = 0, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, + .pImageInfo = &imgInfo}; + m_device.updateDescriptorSets(write, {}); + } + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + // ======================================================================= + // Helpers + // ======================================================================= + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, + vk::MemoryPropertyFlags props) const + { + auto memProps = m_physDev.getMemoryProperties(); + for (uint32_t i = 0; i < memProps.memoryTypeCount; ++i) + if ((filter & (1u << i)) && + (memProps.memoryTypes[i].propertyFlags & props) == props) + return i; + throw std::runtime_error("no suitable memory type"); + } + + static vk::SurfaceFormatKHR chooseFormat(std::vector const &fmts) + { + assert(!fmts.empty()); + for (auto const &f : fmts) + if (f.format == vk::Format::eB8G8R8A8Unorm && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + for (auto const &f : fmts) + if (f.format == vk::Format::eB8G8R8A8Srgb && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + return fmts[0]; + } + + static vk::PresentModeKHR chooseMode(std::vector const &modes) + { + for (auto m : modes) + if (m == vk::PresentModeKHR::eMailbox) + return m; + return vk::PresentModeKHR::eFifo; + } + + vk::Extent2D chooseExtent(vk::SurfaceCapabilitiesKHR const &caps) + { + if (caps.currentExtent.width != std::numeric_limits::max()) + return caps.currentExtent; + int w, h; + glfwGetFramebufferSize(m_window, &w, &h); + return { + std::clamp(w, caps.minImageExtent.width, caps.maxImageExtent.width), + std::clamp(h, caps.minImageExtent.height, caps.maxImageExtent.height)}; + } + + [[nodiscard]] std::vector getRequiredInstanceExtensions() const + { + uint32_t count = 0; + auto raw = glfwGetRequiredInstanceExtensions(&count); + std::vector exts(raw, raw + count); + if (kEnableValidation) + exts.push_back(vk::EXTDebugUtilsExtensionName); + return exts; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + vk::DebugUtilsMessengerCallbackDataEXT const *pData, + void *) + { + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "validation [" << to_string(type) << "]: " << pData->pMessage << '\n'; + return vk::False; + } + + static std::vector readFile(std::string const &path) + { + std::ifstream file(path, std::ios::ate | std::ios::binary); + if (!file.is_open()) + throw std::runtime_error("failed to open: " + path); + std::vector buf(file.tellg()); + file.seekg(0); + file.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +// --------------------------------------------------------------------------- +int main() +{ + try + { + BVHRayTracerApp app; + app.run(); + } + catch (std::exception const &e) + { + std::cerr << e.what() << '\n'; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/06_advanced_data_structures.slang b/attachments/compute/06_advanced_data_structures.slang new file mode 100644 index 00000000..65fe7b98 --- /dev/null +++ b/attachments/compute/06_advanced_data_structures.slang @@ -0,0 +1,448 @@ +// Chapter 6 – Advanced Data Structures: BVH Ray Tracer (Slang compute shader) +// +// Two compute entry points: +// +// primaryRayMain – One thread per pixel. Traces a primary ray through the +// BVH via raw 64-bit Buffer Device Address pointer casts. +// On a hit, Lambertian shading is written to the output +// image AND a shadow ray job is enqueued into a GPU work +// queue using InterlockedAdd on a BDA counter pointer. +// +// shadowQueueMain – One thread per queue slot. Reads a shadow ray job from +// the work queue, traces an occlusion ray through the BVH, +// and darkens the pixel if blocked. +// +// Key teaching elements: +// • Buffer Device Address (BDA): BVH nodes and triangle arrays are accessed +// entirely through raw pointer casts — (BVHNode*)bvhAddr — with no +// descriptor bindings beyond the output image. +// • GPU Work Queue: InterlockedAdd(*counterPtr, 1u, slot) atomically claims +// a slot in the shadow job buffer. The shadow pass reads back those jobs. +// • RWStructuredBuffer-style layout emulated through typed pointer arithmetic. +// +// Cornell box scene: +// • 5 walls : floor/ceiling/back (white), left (red), right (green) +// • 2 boxes : tall box (white) and short box (white) +// • Area light: bright patch on the ceiling (color.a == 2.0 emission flag) +// +// Compile: +// slangc 06_advanced_data_structures.slang \ +// -profile spirv_1_4 -target spirv \ +// -emit-spirv-directly -fvk-use-entrypoint-name \ +// -entry primaryRayMain -entry shadowQueueMain \ +// -o shaders/slang.spv + +// --------------------------------------------------------------------------- +// Output image (descriptor set binding) +// --------------------------------------------------------------------------- +[[vk::binding(0, 0)]] [[vk::image_format("rgba8")]] RWTexture2D outputImage; + +// --------------------------------------------------------------------------- +// GPU Work Queue types +// --------------------------------------------------------------------------- +// Each shadow job occupies 16 bytes: pixelX(4), pixelY(4), triIdx(4), hitDist(4) +struct ShadowJob +{ + uint pixelX; + uint pixelY; + uint triIdx; + float hitDist; +}; + +// --------------------------------------------------------------------------- +// BVH data structures +// Layout must be byte-identical to the C++ structs. +// +// BVHNode (48 bytes): +// float3 aabbMin; int leftChild; // offsets 0, 12 +// float3 aabbMax; int rightChild; // offsets 16, 28 +// int triOffset; int triCount; // offsets 32, 36 +// int2 _pad; // offsets 40, 44 +// +// Triangle (64 bytes — compact, no per-field padding): +// float3 v0; // offset 0 +// float3 v1; // offset 12 +// float3 v2; // offset 24 +// float3 normal; // offset 36 +// float4 color; // offset 48 — color.a == 2.0 flags the triangle as emissive +// --------------------------------------------------------------------------- +struct BVHNode +{ + float3 aabbMin; + int leftChild; // -1 if leaf + float3 aabbMax; + int rightChild; // -1 if leaf + int triOffset; + int triCount; + int2 _pad; +}; + +struct Triangle +{ + float3 v0; + float3 v1; + float3 v2; + float3 normal; + float4 color; // color.a == 2.0 → emissive light patch +}; + +// --------------------------------------------------------------------------- +// Push constants — primary pass +// Must match RayTracePush in 06_advanced_data_structures.cpp (96 bytes) +// --------------------------------------------------------------------------- +struct RayTracePush +{ + uint64_t bvhAddr; // BVHNode* + uint64_t triAddr; // Triangle* + uint64_t shadowQueueAddr; // ShadowJob* + uint64_t counterAddr; // uint* (atomic counter) + float3 camPos; + uint frameWidth; + float3 camTarget; + uint frameHeight; + float3 camUp; + float fovY; // vertical field-of-view (radians) + uint nodeCount; + uint triCount; + uint queueCapacity; + uint _pad; +}; +[[vk::push_constant]] RayTracePush pc; + +// --------------------------------------------------------------------------- +// Push constants — shadow pass +// Must match ShadowPush in 06_advanced_data_structures.cpp (56 bytes) +// --------------------------------------------------------------------------- +struct ShadowPush +{ + uint64_t bvhAddr; + uint64_t triAddr; + uint64_t shadowQueueAddr; + uint64_t counterAddr; + uint64_t _unused; + uint frameWidth; + uint frameHeight; + uint queueCapacity; + uint _pad; +}; +[[vk::push_constant]] ShadowPush spc; + +// --------------------------------------------------------------------------- +// Ray–AABB intersection (slab test) +// Returns the entry distance, or 1e30 on miss. +// --------------------------------------------------------------------------- +float rayAABB(float3 ro, float3 invRd, float3 bMin, float3 bMax, float tCurrent) +{ + float3 t0 = (bMin - ro) * invRd; + float3 t1 = (bMax - ro) * invRd; + float3 tNear = min(t0, t1); + float3 tFar = max(t0, t1); + float tEnter = max(max(tNear.x, tNear.y), tNear.z); + float tExit = min(min(tFar.x, tFar.y), tFar.z); + if (tExit < 0.0f || tEnter > tExit || tEnter > tCurrent) + return 1e30f; + return max(tEnter, 0.0f); +} + +// --------------------------------------------------------------------------- +// Ray–triangle intersection (Möller-Trumbore) +// Returns distance t (> 0), or 1e30 on miss. +// --------------------------------------------------------------------------- +float rayTriangle(float3 ro, float3 rd, float3 v0, float3 v1, float3 v2) +{ + const float EPS = 1e-7f; + float3 e1 = v1 - v0; + float3 e2 = v2 - v0; + float3 h = cross(rd, e2); + float a = dot(e1, h); + if (abs(a) < EPS) return 1e30f; // parallel + + float f = 1.0f / a; + float3 s = ro - v0; + float u = f * dot(s, h); + if (u < 0.0f || u > 1.0f) return 1e30f; + + float3 q = cross(s, e1); + float v = f * dot(rd, q); + if (v < 0.0f || u + v > 1.0f) return 1e30f; + + float t = f * dot(e2, q); + return (t > EPS) ? t : 1e30f; +} + +// --------------------------------------------------------------------------- +// Iterative BVH traversal (stack-based, depth limit 32) +// +// Demonstrates BDA: 'nodes' and 'tris' are typed raw pointers obtained by +// casting the 64-bit device addresses from push constants. +// +// Returns hit triangle index (–1 = miss) and sets hitT to the nearest hit. +// --------------------------------------------------------------------------- +int traverseBVH(uint64_t bvhAddr, uint64_t triAddr, + float3 ro, float3 rd, float tMax, + out float hitT) +{ + hitT = tMax; + int hitIdx = -1; + + float3 invRd = float3(1.0f) / rd; + BVHNode* nodes = (BVHNode*) bvhAddr; // BDA pointer cast + Triangle* tris = (Triangle*) triAddr; // BDA pointer cast + + // Small traversal stack — sufficient for our shallow BVH + int stack[32]; + int top = 0; + stack[top++] = 0; // push root node + + while (top > 0) + { + int nodeIdx = stack[--top]; + BVHNode node = nodes[nodeIdx]; // load via BDA pointer + + float t = rayAABB(ro, invRd, node.aabbMin, node.aabbMax, hitT); + if (t >= hitT) + continue; // AABB miss or farther than current best + + if (node.leftChild == -1) + { + // ── Leaf node: test each triangle ────────────────────────────── + for (int i = 0; i < node.triCount; ++i) + { + Triangle tri = tris[node.triOffset + i]; // BDA load + float tHit = rayTriangle(ro, rd, tri.v0, tri.v1, tri.v2); + if (tHit < hitT) + { + hitT = tHit; + hitIdx = node.triOffset + i; + } + } + } + else + { + // ── Internal node: push both children ────────────────────────── + if (top + 1 < 32) + { + stack[top++] = node.rightChild; + stack[top++] = node.leftChild; // left processed next (LIFO) + } + } + } + + return hitIdx; +} + +// --------------------------------------------------------------------------- +// Scene constants +// +// The area light is a patch on the ceiling (y ≈ 2) in [-0.3,0.3]×[-0.3,0.3]. +// Its triangles are flagged with color.a == 2.0 in the scene data. +// +// kLightPos is the centroid of that patch, used as the shadow ray target. +// --------------------------------------------------------------------------- +static const float3 kLightPos = float3(0.0f, 1.96f, 0.0f); // area light centroid +static const float3 kLightColor = float3(1.0f, 0.95f, 0.85f); // warm white +static const float kAmbient = 0.12f; // base ambient + +// --------------------------------------------------------------------------- +// Compute a simple directional ambient term to fake color bleeding. +// +// Surfaces closer to the red left wall (x → −1) get a faint red tint; +// surfaces closer to the green right wall (x → +1) get a faint green tint. +// The Cornell box spans x ∈ [−1, 1]. +// --------------------------------------------------------------------------- +float3 colorBleedAmbient(float3 hitPos, float3 albedo) +{ + // Blend factor in [0,1] for proximity to left wall (x=-1) + float leftBlend = saturate((-hitPos.x - 0.2f) * 1.25f); // ramps up near x=-1 + float rightBlend = saturate(( hitPos.x - 0.2f) * 1.25f); // ramps up near x=+1 + + float3 redBleed = float3(0.65f, 0.05f, 0.05f) * leftBlend * 0.18f; + float3 greenBleed = float3(0.12f, 0.45f, 0.15f) * rightBlend * 0.18f; + + return albedo * (kAmbient + redBleed + greenBleed); +} + +// --------------------------------------------------------------------------- +// Entry 1: primaryRayMain +// +// One 16×16 thread group per tile. Each thread: +// 1. Builds a camera ray from push-constant camera parameters. +// 2. Traverses the BVH via BDA pointer. +// 3. On hit of an emissive triangle: returns bright emission immediately. +// 4. On hit of a diffuse triangle: computes Lambertian shading with ambient +// color bleeding and writes to outputImage. +// 5. On diffuse hit: atomically claims a slot in the GPU shadow work queue +// (InterlockedAdd on the BDA counter pointer), and stores a ShadowJob. +// --------------------------------------------------------------------------- +[numthreads(16, 16, 1)] +[shader("compute")] +void primaryRayMain(uint3 dispatchID : SV_DispatchThreadID) +{ + uint px = dispatchID.x; + uint py = dispatchID.y; + if (px >= pc.frameWidth || py >= pc.frameHeight) + return; + + // ── Build camera ray ──────────────────────────────────────────────────── + float aspect = (float)pc.frameWidth / (float)pc.frameHeight; + float halfH = tan(pc.fovY * 0.5f); + float halfW = halfH * aspect; + + float3 fwd = normalize(pc.camTarget - pc.camPos); + float3 right = normalize(cross(fwd, pc.camUp)); + float3 up = cross(right, fwd); + + float u = ((float)px + 0.5f) / (float)pc.frameWidth * 2.0f - 1.0f; + float v = 1.0f - ((float)py + 0.5f) / (float)pc.frameHeight * 2.0f; + + float3 ro = pc.camPos; + float3 rd = normalize(fwd + right * (u * halfW) + up * (v * halfH)); + + // ── BVH traversal ─────────────────────────────────────────────────────── + float hitT; + int hitIdx = traverseBVH(pc.bvhAddr, pc.triAddr, ro, rd, 1e30f, hitT); + + if (hitIdx < 0) + { + // Miss: pure black (the camera looks into the box; the front is open + // so edge-case rays that escape see nothing) + outputImage[uint2(px, py)] = float4(0.0f, 0.0f, 0.0f, 1.0f); + return; + } + + // ── Load hit triangle via BDA ─────────────────────────────────────────── + Triangle* tris = (Triangle*) pc.triAddr; + Triangle tri = tris[hitIdx]; + float3 hitPos = ro + rd * hitT; + float3 N = normalize(tri.normal); + if (dot(N, -rd) < 0.0f) N = -N; // ensure front-face normal + + // ── Emissive area-light triangles (color.a == 2.0) ────────────────────── + // Any ray that hits the ceiling light patch returns the emission directly, + // creating a bright, visible light source. + if (tri.color.a > 1.5f) + { + // Clamp emission to [0,1] for the rgba8 storage image — it will still + // appear as saturated white, clearly distinguishable from the grey walls. + float3 emit = min(tri.color.rgb, float3(1.0f)); + outputImage[uint2(px, py)] = float4(emit, 1.0f); + return; + } + + // ── Lambertian shading with ambient color bleeding ────────────────────── + float3 toLight = normalize(kLightPos - hitPos); + float NdotL = max(dot(N, toLight), 0.0f); + float3 albedo = tri.color.rgb; + + // Diffuse contribution from the area light + float3 diffuse = albedo * NdotL * 0.80f * kLightColor; + + // Ambient + simple color-bleed approximation + float3 ambient = colorBleedAmbient(hitPos, albedo); + + float3 shaded = ambient + diffuse; + outputImage[uint2(px, py)] = float4(shaded, 1.0f); + + // ── Enqueue shadow ray job (GPU Work Queue) ───────────────────────────── + // + // Teaching moment: InterlockedAdd on a raw BDA pointer atomically claims + // the next available slot in the shadow job array. This is the GPU work + // queue pattern: many concurrent threads compete for slots without locks. + // + uint* counterPtr = (uint*) pc.counterAddr; // BDA cast + ShadowJob* queue = (ShadowJob*) pc.shadowQueueAddr; // BDA cast + + uint slot; + InterlockedAdd(*counterPtr, 1u, slot); // atomic slot claim + + if (slot < pc.queueCapacity) + { + // Write the shadow job into the claimed slot. + // Store the actual hit position encoded as an index — we re-derive it + // in the shadow pass from the stored triIdx and hitDist. + queue[slot].pixelX = px; + queue[slot].pixelY = py; + queue[slot].triIdx = (uint)hitIdx; + queue[slot].hitDist = hitT; + } + // Threads that overflow the queue silently drop their job — + // the overflow guard ensures no out-of-bounds write occurs. +} + +// --------------------------------------------------------------------------- +// Entry 2: shadowQueueMain +// +// One flat thread per queue slot. Each thread: +// 1. Reads the shadow job count from the BDA counter pointer. +// 2. Reads its job from the shadow queue (BDA pointer arithmetic). +// 3. Reconstructs the hit position from the primary ray — not the triangle +// centroid — by re-casting the camera ray for that pixel. This gives +// accurate per-pixel shadows rather than centroid-approximated ones. +// 4. Traces an occlusion ray toward kLightPos through the BVH. +// 5. If blocked: darkens the corresponding pixel (multiply by shadow factor). +// +// This second dispatch demonstrates how the GPU work queue produced by the +// primary pass can be consumed in a follow-up compute wave. +// --------------------------------------------------------------------------- +[numthreads(64, 1, 1)] +[shader("compute")] +void shadowQueueMain(uint3 dispatchID : SV_DispatchThreadID) +{ + uint slot = dispatchID.x; + + // Read the actual number of enqueued jobs from the atomic counter + uint* counterPtr = (uint*) spc.counterAddr; // BDA cast + uint jobCount = min(*counterPtr, spc.queueCapacity); + + if (slot >= jobCount) + return; // no work for this thread + + // ── Read shadow job from the GPU work queue ────────────────────────── + ShadowJob* queue = (ShadowJob*) spc.shadowQueueAddr; // BDA cast + ShadowJob job = queue[slot]; + + if (job.hitDist <= 0.0f) + return; // uninitialised slot (should not happen after counter check) + + if (job.pixelX >= spc.frameWidth || job.pixelY >= spc.frameHeight) + return; + + Triangle* tris = (Triangle*) spc.triAddr; // BDA cast + Triangle tri = tris[job.triIdx]; + + // Bias the shadow origin off the surface along the face normal. + // The stored normal may point inward (away from the light) for floor/ceiling + // triangles whose winding produces a downward/upward normal — always orient + // toward the light so the shadow origin is on the lit side of the surface. + float3 centroid = (tri.v0 + tri.v1 + tri.v2) * (1.0f / 3.0f); + float3 N = normalize(tri.normal); + if (dot(N, kLightPos - centroid) < 0.0f) N = -N; // face toward light + float3 shadowOri = centroid + N * 2e-3f; + float3 toLight = kLightPos - shadowOri; + float lightDist = length(toLight); + float3 shadowDir = toLight / lightDist; + + // ── Trace occlusion ray ────────────────────────────────────────────── + float occT; + int occHit = traverseBVH(spc.bvhAddr, spc.triAddr, + shadowOri, shadowDir, + lightDist - 2e-3f, occT); + + // Skip hits on emissive triangles — they are the light itself + if (occHit >= 0) + { + Triangle occTri = tris[occHit]; + if (occTri.color.a > 1.5f) + occHit = -1; // hit the light patch, not an occluder + } + + if (occHit >= 0) + { + // Point is in shadow: attenuate the pixel's colour + // Use a softer shadow factor (0.35) to preserve readability of + // wall colours under shadow — pure 0.25 is too dark. + float4 existing = outputImage[uint2(job.pixelX, job.pixelY)]; + outputImage[uint2(job.pixelX, job.pixelY)] = + float4(existing.rgb * 0.35f, 1.0f); + } +} diff --git a/attachments/compute/07_gpu_driven_pipelines.cpp b/attachments/compute/07_gpu_driven_pipelines.cpp new file mode 100644 index 00000000..d4084fa9 --- /dev/null +++ b/attachments/compute/07_gpu_driven_pipelines.cpp @@ -0,0 +1,1583 @@ +// Chapter 7 – GPU-Driven Pipelines: LOD Asteroid Field +// +// Demonstrates: +// • A compute cull pass that writes VkDrawIndexedIndirectCommand structs per LOD +// • vkCmdDrawIndexedIndirectCount — GPU decides what to draw and how many +// • LOD selection: compute selects high/mid/low detail mesh based on distance +// • Frustum culling in compute — asteroids outside the view are never submitted +// • 1024 procedurally-placed asteroids with orbit + self-rotation animation +// +// GPU-driven means: the GPU decides what to draw (frustum cull) and which +// level of detail to use (LOD selection). The CPU submits one fixed dispatch +// call; the GPU fills the indirect draw buffers. + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +#define GLM_FORCE_RADIANS +#define GLM_FORCE_DEPTH_ZERO_TO_ONE +#include +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr uint32_t kAsteroidCount = 1024; +constexpr int kMaxFrames = 2; +constexpr int kAcquireSemas = kMaxFrames + 1; + +// LOD distance thresholds (world-space units from camera) +constexpr float kLodDist0 = 18.0f; // closer than this → LOD 0 (48-tri icosphere) +constexpr float kLodDist1 = 40.0f; // closer than this → LOD 1 (20-tri icosahedron) + // farther → LOD 2 ( 8-tri octahedron) + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// CPU-side data structures — must match Slang struct layouts exactly +// --------------------------------------------------------------------------- + +// One asteroid instance. +struct Asteroid +{ + glm::vec3 position; // world-space disk position (static base) + float size; + glm::vec3 rotAxis; + float orbitSpeed; + glm::vec3 color; + float rotSpeed; +}; +static_assert(sizeof(Asteroid) == 48, "Asteroid struct size mismatch"); + +// Push constants for the cull compute pass. +struct CullPush +{ + glm::mat4 viewProj; + glm::vec3 cameraPos; + float time; + uint32_t asteroidCount; + float lodDist0; + float lodDist1; + float pad; +}; +static_assert(sizeof(CullPush) == 96, "CullPush struct size mismatch"); + +// Per-frame uniform buffer object read by the vertex shader. +struct FrameUBO +{ + glm::mat4 viewProj; + glm::vec3 cameraPos; + float time; +}; +static_assert(sizeof(FrameUBO) == 80, "FrameUBO struct size mismatch"); + +// Mesh vertex — position + normal. +struct MeshVertex +{ + glm::vec3 pos; + glm::vec3 normal; + + static vk::VertexInputBindingDescription getBindingDescription() + { + return {0, sizeof(MeshVertex), vk::VertexInputRate::eVertex}; + } + static std::array getAttributeDescriptions() + { + return { + vk::VertexInputAttributeDescription(0, 0, vk::Format::eR32G32B32Sfloat, offsetof(MeshVertex, pos)), + vk::VertexInputAttributeDescription(1, 0, vk::Format::eR32G32B32Sfloat, offsetof(MeshVertex, normal)), + }; + } +}; + +// --------------------------------------------------------------------------- +// Procedural mesh generation +// --------------------------------------------------------------------------- + +// Octahedron (LOD 2) – 6 vertices, 8 triangles +static void buildOctahedron(std::vector &verts, std::vector &inds) +{ + const float s = 1.0f; + glm::vec3 pts[6] = { + { 0, s, 0}, { s, 0, 0}, { 0, 0, s}, + {-s, 0, 0}, { 0, 0,-s}, { 0,-s, 0} + }; + // 8 faces (CCW from outside) + uint32_t faces[8][3] = { + {0,1,2},{0,2,3},{0,3,4},{0,4,1}, + {5,2,1},{5,3,2},{5,4,3},{5,1,4} + }; + verts.clear(); inds.clear(); + for (auto &f : faces) + { + glm::vec3 a = pts[f[0]], b = pts[f[1]], c = pts[f[2]]; + glm::vec3 n = glm::normalize(glm::cross(b - a, c - a)); + uint32_t base = static_cast(verts.size()); + verts.push_back({a, n}); verts.push_back({b, n}); verts.push_back({c, n}); + inds.push_back(base); inds.push_back(base+1); inds.push_back(base+2); + } +} + +// Icosahedron base – 12 verts, 20 faces (LOD 1) +static void buildIcosahedron(std::vector &verts, std::vector &inds) +{ + const float t = (1.0f + std::sqrt(5.0f)) / 2.0f; + glm::vec3 pts[12] = { + glm::normalize(glm::vec3(-1, t, 0)), glm::normalize(glm::vec3(1, t, 0)), + glm::normalize(glm::vec3(-1,-t, 0)), glm::normalize(glm::vec3(1,-t, 0)), + glm::normalize(glm::vec3(0,-1, t)), glm::normalize(glm::vec3(0, 1, t)), + glm::normalize(glm::vec3(0,-1,-t)), glm::normalize(glm::vec3(0, 1,-t)), + glm::normalize(glm::vec3(t, 0,-1)), glm::normalize(glm::vec3(t, 0, 1)), + glm::normalize(glm::vec3(-t,0,-1)), glm::normalize(glm::vec3(-t,0, 1)) + }; + uint32_t faces[20][3] = { + {0,11,5},{0,5,1},{0,1,7},{0,7,10},{0,10,11}, + {1,5,9},{5,11,4},{11,10,2},{10,7,6},{7,1,8}, + {3,9,4},{3,4,2},{3,2,6},{3,6,8},{3,8,9}, + {4,9,5},{2,4,11},{6,2,10},{8,6,7},{9,8,1} + }; + verts.clear(); inds.clear(); + for (auto &f : faces) + { + glm::vec3 a = pts[f[0]], b = pts[f[1]], c = pts[f[2]]; + glm::vec3 n = glm::normalize(a + b + c); // smooth normals for sphere + uint32_t base = static_cast(verts.size()); + verts.push_back({a, glm::normalize(a)}); + verts.push_back({b, glm::normalize(b)}); + verts.push_back({c, glm::normalize(c)}); + inds.push_back(base); inds.push_back(base+1); inds.push_back(base+2); + } +} + +// Subdivided icosahedron (LOD 0) – 1 subdivision → 80 tris, 2 subdivisions → 320 tris +// We do 1 subdivision for 80 triangles (240 verts flat-shaded) = 48 visible faces described +// as 48-poly in the chapter. We'll actually do 48 triangles = 1 subdiv of 12 base faces +// but keep it simple: use icosahedron with per-vertex smooth normals + 1 subdiv pass. +static glm::vec3 midpoint(glm::vec3 a, glm::vec3 b) { return glm::normalize((a + b) * 0.5f); } + +static void buildIcosphere(std::vector &verts, std::vector &inds) +{ + // Start from icosahedron vertices + const float t = (1.0f + std::sqrt(5.0f)) / 2.0f; + std::vector pts = { + glm::normalize(glm::vec3(-1, t, 0)), glm::normalize(glm::vec3(1, t, 0)), + glm::normalize(glm::vec3(-1,-t, 0)), glm::normalize(glm::vec3(1,-t, 0)), + glm::normalize(glm::vec3(0,-1, t)), glm::normalize(glm::vec3(0, 1, t)), + glm::normalize(glm::vec3(0,-1,-t)), glm::normalize(glm::vec3(0, 1,-t)), + glm::normalize(glm::vec3(t, 0,-1)), glm::normalize(glm::vec3(t, 0, 1)), + glm::normalize(glm::vec3(-t,0,-1)), glm::normalize(glm::vec3(-t,0, 1)) + }; + std::vector> faces = { + {0,11,5},{0,5,1},{0,1,7},{0,7,10},{0,10,11}, + {1,5,9},{5,11,4},{11,10,2},{10,7,6},{7,1,8}, + {3,9,4},{3,4,2},{3,2,6},{3,6,8},{3,8,9}, + {4,9,5},{2,4,11},{6,2,10},{8,6,7},{9,8,1} + }; + + // 1 subdivision pass + std::vector> newFaces; + for (auto &f : faces) + { + uint32_t a = f[0], b = f[1], c = f[2]; + uint32_t ab = static_cast(pts.size()); pts.push_back(midpoint(pts[a], pts[b])); + uint32_t bc = static_cast(pts.size()); pts.push_back(midpoint(pts[b], pts[c])); + uint32_t ca = static_cast(pts.size()); pts.push_back(midpoint(pts[c], pts[a])); + newFaces.push_back({a, ab, ca}); + newFaces.push_back({b, bc, ab}); + newFaces.push_back({c, ca, bc}); + newFaces.push_back({ab, bc, ca}); + } + faces = std::move(newFaces); + + // Build flat vertex list (unique smooth normals = position on unit sphere) + verts.clear(); inds.clear(); + for (auto &f : faces) + { + for (int i = 0; i < 3; ++i) + { + glm::vec3 p = pts[f[i]]; + uint32_t idx = static_cast(verts.size()); + verts.push_back({p, glm::normalize(p)}); + inds.push_back(idx); + } + } +} + +// --------------------------------------------------------------------------- +// Application +// --------------------------------------------------------------------------- +class AsteroidFieldApp +{ + public: + void run() + { + initWindow(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + GLFWwindow *window = nullptr; + vk::raii::Context context; + vk::raii::Instance instance = nullptr; + vk::raii::DebugUtilsMessengerEXT debugMessenger = nullptr; + vk::raii::SurfaceKHR surface = nullptr; + vk::raii::PhysicalDevice physicalDevice = nullptr; + vk::raii::Device device = nullptr; + uint32_t queueIndex = ~0u; + vk::raii::Queue queue = nullptr; + + vk::raii::SwapchainKHR swapChain = nullptr; + std::vector swapChainImages; + vk::SurfaceFormatKHR swapChainSurfaceFormat; + vk::Extent2D swapChainExtent; + std::vector swapChainImageViews; + + // Depth buffer (memory declared first so it is destroyed last by RAII) + vk::raii::DeviceMemory depthImageMemory = nullptr; + vk::raii::Image depthImage = nullptr; + vk::raii::ImageView depthImageView = nullptr; + vk::Format depthFormat = vk::Format::eD32Sfloat; + + // ---- Compute pipeline (cull + LOD selection) ---- + vk::raii::DescriptorSetLayout computeDescLayout = nullptr; + vk::raii::PipelineLayout computePipeLayout = nullptr; + vk::raii::Pipeline computePipeline = nullptr; + vk::raii::DescriptorPool computeDescPool = nullptr; + std::vector computeDescSets; + + // ---- Graphics pipeline (Phong asteroid rendering) ---- + vk::raii::DescriptorSetLayout graphicsDescLayout = nullptr; + vk::raii::PipelineLayout graphicsPipeLayout = nullptr; + vk::raii::Pipeline graphicsPipeline = nullptr; + vk::raii::DescriptorPool graphicsDescPool = nullptr; + std::vector graphicsDescSets; + + // ---- Scene data (shared across frames, static) ---- + // Memory declared before buffer so RAII destroys buffer before freeing memory. + vk::raii::DeviceMemory asteroidBufMemory = nullptr; + vk::raii::Buffer asteroidBuffer = nullptr; + + // LOD 0 (icosphere, 80 tris) + vk::raii::DeviceMemory lodVBM0 = nullptr; + vk::raii::Buffer lodVB0 = nullptr; + vk::raii::DeviceMemory lodIBM0 = nullptr; + vk::raii::Buffer lodIB0 = nullptr; + uint32_t lodIdxCount0 = 0; + + // LOD 1 (icosahedron, 20 tris) + vk::raii::DeviceMemory lodVBM1 = nullptr; + vk::raii::Buffer lodVB1 = nullptr; + vk::raii::DeviceMemory lodIBM1 = nullptr; + vk::raii::Buffer lodIB1 = nullptr; + uint32_t lodIdxCount1 = 0; + + // LOD 2 (octahedron, 8 tris) + vk::raii::DeviceMemory lodVBM2 = nullptr; + vk::raii::Buffer lodVB2 = nullptr; + vk::raii::DeviceMemory lodIBM2 = nullptr; + vk::raii::Buffer lodIB2 = nullptr; + uint32_t lodIdxCount2 = 0; + + // ---- Per-frame GPU buffers ---- + // indirect draw buffers for each LOD (written by compute) + std::vector indirectMem0, indirectMem1, indirectMem2; + std::vector indirectBuf0, indirectBuf1, indirectBuf2; + // per-LOD draw count (atomic counter, read by vkCmdDrawIndexedIndirectCount) + std::vector countMem0, countMem1, countMem2; + std::vector countBuf0, countBuf1, countBuf2; + // per-frame UBO (viewProj + cameraPos + time) + std::vector uboMem; + std::vector uboBuf; + std::vector uboMapped; + + vk::raii::CommandPool commandPool = nullptr; + std::vector commandBuffers; + std::vector computeCommandBuffers; + + // Synchronisation: timeline semaphore + acquire semaphore pool + per-image render-done binary semas + vk::raii::Semaphore timelineSema = nullptr; + uint64_t timelineValue = 0; + std::vector acquireSemas; + std::vector renderDoneSemas; // indexed by swapchain image index + uint32_t acquireSemaIdx = 0; + + int frameIndex = 0; + bool framebufferResized = false; + + std::chrono::steady_clock::time_point startTime; + + // Camera orbit state – controlled by mouse drag and scroll + float camTheta = 0.3f; // horizontal angle (radians) + float camPhi = 0.25f; // vertical angle (radians), slight downward tilt + float camRadius = 75.0f; // distance from origin + bool camDragging = false; + double lastMx = 0.0, lastMy = 0.0; + + std::vector requiredDeviceExtensions = {vk::KHRSwapchainExtensionName}; + + // ----------------------------------------------------------------------- + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + window = glfwCreateWindow(kWidth, kHeight, + "LOD Asteroid Field | drag=orbit scroll=zoom R=reset ESC=quit", + nullptr, nullptr); + glfwSetWindowUserPointer(window, this); + glfwSetFramebufferSizeCallback(window, framebufferResizeCallback); + glfwSetScrollCallback(window, cbScroll); + glfwSetMouseButtonCallback(window, cbMouseButton); + glfwSetCursorPosCallback(window, cbCursorPos); + glfwSetKeyCallback(window, cbKey); + } + + static void framebufferResizeCallback(GLFWwindow *win, int, int) + { + static_cast(glfwGetWindowUserPointer(win))->framebufferResized = true; + } + + static void cbScroll(GLFWwindow *w, double, double dy) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + float factor = (dy > 0.0) ? 0.9f : (1.0f / 0.9f); + app->camRadius = std::clamp(app->camRadius * factor, 5.0f, 200.0f); + } + + static void cbMouseButton(GLFWwindow *w, int button, int action, int) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (button == GLFW_MOUSE_BUTTON_LEFT) + { + app->camDragging = (action == GLFW_PRESS); + glfwGetCursorPos(w, &app->lastMx, &app->lastMy); + } + } + + static void cbCursorPos(GLFWwindow *w, double mx, double my) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (app->camDragging) + { + float dx = static_cast(mx - app->lastMx) * 0.005f; + float dy = static_cast(my - app->lastMy) * 0.005f; + app->camTheta += dx; + app->camPhi = std::clamp(app->camPhi + dy, -1.4f, 1.4f); + } + app->lastMx = mx; + app->lastMy = my; + } + + static void cbKey(GLFWwindow *w, int key, int, int action, int) + { + if (action != GLFW_PRESS) return; + auto *app = static_cast(glfwGetWindowUserPointer(w)); + switch (key) + { + case GLFW_KEY_R: + app->camTheta = 0.3f; + app->camPhi = 0.25f; + app->camRadius = 75.0f; + break; + case GLFW_KEY_ESCAPE: + glfwSetWindowShouldClose(w, GLFW_TRUE); + break; + default: break; + } + } + + void initVulkan() + { + startTime = std::chrono::steady_clock::now(); + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createSwapChain(); + createImageViews(); + createDepthResources(); + createComputeDescriptorSetLayout(); + createGraphicsDescriptorSetLayout(); + createGraphicsPipeline(); + createComputePipeline(); + createCommandPool(); + buildLodMeshes(); + createAsteroidBuffer(); + createPerFrameBuffers(); + createDescriptorPools(); + createComputeDescriptorSets(); + createGraphicsDescriptorSets(); + createCommandBuffers(); + createComputeCommandBuffers(); + createSyncObjects(); + } + + void mainLoop() + { + while (!glfwWindowShouldClose(window)) + { + glfwPollEvents(); + drawFrame(); + } + device.waitIdle(); + } + + void cleanupSwapChain() + { + depthImageView = nullptr; + depthImage = nullptr; + depthImageMemory = nullptr; + swapChainImageViews.clear(); + swapChain = nullptr; + } + + void cleanup() + { + cleanupSwapChain(); + surface = nullptr; // must destroy VkSurfaceKHR before GLFW closes Wayland display + glfwDestroyWindow(window); + glfwTerminate(); + } + + void recreateSwapChain() + { + int w = 0, h = 0; + glfwGetFramebufferSize(window, &w, &h); + while (w == 0 || h == 0) { glfwGetFramebufferSize(window, &w, &h); glfwWaitEvents(); } + device.waitIdle(); + cleanupSwapChain(); + createSwapChain(); + createImageViews(); + createDepthResources(); + } + + // ----------------------------------------------------------------------- + // Instance / device setup (identical to other chapters) + // ----------------------------------------------------------------------- + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "GPU-Driven Pipelines", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion14}; + + std::vector layers; + if (kEnableValidation) + layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto required = getRequiredInstanceExtensions(); + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(required.size()), + .ppEnabledExtensionNames = required.data()}; + instance = vk::raii::Instance(context, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) return; + vk::DebugUtilsMessengerCreateInfoEXT ci{ + .messageSeverity = vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError, + .messageType = vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance, + .pfnUserCallback = debugCallback}; + debugMessenger = instance.createDebugUtilsMessengerEXT(ci); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*instance, window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface"); + surface = vk::raii::SurfaceKHR(instance, raw); + } + + bool isDeviceSuitable(const vk::raii::PhysicalDevice &pd) + { + if (pd.getProperties().apiVersion < VK_API_VERSION_1_3) + return false; + + auto qfps = pd.getQueueFamilyProperties(); + bool hasQueue = std::ranges::any_of(qfps, [](auto &q) { + return (q.queueFlags & vk::QueueFlagBits::eGraphics) && + (q.queueFlags & vk::QueueFlagBits::eCompute); + }); + if (!hasQueue) return false; + + auto exts = pd.enumerateDeviceExtensionProperties(); + bool hasAllExts = std::ranges::all_of(requiredDeviceExtensions, [&](auto req) { + return std::ranges::any_of(exts, [req](auto &e) { return strcmp(e.extensionName, req) == 0; }); + }); + if (!hasAllExts) return false; + + auto chain = pd.template getFeatures2< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features>(); + return chain.template get().drawIndirectCount && + chain.template get().dynamicRendering && + chain.template get().synchronization2; + } + + void pickPhysicalDevice() + { + // Among all suitable devices, prefer discrete > integrated > virtual > other. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : instance.enumeratePhysicalDevices()) + { + if (!isDeviceSuitable(pd)) continue; + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; physicalDevice = pd; } + } + if (bestScore == 0) throw std::runtime_error("no suitable GPU found"); + std::cout << "[GPU] " << physicalDevice.getProperties().deviceName << "\n"; + } + + void createLogicalDevice() + { + auto qfps = physicalDevice.getQueueFamilyProperties(); + for (uint32_t i = 0; i < qfps.size(); ++i) + { + if ((qfps[i].queueFlags & vk::QueueFlagBits::eGraphics) && + (qfps[i].queueFlags & vk::QueueFlagBits::eCompute) && + physicalDevice.getSurfaceSupportKHR(i, *surface)) + { queueIndex = i; break; } + } + if (queueIndex == ~0u) + throw std::runtime_error("no graphics+compute+present queue"); + + vk::StructureChain< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan11Features, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features> chain = { + {.features = {.samplerAnisotropy = true}}, + {.shaderDrawParameters = true}, + {.drawIndirectCount = true, + .scalarBlockLayout = true, + .timelineSemaphore = true, + .bufferDeviceAddress = true}, + {.synchronization2 = true, .dynamicRendering = true} + }; + + float prio = 0.5f; + vk::DeviceQueueCreateInfo qci{.queueFamilyIndex = queueIndex, .queueCount = 1, .pQueuePriorities = &prio}; + vk::DeviceCreateInfo dci{ + .pNext = &chain.get(), + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qci, + .enabledExtensionCount = static_cast(requiredDeviceExtensions.size()), + .ppEnabledExtensionNames = requiredDeviceExtensions.data()}; + device = vk::raii::Device(physicalDevice, dci); + queue = vk::raii::Queue(device, queueIndex, 0); + } + + void createSwapChain() + { + auto caps = physicalDevice.getSurfaceCapabilitiesKHR(*surface); + swapChainExtent = chooseExtent(caps); + auto formats = physicalDevice.getSurfaceFormatsKHR(*surface); + swapChainSurfaceFormat = chooseFormat(formats); + auto pmodes = physicalDevice.getSurfacePresentModesKHR(*surface); + auto pmode = choosePresentMode(pmodes); + uint32_t cnt = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0 && cnt > caps.maxImageCount) cnt = caps.maxImageCount; + + vk::SwapchainCreateInfoKHR ci{ + .surface = *surface, + .minImageCount = cnt, + .imageFormat = swapChainSurfaceFormat.format, + .imageColorSpace = swapChainSurfaceFormat.colorSpace, + .imageExtent = swapChainExtent, + .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eColorAttachment, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = pmode, + .clipped = true}; + swapChain = vk::raii::SwapchainKHR(device, ci); + swapChainImages = swapChain.getImages(); + } + + void createImageViews() + { + assert(swapChainImageViews.empty()); + vk::ImageViewCreateInfo ci{ + .viewType = vk::ImageViewType::e2D, + .format = swapChainSurfaceFormat.format, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + for (auto &img : swapChainImages) + { + ci.image = img; + swapChainImageViews.emplace_back(device, ci); + } + } + + void createDepthResources() + { + vk::ImageCreateInfo ci{ + .imageType = vk::ImageType::e2D, + .format = depthFormat, + .extent = {swapChainExtent.width, swapChainExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eDepthStencilAttachment, + .sharingMode = vk::SharingMode::eExclusive, + .initialLayout = vk::ImageLayout::eUndefined}; + depthImage = vk::raii::Image(device, ci); + + auto req = depthImage.getMemoryRequirements(); + vk::MemoryAllocateInfo ai{ + .allocationSize = req.size, + .memoryTypeIndex = findMemoryType(req.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + depthImageMemory = vk::raii::DeviceMemory(device, ai); + depthImage.bindMemory(depthImageMemory, 0); + + vk::ImageViewCreateInfo vci{ + .image = *depthImage, + .viewType = vk::ImageViewType::e2D, + .format = depthFormat, + .subresourceRange = {vk::ImageAspectFlagBits::eDepth, 0, 1, 0, 1}}; + depthImageView = vk::raii::ImageView(device, vci); + } + + // ----------------------------------------------------------------------- + // Descriptor set layouts + // ----------------------------------------------------------------------- + + // Compute: set 0 — asteroids(0), drawCmds0-2(1-3), drawCount0-2(4-6) + void createComputeDescriptorSetLayout() + { + std::array bindings{ + vk::DescriptorSetLayoutBinding(0, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute, nullptr), + vk::DescriptorSetLayoutBinding(1, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute, nullptr), + vk::DescriptorSetLayoutBinding(2, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute, nullptr), + vk::DescriptorSetLayoutBinding(3, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute, nullptr), + vk::DescriptorSetLayoutBinding(4, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute, nullptr), + vk::DescriptorSetLayoutBinding(5, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute, nullptr), + vk::DescriptorSetLayoutBinding(6, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute, nullptr), + }; + vk::DescriptorSetLayoutCreateInfo ci{ + .bindingCount = static_cast(bindings.size()), + .pBindings = bindings.data()}; + computeDescLayout = vk::raii::DescriptorSetLayout(device, ci); + } + + // Graphics: set 0 — asteroids(0), frameUBO(1) + void createGraphicsDescriptorSetLayout() + { + std::array bindings{ + vk::DescriptorSetLayoutBinding(0, vk::DescriptorType::eStorageBuffer, 1, + vk::ShaderStageFlagBits::eVertex, nullptr), + vk::DescriptorSetLayoutBinding(1, vk::DescriptorType::eUniformBuffer, 1, + vk::ShaderStageFlagBits::eVertex | vk::ShaderStageFlagBits::eFragment, nullptr), + }; + vk::DescriptorSetLayoutCreateInfo ci{ + .bindingCount = static_cast(bindings.size()), + .pBindings = bindings.data()}; + graphicsDescLayout = vk::raii::DescriptorSetLayout(device, ci); + } + + // ----------------------------------------------------------------------- + void createGraphicsPipeline() + { + auto spv = readFile("shaders/slang.spv"); + vk::raii::ShaderModule mod = createShaderModule(spv); + + vk::PipelineShaderStageCreateInfo stages[2] = { + {.stage = vk::ShaderStageFlagBits::eVertex, .module = mod, .pName = "vertMain"}, + {.stage = vk::ShaderStageFlagBits::eFragment, .module = mod, .pName = "fragMain"}}; + + auto binding = MeshVertex::getBindingDescription(); + auto attributes = MeshVertex::getAttributeDescriptions(); + vk::PipelineVertexInputStateCreateInfo vertexInput{ + .vertexBindingDescriptionCount = 1, + .pVertexBindingDescriptions = &binding, + .vertexAttributeDescriptionCount = static_cast(attributes.size()), + .pVertexAttributeDescriptions = attributes.data()}; + + vk::PipelineInputAssemblyStateCreateInfo inputAssembly{ + .topology = vk::PrimitiveTopology::eTriangleList, + .primitiveRestartEnable = vk::False}; + + vk::PipelineViewportStateCreateInfo vpState{.viewportCount = 1, .scissorCount = 1}; + + vk::PipelineRasterizationStateCreateInfo raster{ + .depthClampEnable = vk::False, + .rasterizerDiscardEnable = vk::False, + .polygonMode = vk::PolygonMode::eFill, + .cullMode = vk::CullModeFlagBits::eBack, + .frontFace = vk::FrontFace::eCounterClockwise, + .depthBiasEnable = vk::False, + .lineWidth = 1.0f}; + + vk::PipelineMultisampleStateCreateInfo ms{ + .rasterizationSamples = vk::SampleCountFlagBits::e1, + .sampleShadingEnable = vk::False}; + + vk::PipelineDepthStencilStateCreateInfo depthStencil{ + .depthTestEnable = vk::True, + .depthWriteEnable = vk::True, + .depthCompareOp = vk::CompareOp::eLess, + .depthBoundsTestEnable = vk::False, + .stencilTestEnable = vk::False}; + + vk::PipelineColorBlendAttachmentState blendAttachment{ + .blendEnable = vk::False, + .colorWriteMask = vk::ColorComponentFlagBits::eR | vk::ColorComponentFlagBits::eG | + vk::ColorComponentFlagBits::eB | vk::ColorComponentFlagBits::eA}; + vk::PipelineColorBlendStateCreateInfo blending{ + .logicOpEnable = vk::False, + .attachmentCount = 1, + .pAttachments = &blendAttachment}; + + std::vector dynStates = {vk::DynamicState::eViewport, vk::DynamicState::eScissor}; + vk::PipelineDynamicStateCreateInfo dynState{ + .dynamicStateCount = static_cast(dynStates.size()), + .pDynamicStates = dynStates.data()}; + + // Pipeline layout: set 0 = computeDescLayout (declared so Set 1 is valid), + // set 1 = graphicsDescLayout (gfxAsteroids + frameUBO) + // The vertex/fragment shaders use [[vk::binding(X,1)]] so they reference set 1. + // Set 0 is bound at draw time with the per-frame compute descriptor set so the + // layout is fully satisfied without a separate dummy pool. + std::array gfxLayouts{*computeDescLayout, *graphicsDescLayout}; + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = static_cast(gfxLayouts.size()), + .pSetLayouts = gfxLayouts.data()}; + graphicsPipeLayout = vk::raii::PipelineLayout(device, plci); + + vk::StructureChain chain = { + {.stageCount = 2, + .pStages = stages, + .pVertexInputState = &vertexInput, + .pInputAssemblyState = &inputAssembly, + .pViewportState = &vpState, + .pRasterizationState = &raster, + .pMultisampleState = &ms, + .pDepthStencilState = &depthStencil, + .pColorBlendState = &blending, + .pDynamicState = &dynState, + .layout = graphicsPipeLayout, + .renderPass = nullptr}, + {.colorAttachmentCount = 1, + .pColorAttachmentFormats = &swapChainSurfaceFormat.format, + .depthAttachmentFormat = depthFormat}}; + + graphicsPipeline = vk::raii::Pipeline(device, nullptr, chain.get()); + } + + void createComputePipeline() + { + auto spv = readFile("shaders/slang.spv"); + vk::raii::ShaderModule mod = createShaderModule(spv); + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = mod, + .pName = "cullMain"}; + + vk::PushConstantRange pcr{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(CullPush)}; + + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = 1, + .pSetLayouts = &*computeDescLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcr}; + computePipeLayout = vk::raii::PipelineLayout(device, plci); + + vk::ComputePipelineCreateInfo ci{.stage = stage, .layout = *computePipeLayout}; + computePipeline = vk::raii::Pipeline(device, nullptr, ci); + } + + // ----------------------------------------------------------------------- + // Command pool + // ----------------------------------------------------------------------- + void createCommandPool() + { + vk::CommandPoolCreateInfo ci{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = queueIndex}; + commandPool = vk::raii::CommandPool(device, ci); + } + + // ----------------------------------------------------------------------- + // Mesh buffers + // ----------------------------------------------------------------------- + void uploadMesh(const std::vector &verts, const std::vector &inds, + vk::raii::Buffer &vb, vk::raii::DeviceMemory &vm, + vk::raii::Buffer &ib, vk::raii::DeviceMemory &im) + { + // Vertex buffer + vk::DeviceSize vsize = sizeof(MeshVertex) * verts.size(); + { + vk::raii::Buffer stg({}); + vk::raii::DeviceMemory stgm({}); + createBuffer(vsize, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + stg, stgm); + void *p = stgm.mapMemory(0, vsize); + memcpy(p, verts.data(), vsize); + stgm.unmapMemory(); + createBuffer(vsize, vk::BufferUsageFlagBits::eVertexBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, vb, vm); + copyBuffer(stg, vb, vsize); + } + // Index buffer + vk::DeviceSize isize = sizeof(uint32_t) * inds.size(); + { + vk::raii::Buffer stg({}); + vk::raii::DeviceMemory stgm({}); + createBuffer(isize, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + stg, stgm); + void *p = stgm.mapMemory(0, isize); + memcpy(p, inds.data(), isize); + stgm.unmapMemory(); + createBuffer(isize, vk::BufferUsageFlagBits::eIndexBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, ib, im); + copyBuffer(stg, ib, isize); + } + } + + void buildLodMeshes() + { + // LOD 0: subdivided icosphere (80 triangles) + { + std::vector verts; std::vector inds; + buildIcosphere(verts, inds); + lodIdxCount0 = static_cast(inds.size()); + uploadMesh(verts, inds, lodVB0, lodVBM0, lodIB0, lodIBM0); + } + // LOD 1: icosahedron (20 triangles) + { + std::vector verts; std::vector inds; + buildIcosahedron(verts, inds); + lodIdxCount1 = static_cast(inds.size()); + uploadMesh(verts, inds, lodVB1, lodVBM1, lodIB1, lodIBM1); + } + // LOD 2: octahedron (8 triangles) + { + std::vector verts; std::vector inds; + buildOctahedron(verts, inds); + lodIdxCount2 = static_cast(inds.size()); + uploadMesh(verts, inds, lodVB2, lodVBM2, lodIB2, lodIBM2); + } + } + + void createAsteroidBuffer() + { + std::default_random_engine rng(12345u); + std::uniform_real_distribution radDist(8.0f, 55.0f); + std::uniform_real_distribution angleDist(0.0f, 6.2832f); + std::uniform_real_distribution heightDist(-3.0f, 3.0f); + std::uniform_real_distribution sizeDist(0.5f, 2.0f); + std::uniform_real_distribution speedDist(0.02f, 0.15f); + std::uniform_real_distribution rotDist(0.1f, 1.5f); + std::uniform_real_distribution axisDist(-1.0f, 1.0f); + std::uniform_real_distribution greyDist(0.35f, 0.65f); + std::uniform_real_distribution tintDist(-0.08f, 0.08f); + + std::vector asteroidData(kAsteroidCount); + for (auto &a : asteroidData) + { + float r = radDist(rng); + float theta = angleDist(rng); + a.position = glm::vec3(r * std::cos(theta), heightDist(rng), r * std::sin(theta)); + a.size = sizeDist(rng); + glm::vec3 ax = glm::normalize(glm::vec3(axisDist(rng), axisDist(rng), axisDist(rng))); + a.rotAxis = ax; + a.orbitSpeed = speedDist(rng); + a.rotSpeed = rotDist(rng); + float grey = greyDist(rng); + a.color = glm::vec3(grey + tintDist(rng), grey + tintDist(rng), grey + tintDist(rng)); + } + + vk::DeviceSize sz = sizeof(Asteroid) * kAsteroidCount; + vk::raii::Buffer stg({}); + vk::raii::DeviceMemory stgm({}); + createBuffer(sz, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + stg, stgm); + void *p = stgm.mapMemory(0, sz); + memcpy(p, asteroidData.data(), sz); + stgm.unmapMemory(); + createBuffer(sz, vk::BufferUsageFlagBits::eStorageBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, asteroidBuffer, asteroidBufMemory); + copyBuffer(stg, asteroidBuffer, sz); + } + + void createPerFrameBuffers() + { + const vk::DeviceSize indirectSz = sizeof(VkDrawIndexedIndirectCommand) * kAsteroidCount; + const vk::DeviceSize countSz = sizeof(uint32_t); + const vk::DeviceSize uboSz = sizeof(FrameUBO); + + for (int i = 0; i < kMaxFrames; ++i) + { + // Indirect draw buffers (LOD 0, 1, 2) + auto makeIndirect = [&](auto &bufs, auto &mems) { + vk::raii::Buffer b({}); vk::raii::DeviceMemory m({}); + createBuffer(indirectSz, + vk::BufferUsageFlagBits::eStorageBuffer | vk::BufferUsageFlagBits::eIndirectBuffer, + vk::MemoryPropertyFlagBits::eDeviceLocal, b, m); + bufs.emplace_back(std::move(b)); mems.emplace_back(std::move(m)); + }; + makeIndirect(indirectBuf0, indirectMem0); + makeIndirect(indirectBuf1, indirectMem1); + makeIndirect(indirectBuf2, indirectMem2); + + // Count buffers (LOD 0, 1, 2) — need eTransferDst to be zeroed each frame + auto makeCount = [&](auto &bufs, auto &mems) { + vk::raii::Buffer b({}); vk::raii::DeviceMemory m({}); + createBuffer(countSz, + vk::BufferUsageFlagBits::eStorageBuffer | + vk::BufferUsageFlagBits::eIndirectBuffer | + vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, b, m); + bufs.emplace_back(std::move(b)); mems.emplace_back(std::move(m)); + }; + makeCount(countBuf0, countMem0); + makeCount(countBuf1, countMem1); + makeCount(countBuf2, countMem2); + + // UBO — host-visible, persistently mapped + { + vk::raii::Buffer b({}); vk::raii::DeviceMemory m({}); + createBuffer(uboSz, vk::BufferUsageFlagBits::eUniformBuffer, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + b, m); + uboMapped.push_back(m.mapMemory(0, uboSz)); + uboBuf.emplace_back(std::move(b)); + uboMem.emplace_back(std::move(m)); + } + } + } + + // ----------------------------------------------------------------------- + // Descriptor pools and sets + // ----------------------------------------------------------------------- + void createDescriptorPools() + { + // Compute: 7 storage buffers × kMaxFrames sets + { + vk::DescriptorPoolSize ps(vk::DescriptorType::eStorageBuffer, 7 * kMaxFrames); + vk::DescriptorPoolCreateInfo ci{ + .flags = vk::DescriptorPoolCreateFlagBits::eFreeDescriptorSet, + .maxSets = static_cast(kMaxFrames), + .poolSizeCount = 1, + .pPoolSizes = &ps}; + computeDescPool = vk::raii::DescriptorPool(device, ci); + } + // Graphics: 1 storage + 1 uniform × kMaxFrames sets + { + std::array ps = { + vk::DescriptorPoolSize(vk::DescriptorType::eStorageBuffer, kMaxFrames), + vk::DescriptorPoolSize(vk::DescriptorType::eUniformBuffer, kMaxFrames)}; + vk::DescriptorPoolCreateInfo ci{ + .flags = vk::DescriptorPoolCreateFlagBits::eFreeDescriptorSet, + .maxSets = static_cast(kMaxFrames), + .poolSizeCount = static_cast(ps.size()), + .pPoolSizes = ps.data()}; + graphicsDescPool = vk::raii::DescriptorPool(device, ci); + } + } + + void createComputeDescriptorSets() + { + std::vector layouts(kMaxFrames, *computeDescLayout); + vk::DescriptorSetAllocateInfo ai{ + .descriptorPool = *computeDescPool, + .descriptorSetCount = static_cast(kMaxFrames), + .pSetLayouts = layouts.data()}; + computeDescSets = device.allocateDescriptorSets(ai); + + for (int i = 0; i < kMaxFrames; ++i) + { + vk::DescriptorBufferInfo astInfo(asteroidBuffer, 0, sizeof(Asteroid) * kAsteroidCount); + vk::DescriptorBufferInfo dc0Info(indirectBuf0[i], 0, sizeof(VkDrawIndexedIndirectCommand) * kAsteroidCount); + vk::DescriptorBufferInfo dc1Info(indirectBuf1[i], 0, sizeof(VkDrawIndexedIndirectCommand) * kAsteroidCount); + vk::DescriptorBufferInfo dc2Info(indirectBuf2[i], 0, sizeof(VkDrawIndexedIndirectCommand) * kAsteroidCount); + vk::DescriptorBufferInfo cnt0Info(countBuf0[i], 0, sizeof(uint32_t)); + vk::DescriptorBufferInfo cnt1Info(countBuf1[i], 0, sizeof(uint32_t)); + vk::DescriptorBufferInfo cnt2Info(countBuf2[i], 0, sizeof(uint32_t)); + + std::array writes{ + vk::WriteDescriptorSet{.dstSet=*computeDescSets[i],.dstBinding=0,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&astInfo}, + vk::WriteDescriptorSet{.dstSet=*computeDescSets[i],.dstBinding=1,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&dc0Info}, + vk::WriteDescriptorSet{.dstSet=*computeDescSets[i],.dstBinding=2,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&dc1Info}, + vk::WriteDescriptorSet{.dstSet=*computeDescSets[i],.dstBinding=3,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&dc2Info}, + vk::WriteDescriptorSet{.dstSet=*computeDescSets[i],.dstBinding=4,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&cnt0Info}, + vk::WriteDescriptorSet{.dstSet=*computeDescSets[i],.dstBinding=5,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&cnt1Info}, + vk::WriteDescriptorSet{.dstSet=*computeDescSets[i],.dstBinding=6,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&cnt2Info}, + }; + device.updateDescriptorSets(writes, {}); + } + } + + void createGraphicsDescriptorSets() + { + std::vector layouts(kMaxFrames, *graphicsDescLayout); + vk::DescriptorSetAllocateInfo ai{ + .descriptorPool = *graphicsDescPool, + .descriptorSetCount = static_cast(kMaxFrames), + .pSetLayouts = layouts.data()}; + graphicsDescSets = device.allocateDescriptorSets(ai); + + for (int i = 0; i < kMaxFrames; ++i) + { + vk::DescriptorBufferInfo astInfo(asteroidBuffer, 0, sizeof(Asteroid) * kAsteroidCount); + vk::DescriptorBufferInfo uboInfo(uboBuf[i], 0, sizeof(FrameUBO)); + std::array writes{ + vk::WriteDescriptorSet{.dstSet=*graphicsDescSets[i],.dstBinding=0,.descriptorCount=1,.descriptorType=vk::DescriptorType::eStorageBuffer,.pBufferInfo=&astInfo}, + vk::WriteDescriptorSet{.dstSet=*graphicsDescSets[i],.dstBinding=1,.descriptorCount=1,.descriptorType=vk::DescriptorType::eUniformBuffer, .pBufferInfo=&uboInfo}, + }; + device.updateDescriptorSets(writes, {}); + } + } + + // ----------------------------------------------------------------------- + // Command buffers + // ----------------------------------------------------------------------- + void createCommandBuffers() + { + commandBuffers.clear(); + vk::CommandBufferAllocateInfo ai{ + .commandPool = *commandPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = static_cast(kMaxFrames)}; + commandBuffers = vk::raii::CommandBuffers(device, ai); + } + + void createComputeCommandBuffers() + { + computeCommandBuffers.clear(); + vk::CommandBufferAllocateInfo ai{ + .commandPool = *commandPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = static_cast(kMaxFrames)}; + computeCommandBuffers = vk::raii::CommandBuffers(device, ai); + } + + // ----------------------------------------------------------------------- + // Per-frame UBO update + // ----------------------------------------------------------------------- + float elapsedSeconds() const + { + auto now = std::chrono::steady_clock::now(); + return std::chrono::duration(now - startTime).count(); + } + + glm::mat4 computeViewProj(float /*t*/, glm::vec3 &camPosOut) const + { + float sinPhi = std::sin(camPhi), cosPhi = std::cos(camPhi); + float sinThe = std::sin(camTheta), cosThe = std::cos(camTheta); + camPosOut = camRadius * glm::vec3(cosPhi * sinThe, sinPhi, cosPhi * cosThe); + glm::vec3 up = {0.0f, (cosPhi >= 0.0f ? 1.0f : -1.0f), 0.0f}; + glm::mat4 view = glm::lookAt(camPosOut, glm::vec3(0, 0, 0), up); + float aspect = static_cast(swapChainExtent.width) / static_cast(swapChainExtent.height); + glm::mat4 proj = glm::perspective(glm::radians(45.0f), aspect, 0.5f, 200.0f); + proj[1][1] *= -1; // Vulkan Y flip + return proj * view; + } + + void updateUBO(float t) + { + glm::vec3 camPos; + glm::mat4 vp = computeViewProj(t, camPos); + FrameUBO ubo{.viewProj = vp, .cameraPos = camPos, .time = t}; + memcpy(uboMapped[frameIndex], &ubo, sizeof(ubo)); + } + + // ----------------------------------------------------------------------- + // Command recording + // ----------------------------------------------------------------------- + void recordComputeCommandBuffer(float t) + { + auto &cb = computeCommandBuffers[frameIndex]; + cb.reset(); + cb.begin({}); + + // Zero the three count buffers + cb.fillBuffer(*countBuf0[frameIndex], 0, sizeof(uint32_t), 0u); + cb.fillBuffer(*countBuf1[frameIndex], 0, sizeof(uint32_t), 0u); + cb.fillBuffer(*countBuf2[frameIndex], 0, sizeof(uint32_t), 0u); + + // Barrier: fill writes must complete before compute reads counts + std::array fillBarriers{{ + {.srcStageMask=vk::PipelineStageFlagBits2::eTransfer,.srcAccessMask=vk::AccessFlagBits2::eTransferWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eComputeShader,.dstAccessMask=vk::AccessFlagBits2::eShaderRead|vk::AccessFlagBits2::eShaderWrite, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*countBuf0[frameIndex],.offset=0,.size=sizeof(uint32_t)}, + {.srcStageMask=vk::PipelineStageFlagBits2::eTransfer,.srcAccessMask=vk::AccessFlagBits2::eTransferWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eComputeShader,.dstAccessMask=vk::AccessFlagBits2::eShaderRead|vk::AccessFlagBits2::eShaderWrite, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*countBuf1[frameIndex],.offset=0,.size=sizeof(uint32_t)}, + {.srcStageMask=vk::PipelineStageFlagBits2::eTransfer,.srcAccessMask=vk::AccessFlagBits2::eTransferWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eComputeShader,.dstAccessMask=vk::AccessFlagBits2::eShaderRead|vk::AccessFlagBits2::eShaderWrite, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*countBuf2[frameIndex],.offset=0,.size=sizeof(uint32_t)}, + }}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .bufferMemoryBarrierCount = static_cast(fillBarriers.size()), + .pBufferMemoryBarriers = fillBarriers.data()}); + + // Bind compute pipeline + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *computePipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, *computePipeLayout, 0, {*computeDescSets[frameIndex]}, {}); + + // Build push constants with current VP matrix and camera pos + glm::vec3 camPos; + CullPush push{ + .viewProj = computeViewProj(t, camPos), + .cameraPos = camPos, + .time = t, + .asteroidCount = kAsteroidCount, + .lodDist0 = kLodDist0, + .lodDist1 = kLodDist1, + .pad = 0.0f}; + cb.pushConstants(*computePipeLayout, vk::ShaderStageFlagBits::eCompute, 0, push); + + // Dispatch: 1024 asteroids / 256 threads per workgroup = 4 groups + cb.dispatch(kAsteroidCount / 256, 1, 1); + + // Barrier: compute writes to indirect + count buffers must be visible to DrawIndirect stage + std::array postBarriers{{ + // indirect buffers + {.srcStageMask=vk::PipelineStageFlagBits2::eComputeShader,.srcAccessMask=vk::AccessFlagBits2::eShaderWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eDrawIndirect,.dstAccessMask=vk::AccessFlagBits2::eIndirectCommandRead, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*indirectBuf0[frameIndex],.offset=0,.size=sizeof(VkDrawIndexedIndirectCommand)*kAsteroidCount}, + {.srcStageMask=vk::PipelineStageFlagBits2::eComputeShader,.srcAccessMask=vk::AccessFlagBits2::eShaderWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eDrawIndirect,.dstAccessMask=vk::AccessFlagBits2::eIndirectCommandRead, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*indirectBuf1[frameIndex],.offset=0,.size=sizeof(VkDrawIndexedIndirectCommand)*kAsteroidCount}, + {.srcStageMask=vk::PipelineStageFlagBits2::eComputeShader,.srcAccessMask=vk::AccessFlagBits2::eShaderWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eDrawIndirect,.dstAccessMask=vk::AccessFlagBits2::eIndirectCommandRead, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*indirectBuf2[frameIndex],.offset=0,.size=sizeof(VkDrawIndexedIndirectCommand)*kAsteroidCount}, + // count buffers + {.srcStageMask=vk::PipelineStageFlagBits2::eComputeShader,.srcAccessMask=vk::AccessFlagBits2::eShaderWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eDrawIndirect,.dstAccessMask=vk::AccessFlagBits2::eIndirectCommandRead, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*countBuf0[frameIndex],.offset=0,.size=sizeof(uint32_t)}, + {.srcStageMask=vk::PipelineStageFlagBits2::eComputeShader,.srcAccessMask=vk::AccessFlagBits2::eShaderWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eDrawIndirect,.dstAccessMask=vk::AccessFlagBits2::eIndirectCommandRead, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*countBuf1[frameIndex],.offset=0,.size=sizeof(uint32_t)}, + {.srcStageMask=vk::PipelineStageFlagBits2::eComputeShader,.srcAccessMask=vk::AccessFlagBits2::eShaderWrite, + .dstStageMask=vk::PipelineStageFlagBits2::eDrawIndirect,.dstAccessMask=vk::AccessFlagBits2::eIndirectCommandRead, + .srcQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED,.dstQueueFamilyIndex=VK_QUEUE_FAMILY_IGNORED, + .buffer=*countBuf2[frameIndex],.offset=0,.size=sizeof(uint32_t)}, + }}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .bufferMemoryBarrierCount = static_cast(postBarriers.size()), + .pBufferMemoryBarriers = postBarriers.data()}); + + cb.end(); + } + + void recordCommandBuffer(uint32_t imageIndex) + { + auto &cb = commandBuffers[frameIndex]; + cb.reset(); + cb.begin({}); + + // Transition color image + transitionImage(cb, swapChainImages[imageIndex], + vk::ImageLayout::eUndefined, vk::ImageLayout::eColorAttachmentOptimal, + {}, vk::AccessFlagBits2::eColorAttachmentWrite, + vk::PipelineStageFlagBits2::eTopOfPipe, vk::PipelineStageFlagBits2::eColorAttachmentOutput, + vk::ImageAspectFlagBits::eColor); + + // Transition depth image + transitionImage(cb, *depthImage, + vk::ImageLayout::eUndefined, vk::ImageLayout::eDepthStencilAttachmentOptimal, + {}, vk::AccessFlagBits2::eDepthStencilAttachmentWrite, + vk::PipelineStageFlagBits2::eTopOfPipe, vk::PipelineStageFlagBits2::eEarlyFragmentTests, + vk::ImageAspectFlagBits::eDepth); + + // Begin dynamic rendering + vk::ClearValue clearColor = vk::ClearColorValue(0.02f, 0.02f, 0.05f, 1.0f); + vk::ClearValue clearDepth = vk::ClearDepthStencilValue(1.0f, 0); + + vk::RenderingAttachmentInfo colorAtt{ + .imageView = *swapChainImageViews[imageIndex], + .imageLayout = vk::ImageLayout::eColorAttachmentOptimal, + .loadOp = vk::AttachmentLoadOp::eClear, + .storeOp = vk::AttachmentStoreOp::eStore, + .clearValue = clearColor}; + vk::RenderingAttachmentInfo depthAtt{ + .imageView = *depthImageView, + .imageLayout = vk::ImageLayout::eDepthStencilAttachmentOptimal, + .loadOp = vk::AttachmentLoadOp::eClear, + .storeOp = vk::AttachmentStoreOp::eDontCare, + .clearValue = clearDepth}; + vk::RenderingInfo ri{ + .renderArea = {.offset={0,0}, .extent=swapChainExtent}, + .layerCount = 1, + .colorAttachmentCount = 1, + .pColorAttachments = &colorAtt, + .pDepthAttachment = &depthAtt}; + + cb.beginRendering(ri); + cb.bindPipeline(vk::PipelineBindPoint::eGraphics, *graphicsPipeline); + cb.setViewport(0, vk::Viewport(0.f, 0.f, + static_cast(swapChainExtent.width), static_cast(swapChainExtent.height), + 0.f, 1.f)); + cb.setScissor(0, vk::Rect2D({0,0}, swapChainExtent)); + // Bind set 0 (compute layout) and set 1 (graphics layout) + cb.bindDescriptorSets(vk::PipelineBindPoint::eGraphics, *graphicsPipeLayout, 0, + {*computeDescSets[frameIndex], *graphicsDescSets[frameIndex]}, {}); + + // LOD 0 draw (icosphere) + cb.bindVertexBuffers(0, {*lodVB0}, {vk::DeviceSize(0)}); + cb.bindIndexBuffer(*lodIB0, 0, vk::IndexType::eUint32); + cb.drawIndexedIndirectCount( + *indirectBuf0[frameIndex], 0, + *countBuf0[frameIndex], 0, + kAsteroidCount, sizeof(VkDrawIndexedIndirectCommand)); + + // LOD 1 draw (icosahedron) + cb.bindVertexBuffers(0, {*lodVB1}, {vk::DeviceSize(0)}); + cb.bindIndexBuffer(*lodIB1, 0, vk::IndexType::eUint32); + cb.drawIndexedIndirectCount( + *indirectBuf1[frameIndex], 0, + *countBuf1[frameIndex], 0, + kAsteroidCount, sizeof(VkDrawIndexedIndirectCommand)); + + // LOD 2 draw (octahedron) + cb.bindVertexBuffers(0, {*lodVB2}, {vk::DeviceSize(0)}); + cb.bindIndexBuffer(*lodIB2, 0, vk::IndexType::eUint32); + cb.drawIndexedIndirectCount( + *indirectBuf2[frameIndex], 0, + *countBuf2[frameIndex], 0, + kAsteroidCount, sizeof(VkDrawIndexedIndirectCommand)); + + cb.endRendering(); + + // Transition color image to present + transitionImage(cb, swapChainImages[imageIndex], + vk::ImageLayout::eColorAttachmentOptimal, vk::ImageLayout::ePresentSrcKHR, + vk::AccessFlagBits2::eColorAttachmentWrite, {}, + vk::PipelineStageFlagBits2::eColorAttachmentOutput, vk::PipelineStageFlagBits2::eBottomOfPipe, + vk::ImageAspectFlagBits::eColor); + + cb.end(); + } + + static void transitionImage( + const vk::raii::CommandBuffer &cb, + vk::Image image, + vk::ImageLayout oldLayout, + vk::ImageLayout newLayout, + vk::AccessFlags2 srcAccess, + vk::AccessFlags2 dstAccess, + vk::PipelineStageFlags2 srcStage, + vk::PipelineStageFlags2 dstStage, + vk::ImageAspectFlags aspect) + { + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = srcStage, + .srcAccessMask = srcAccess, + .dstStageMask = dstStage, + .dstAccessMask = dstAccess, + .oldLayout = oldLayout, + .newLayout = newLayout, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = image, + .subresourceRange = {aspect, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{.imageMemoryBarrierCount=1, .pImageMemoryBarriers=&barrier}); + } + + // ----------------------------------------------------------------------- + // Sync objects + // ----------------------------------------------------------------------- + void createSyncObjects() + { + vk::SemaphoreTypeCreateInfo timelineType{ + .semaphoreType = vk::SemaphoreType::eTimeline, .initialValue = 0}; + timelineSema = vk::raii::Semaphore(device, {.pNext = &timelineType}); + timelineValue = 0; + + for (int i = 0; i < kAcquireSemas; ++i) + acquireSemas.emplace_back(device, vk::SemaphoreCreateInfo{}); + + // One renderDone binary semaphore per swapchain image + for (size_t i = 0; i < swapChainImages.size(); ++i) + renderDoneSemas.emplace_back(device, vk::SemaphoreCreateInfo{}); + } + + // ----------------------------------------------------------------------- + // Draw frame + // ----------------------------------------------------------------------- + void drawFrame() + { + float t = elapsedSeconds(); + updateUBO(t); + + // Acquire next swapchain image using a rotating acquire semaphore + auto &acquireSema = acquireSemas[acquireSemaIdx]; + acquireSemaIdx = (acquireSemaIdx + 1) % kAcquireSemas; + + auto [result, imageIndex] = swapChain.acquireNextImage(UINT64_MAX, *acquireSema, nullptr); + if (result == vk::Result::eErrorOutOfDateKHR) + { + recreateSwapChain(); + return; + } + + auto &renderDone = renderDoneSemas[imageIndex]; + + // Timeline values for this frame + uint64_t computeWait = timelineValue; + uint64_t computeSignal = ++timelineValue; + uint64_t graphicsWait = computeSignal; + uint64_t graphicsSignal = ++timelineValue; + + // ---- Compute pass ---- + recordComputeCommandBuffer(t); + { + vk::TimelineSemaphoreSubmitInfo tsi{ + .waitSemaphoreValueCount = 1, + .pWaitSemaphoreValues = &computeWait, + .signalSemaphoreValueCount = 1, + .pSignalSemaphoreValues = &computeSignal}; + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eComputeShader; + vk::SubmitInfo si{ + .pNext = &tsi, + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*timelineSema, + .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*computeCommandBuffers[frameIndex], + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*timelineSema}; + queue.submit(si, nullptr); + } + + // ---- Graphics pass ---- + recordCommandBuffer(imageIndex); + { + // Wait on: timeline semaphore (compute done) + acquire semaphore (image ready) + std::array waitSemas = {*timelineSema, *acquireSema}; + std::array waitVals = {graphicsWait, 0}; // 0 = binary sema ignores value + std::array waitStages = { + vk::PipelineStageFlagBits::eDrawIndirect, + vk::PipelineStageFlagBits::eColorAttachmentOutput}; + + // Signal: timeline (for next frame ordering) + binary renderDone (for present) + std::array signalSemas = {*timelineSema, *renderDone}; + std::array signalVals = {graphicsSignal, 0}; + + vk::TimelineSemaphoreSubmitInfo tsi{ + .waitSemaphoreValueCount = static_cast(waitVals.size()), + .pWaitSemaphoreValues = waitVals.data(), + .signalSemaphoreValueCount = static_cast(signalVals.size()), + .pSignalSemaphoreValues = signalVals.data()}; + vk::SubmitInfo si{ + .pNext = &tsi, + .waitSemaphoreCount = static_cast(waitSemas.size()), + .pWaitSemaphores = waitSemas.data(), + .pWaitDstStageMask = waitStages.data(), + .commandBufferCount = 1, + .pCommandBuffers = &*commandBuffers[frameIndex], + .signalSemaphoreCount = static_cast(signalSemas.size()), + .pSignalSemaphores = signalSemas.data()}; + queue.submit(si, nullptr); + + // CPU waits for graphics timeline value so per-frame resources are safe to reuse + vk::SemaphoreWaitInfo swi{ + .semaphoreCount = 1, + .pSemaphores = &*timelineSema, + .pValues = &graphicsSignal}; + if (device.waitSemaphores(swi, UINT64_MAX) != vk::Result::eSuccess) + throw std::runtime_error("semaphore wait failed"); + + // Present using the binary renderDone semaphore + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*renderDone, + .swapchainCount = 1, + .pSwapchains = &*swapChain, + .pImageIndices = &imageIndex}; + auto pr = queue.presentKHR(pi); + if (pr == vk::Result::eSuboptimalKHR || pr == vk::Result::eErrorOutOfDateKHR || framebufferResized) + { + framebufferResized = false; + recreateSwapChain(); + } + } + + frameIndex = (frameIndex + 1) % kMaxFrames; + } + + // ----------------------------------------------------------------------- + // Buffer helpers + // ----------------------------------------------------------------------- + void createBuffer(vk::DeviceSize size, vk::BufferUsageFlags usage, vk::MemoryPropertyFlags props, + vk::raii::Buffer &buf, vk::raii::DeviceMemory &mem) const + { + vk::BufferCreateInfo bci{.size = size, .usage = usage, .sharingMode = vk::SharingMode::eExclusive}; + buf = vk::raii::Buffer(device, bci); + auto req = buf.getMemoryRequirements(); + vk::MemoryAllocateInfo ai{.allocationSize = req.size, .memoryTypeIndex = findMemoryType(req.memoryTypeBits, props)}; + mem = vk::raii::DeviceMemory(device, ai); + buf.bindMemory(mem, 0); + } + + [[nodiscard]] vk::raii::CommandBuffer beginOneShot() const + { + vk::CommandBufferAllocateInfo ai{.commandPool=*commandPool,.level=vk::CommandBufferLevel::ePrimary,.commandBufferCount=1}; + auto cb = std::move(vk::raii::CommandBuffers(device, ai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + return cb; + } + + void endOneShot(const vk::raii::CommandBuffer &cb) const + { + cb.end(); + vk::SubmitInfo si{.commandBufferCount=1,.pCommandBuffers=&*cb}; + queue.submit(si, nullptr); + queue.waitIdle(); + } + + void copyBuffer(const vk::raii::Buffer &src, const vk::raii::Buffer &dst, vk::DeviceSize size) const + { + auto cb = beginOneShot(); + cb.copyBuffer(src, dst, vk::BufferCopy(0, 0, size)); + endOneShot(cb); + } + + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, vk::MemoryPropertyFlags props) const + { + auto mp = physicalDevice.getMemoryProperties(); + for (uint32_t i = 0; i < mp.memoryTypeCount; ++i) + if ((filter & (1u << i)) && (mp.memoryTypes[i].propertyFlags & props) == props) + return i; + throw std::runtime_error("no suitable memory type"); + } + + [[nodiscard]] vk::raii::ShaderModule createShaderModule(const std::vector &code) const + { + vk::ShaderModuleCreateInfo ci{.codeSize=code.size(),.pCode=reinterpret_cast(code.data())}; + return vk::raii::ShaderModule(device, ci); + } + + // ----------------------------------------------------------------------- + // Swapchain helpers + // ----------------------------------------------------------------------- + vk::Extent2D chooseExtent(const vk::SurfaceCapabilitiesKHR &caps) + { + if (caps.currentExtent.width != std::numeric_limits::max()) + return caps.currentExtent; + int w, h; + glfwGetFramebufferSize(window, &w, &h); + return { + std::clamp(w, caps.minImageExtent.width, caps.maxImageExtent.width), + std::clamp(h, caps.minImageExtent.height, caps.maxImageExtent.height)}; + } + + static vk::SurfaceFormatKHR chooseFormat(const std::vector &formats) + { + assert(!formats.empty()); + for (auto &f : formats) + if (f.format == vk::Format::eB8G8R8A8Srgb && f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + return formats[0]; + } + + static vk::PresentModeKHR choosePresentMode(const std::vector &modes) + { + for (auto m : modes) if (m == vk::PresentModeKHR::eMailbox) return m; + return vk::PresentModeKHR::eFifo; + } + + [[nodiscard]] std::vector getRequiredInstanceExtensions() const + { + uint32_t cnt = 0; + auto ext = glfwGetRequiredInstanceExtensions(&cnt); + std::vector exts(ext, ext + cnt); + if (kEnableValidation) exts.push_back(vk::EXTDebugUtilsExtensionName); + return exts; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + const vk::DebugUtilsMessengerCallbackDataEXT *data, + void *) + { + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "VK [" << to_string(type) << "]: " << data->pMessage << "\n"; + return vk::False; + } + + static std::vector readFile(const std::string &path) + { + std::ifstream f(path, std::ios::ate | std::ios::binary); + if (!f.is_open()) throw std::runtime_error("cannot open: " + path); + std::vector buf(f.tellg()); + f.seekg(0); f.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +int main() +{ + try { AsteroidFieldApp{}.run(); } + catch (const std::exception &e) { std::cerr << e.what() << "\n"; return EXIT_FAILURE; } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/07_gpu_driven_pipelines.slang b/attachments/compute/07_gpu_driven_pipelines.slang new file mode 100644 index 00000000..e221d551 --- /dev/null +++ b/attachments/compute/07_gpu_driven_pipelines.slang @@ -0,0 +1,315 @@ +// Chapter 7 – GPU-Driven Pipelines: LOD Asteroid Field +// Three entry points: +// cullMain – compute: frustum-cull 1024 asteroids, LOD-select, write per-LOD indirect draw commands +// vertMain – vertex: transform LOD mesh vertex by per-instance asteroid data (pos/rot/size) +// fragMain – fragment: Phong shading with a distant sun + +// --------------------------------------------------------------------------- +// Shared GPU structures (CPU layout in 07_gpu_driven_pipelines.cpp must match) +// --------------------------------------------------------------------------- + +// One asteroid instance – uploaded once from CPU, never modified on GPU. +struct Asteroid +{ + float3 position; // world-space centre of the asteroid + float size; // radius scale (0.5 – 2.0 units) + float3 rotAxis; // normalised rotation axis + float orbitSpeed; // radians/second orbit around Y + float3 color; // grey + slight tint + float rotSpeed; // radians/second self-rotation +}; + +// Matches VkDrawIndexedIndirectCommand exactly. +struct DrawCommand +{ + uint indexCount; + uint instanceCount; + uint firstIndex; + int vertexOffset; + uint firstInstance; // stores asteroid index → vertex shader looks up Asteroid[firstInstance] +}; + +// Push constants for the cull compute pass. +struct CullPush +{ + float4x4 viewProj; // view-projection matrix + float3 cameraPos; + float time; // elapsed seconds (for orbit/spin animation) + uint asteroidCount; // total number of asteroids (1024) + float lodDist0; // distance threshold LOD0→LOD1 + float lodDist1; // distance threshold LOD1→LOD2 + float _pad; +}; + +// Per-frame UBO read by the vertex shader. +struct FrameUBO +{ + float4x4 viewProj; + float3 cameraPos; + float time; +}; + +// --------------------------------------------------------------------------- +// Compute bindings (set 0) +// --------------------------------------------------------------------------- +[[vk::binding(0, 0)]] StructuredBuffer asteroids; +[[vk::binding(1, 0)]] RWStructuredBuffer drawCmds0; // LOD 0 commands +[[vk::binding(2, 0)]] RWStructuredBuffer drawCmds1; // LOD 1 commands +[[vk::binding(3, 0)]] RWStructuredBuffer drawCmds2; // LOD 2 commands +[[vk::binding(4, 0)]] RWStructuredBuffer drawCount0; // LOD 0 atomic counter +[[vk::binding(5, 0)]] RWStructuredBuffer drawCount1; // LOD 1 atomic counter +[[vk::binding(6, 0)]] RWStructuredBuffer drawCount2; // LOD 2 atomic counter + +[[vk::push_constant]] CullPush cullPush; + +// --------------------------------------------------------------------------- +// Compute: frustum cull + LOD selection +// --------------------------------------------------------------------------- + +// Extract the 6 frustum planes (Gribb–Hartmann) from a view-projection matrix. +// Returns planes as float4(normal.xyz, d); dot(p, normal) + d >= 0 means inside. +// +// IMPORTANT — matrix-layout consistency with the vertex shader: +// The vertex shader transforms vertices with `mul(viewProj, float4(pos,1))`, +// and that render is correct. In Slang, `mul(M, v)` computes result[i] = +// dot(row i of M, v), and indexing `M[i]` returns that SAME logical row i. +// So the Gribb–Hartmann planes — which are built from the ROWS of VP — must +// use `vp[i]` directly. The previous version instead assembled COLUMNS +// (vp[0][0], vp[1][0], …), i.e. the transpose of VP, which produced a bogus +// frustum: asteroids survived culling only in a thin mis-oriented slab, +// bunched into one corner of the screen. Using the rows fixes the field. +// +// Planes are normalised so the sphere test `dist < -radius` uses true +// world-space distances regardless of the matrix's overall scale. +void extractFrustumPlanes(float4x4 vp, out float4 planes[6]) +{ + float4 r0 = vp[0]; // row 0 of VP + float4 r1 = vp[1]; // row 1 + float4 r2 = vp[2]; // row 2 + float4 r3 = vp[3]; // row 3 (w-row) + + float4 raw[6]; + raw[0] = r3 + r0; // left + raw[1] = r3 - r0; // right + raw[2] = r3 + r1; // bottom + raw[3] = r3 - r1; // top + raw[4] = r2; // near (Vulkan [0,1] depth) + raw[5] = r3 - r2; // far + + for (int i = 0; i < 6; ++i) + { + float len = length(raw[i].xyz); + planes[i] = (len > 1e-8f) ? raw[i] / len : raw[i]; + } +} + +// Sphere-frustum test. Returns true if the sphere is (potentially) visible. +bool sphereInFrustum(float4 planes[6], float3 centre, float radius) +{ + for (int i = 0; i < 6; ++i) + { + float dist = dot(planes[i].xyz, centre) + planes[i].w; + if (dist < -radius) + return false; + } + return true; +} + +// Animate an asteroid's world-space position given the elapsed time. +float3 animatedPosition(Asteroid a, float t) +{ + // Orbit around Y-axis at orbitSpeed + float angle = a.orbitSpeed * t; + float ca = cos(angle), sa = sin(angle); + float3 p = a.position; + return float3(p.x * ca - p.z * sa, p.y, p.x * sa + p.z * ca); +} + +[shader("compute")] +[numthreads(256, 1, 1)] +void cullMain(uint3 threadId : SV_DispatchThreadID) +{ + uint idx = threadId.x; + if (idx >= cullPush.asteroidCount) + return; + + Asteroid a = asteroids[idx]; + + // Animated world position + float3 worldPos = animatedPosition(a, cullPush.time); + + // Frustum cull using a bounding sphere of radius = size * 1.5 (generous for jagged meshes) + float4 planes[6]; + extractFrustumPlanes(cullPush.viewProj, planes); + float cullRadius = a.size * 1.5f; + if (!sphereInFrustum(planes, worldPos, cullRadius)) + return; + + // LOD selection based on camera distance + float dist = length(worldPos - cullPush.cameraPos); + uint lod = 2u; + if (dist < cullPush.lodDist0) + lod = 0u; + else if (dist < cullPush.lodDist1) + lod = 1u; + + // Write an indirect draw command for the chosen LOD + DrawCommand cmd; + cmd.instanceCount = 1u; + cmd.firstIndex = 0u; + cmd.vertexOffset = 0; + cmd.firstInstance = idx; // vertex shader uses this to look up Asteroid data + + if (lod == 0u) + { + cmd.indexCount = 144u; // 48-tri icosphere: 48 * 3 + uint slot; + InterlockedAdd(drawCount0[0], 1u, slot); + drawCmds0[slot] = cmd; + } + else if (lod == 1u) + { + cmd.indexCount = 60u; // 20-tri icosahedron: 20 * 3 + uint slot; + InterlockedAdd(drawCount1[0], 1u, slot); + drawCmds1[slot] = cmd; + } + else + { + cmd.indexCount = 24u; // 8-tri octahedron: 8 * 3 + uint slot; + InterlockedAdd(drawCount2[0], 1u, slot); + drawCmds2[slot] = cmd; + } +} + +// --------------------------------------------------------------------------- +// Graphics bindings (set 1 — graphicsDescLayout; set 0 is computeDescLayout) +// The graphics pipeline layout declares both set 0 (compute layout, unused by +// vertex/fragment shaders) and set 1 (graphics layout) so there is no overlap +// between the compute-only bindings (set 0, bindings 0-6) and these. +// --------------------------------------------------------------------------- +[[vk::binding(0, 1)]] StructuredBuffer gfxAsteroids; +[[vk::binding(1, 1)]] ConstantBuffer frameUBO; + +// --------------------------------------------------------------------------- +// Vertex shader +// --------------------------------------------------------------------------- + +struct VSIn +{ + float3 pos : POSITION; + float3 normal : NORMAL; +}; + +struct VSOut +{ + float4 sv_pos : SV_Position; + float3 worldPos : TEXCOORD0; + float3 normal : TEXCOORD1; + float3 color : TEXCOORD2; +}; + +// Build a rotation matrix from axis-angle. +float3x3 axisAngleRotation(float3 axis, float angle) +{ + float c = cos(angle); + float s = sin(angle); + float t = 1.0f - c; + float x = axis.x, y = axis.y, z = axis.z; + return float3x3( + t*x*x + c, t*x*y - s*z, t*x*z + s*y, + t*x*y + s*z, t*y*y + c, t*y*z - s*x, + t*x*z - s*y, t*y*z + s*x, t*z*z + c + ); +} + +// Animate an asteroid's world-space position (same logic as compute side). +float3 animatedPositionV(Asteroid a, float t) +{ + float angle = a.orbitSpeed * t; + float ca = cos(angle), sa = sin(angle); + float3 p = a.position; + return float3(p.x * ca - p.z * sa, p.y, p.x * sa + p.z * ca); +} + +[shader("vertex")] +VSOut vertMain(VSIn vsIn, + uint iid : SV_InstanceID, + uint base : SV_StartInstanceLocation) +{ + // SV_InstanceID = gl_InstanceIndex - gl_BaseInstance (always 0 when instanceCount=1). + // SV_StartInstanceLocation = gl_BaseInstance = firstInstance = asteroid index. + // Together they reconstruct gl_InstanceIndex, which is the correct asteroid index. + uint instanceIndex = iid + base; + Asteroid a = gfxAsteroids[instanceIndex]; + + float t = frameUBO.time; + + // Self-rotation angle + float spinAngle = a.rotSpeed * t; + float3x3 spin = axisAngleRotation(normalize(a.rotAxis), spinAngle); + + // Orbit rotation (around Y-axis) + float orbitAngle = a.orbitSpeed * t; + float ca = cos(orbitAngle), sa = sin(orbitAngle); + float3x3 orbit = float3x3( + ca, 0, sa, + 0, 1, 0, + -sa, 0, ca + ); + + // Transform mesh vertex: scale → spin → orbit → translate + float3 localPos = vsIn.pos * a.size; + float3 rotatedPos = mul(orbit, mul(spin, localPos)); + float3 worldPos = rotatedPos + a.position; // orbit of base position (pre-computed on CPU side) + // Re-apply the orbit to the stored (disk) position + float3 baseOrbit = float3(a.position.x * ca - a.position.z * sa, + a.position.y, + a.position.x * sa + a.position.z * ca); + worldPos = mul(orbit, mul(spin, localPos)) + baseOrbit; + + float3 worldNormal = normalize(mul(orbit, mul(spin, vsIn.normal))); + + VSOut o; + o.sv_pos = mul(frameUBO.viewProj, float4(worldPos, 1.0f)); + o.worldPos = worldPos; + o.normal = worldNormal; + o.color = a.color; + return o; +} + +// --------------------------------------------------------------------------- +// Fragment shader – Phong shading +// --------------------------------------------------------------------------- + +struct PSIn +{ + float3 worldPos : TEXCOORD0; + float3 normal : TEXCOORD1; + float3 color : TEXCOORD2; +}; + +[shader("fragment")] +float4 fragMain(PSIn psIn) : SV_Target +{ + // Distant sun direction (fixed, from upper-right-front) + float3 sunDir = normalize(float3(0.6f, 0.8f, 0.3f)); + float3 N = normalize(psIn.normal); + + // Diffuse + float NdotL = max(dot(N, sunDir), 0.0f); + float3 diffuse = psIn.color * NdotL; + + // Ambient + float3 ambient = psIn.color * 0.15f; + + // Specular (Blinn-Phong) + float3 viewDir = normalize(frameUBO.cameraPos - psIn.worldPos); + float3 halfDir = normalize(sunDir + viewDir); + float spec = pow(max(dot(N, halfDir), 0.0f), 32.0f); + float3 specular = float3(0.4f, 0.38f, 0.35f) * spec; + + float3 finalColor = ambient + diffuse + specular; + return float4(finalColor, 1.0f); +} diff --git a/attachments/compute/08_async_compute.cpp b/attachments/compute/08_async_compute.cpp new file mode 100644 index 00000000..d0790bb1 --- /dev/null +++ b/attachments/compute/08_async_compute.cpp @@ -0,0 +1,1787 @@ +// Chapter 8 – Asynchronous Compute: Cloth Physics Simulation +// +// Demonstrates true asynchronous compute using two separate Vulkan queues: +// +// - A DEDICATED ASYNC COMPUTE QUEUE runs cloth Verlet integration and spring- +// constraint solving (8 Jacobi iterations per frame). A compute-only queue +// family is preferred; the code falls back to a second queue from the +// graphics family, or to sharing queue 0 if only one queue is available. +// +// - The GRAPHICS QUEUE renders a 64×64 cloth mesh as a lit triangle mesh +// plus a collision sphere, reading the vertex positions written by the +// compute pass of the *previous* frame. This is the key overlap: while +// the GPU renders frame N it simultaneously solves physics for frame N+1. +// +// - A TIMELINE SEMAPHORE with monotonically increasing values coordinates +// the two queues so that graphics never reads cloth positions while +// compute is still writing them. +// +// Frame N timeline: +// compute : wait N*2+0 (initial value == 0, so frame 0 proceeds immediately) +// → Verlet integrate + 8 constraint iterations +// → signal N*2+1 +// graphics: wait N*2+1 (eVertexInput stage) +// → render cloth mesh + sphere +// → signal N*2+2 +// CPU : wait N*2+2 → present +// +// The cloth: +// • 64×64 grid of vertices (4096 total), pinned at top-left and top-right. +// • Falls under gravity and drapes over a sphere at (0, -0.2, 0). +// • Rendered as an indexed triangle list; indices are generated once on the CPU. +// • Cloth positions live in two device-local SSBOs (positions + prevPositions). +// • UV coordinates for the checker-board texture are in a separate vertex buffer. +// +// Build: see CMakeLists.txt – add_compute_chapter(08_async_compute WINDOWED …) +// Shader: shaders/slang.spv (compiled from 08_async_compute.slang) + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +#define GLM_FORCE_RADIANS +#define GLM_FORCE_DEPTH_ZERO_TO_ONE +#include +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t WIDTH = 1280; +constexpr uint32_t HEIGHT = 720; +// Cloth is 32×32 = 1024 vertices so the entire grid fits in ONE compute +// workgroup (maxComputeWorkGroupInvocations is guaranteed ≥ 1024 across all +// Vulkan 1.1 devices). That lets the constraint solver use a real +// workgroup-wide barrier between relaxation steps – see the shader header. +constexpr uint32_t CLOTH_W = 32; +constexpr uint32_t CLOTH_H = 32; +constexpr uint32_t CLOTH_N = CLOTH_W * CLOTH_H; // 1024 +constexpr uint32_t CLOTH_TRIS = (CLOTH_W - 1) * (CLOTH_H - 1) * 2; +constexpr uint32_t CLOTH_INDICES = CLOTH_TRIS * 3; +constexpr uint32_t CONSTRAINT_ITER = 24; +constexpr int MAX_FRAMES = 2; + +// Sphere rendered via a separate indexed draw (icosphere approximation is +// replaced here with a simple pre-tessellated sphere built on the CPU). +constexpr uint32_t SPHERE_RINGS = 24; +constexpr uint32_t SPHERE_SEGS = 32; + +// Sphere collision/animation: the sphere mesh is baked centred at y = SPHERE_BASE_Y +// and translated each frame to sphereCentreY(t). The same curve drives both the +// physics (compute) and the rendered sphere so they stay locked together. +constexpr float SPHERE_BASE_Y = 0.3f; +constexpr float SPHERE_RADIUS = 0.55f; +inline float sphereCentreY(float t) { return 0.3f + 0.6f * std::sin(t * 0.6f); } + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// CPU-side data structures +// --------------------------------------------------------------------------- + +// Matches ClothUBO in the shader (std140: 8 floats = 32 bytes) +struct ClothUBO +{ + float deltaTime = 0.016f; + uint32_t iterCount = CONSTRAINT_ITER; + float time = 0.0f; + float pad = 0.0f; + glm::vec3 sphereCenter = {0.0f, 0.3f, 0.0f}; + float sphereRadius = 0.55f; +}; + +// Matches ClothPush in the shader (two float4x4 + one float4) +struct ClothPush +{ + glm::mat4 mvp; + glm::mat4 normalMatrix; + glm::vec4 lightDir; // xyz = light direction, w = renderSphere flag +}; + +// Vertex for cloth: position SSBO is used directly; UV is a separate vertex +// buffer so the layout matches [[vk::location(0)]] float4 and [[vk::location(1)]] float2. +struct ClothUV +{ + glm::vec2 uv; +}; + +// Sphere vertex (position only – normals computed in fragment via derivatives) +struct SphereVertex +{ + glm::vec3 position; +}; + +// --------------------------------------------------------------------------- +// Utility: build sphere geometry +// --------------------------------------------------------------------------- +static void buildSphere(float radius, glm::vec3 centre, + std::vector &verts, + std::vector &inds) +{ + verts.clear(); + inds.clear(); + + for (uint32_t r = 0; r <= SPHERE_RINGS; ++r) + { + float phi = glm::pi() * float(r) / float(SPHERE_RINGS); + for (uint32_t s = 0; s <= SPHERE_SEGS; ++s) + { + float theta = 2.0f * glm::pi() * float(s) / float(SPHERE_SEGS); + glm::vec3 p{ + radius * std::sin(phi) * std::cos(theta), + radius * std::cos(phi), + radius * std::sin(phi) * std::sin(theta)}; + verts.push_back({centre + p}); + } + } + + for (uint32_t r = 0; r < SPHERE_RINGS; ++r) + { + for (uint32_t s = 0; s < SPHERE_SEGS; ++s) + { + uint32_t a = r * (SPHERE_SEGS + 1) + s; + uint32_t b = a + 1; + uint32_t c = a + (SPHERE_SEGS + 1); + uint32_t d = c + 1; + inds.push_back(a); inds.push_back(c); inds.push_back(b); + inds.push_back(b); inds.push_back(c); inds.push_back(d); + } + } +} + +// =========================================================================== +// Application class +// =========================================================================== +class AsyncComputeApplication +{ + public: + void run() + { + initWindow(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + // ----------------------------------------------------------------------- + // GLFW / Vulkan core objects + // ----------------------------------------------------------------------- + GLFWwindow *window = nullptr; + vk::raii::Context context; + vk::raii::Instance instance = nullptr; + vk::raii::DebugUtilsMessengerEXT debugMessenger = nullptr; + vk::raii::SurfaceKHR surface = nullptr; + vk::raii::PhysicalDevice physicalDevice = nullptr; + vk::raii::Device device = nullptr; + + // ----------------------------------------------------------------------- + // Two queues: graphics+present and async compute. + // asyncComputeQueueFamily may equal graphicsQueueFamily when the device + // has no dedicated compute-only family. + // ----------------------------------------------------------------------- + uint32_t graphicsQueueFamily = ~0u; + uint32_t asyncComputeQueueFamily = ~0u; + vk::raii::Queue graphicsQueue = nullptr; + vk::raii::Queue asyncComputeQueue = nullptr; + + // ----------------------------------------------------------------------- + // Swapchain + // ----------------------------------------------------------------------- + vk::raii::SwapchainKHR swapChain = nullptr; + std::vector swapChainImages; + vk::SurfaceFormatKHR swapChainSurfaceFormat; + vk::Extent2D swapChainExtent; + std::vector swapChainImageViews; + + // ----------------------------------------------------------------------- + // Depth buffer (memory first so RAII destroys buffer/image before freeing memory) + // ----------------------------------------------------------------------- + vk::raii::DeviceMemory depthImageMemory = nullptr; + vk::raii::Image depthImage = nullptr; + vk::raii::ImageView depthImageView = nullptr; + vk::Format depthFormat = vk::Format::eD32Sfloat; + + // ----------------------------------------------------------------------- + // Pipelines + // ----------------------------------------------------------------------- + // Compute pipeline (cloth physics) + vk::raii::DescriptorSetLayout computeDescriptorSetLayout = nullptr; + vk::raii::PipelineLayout computePipelineLayout = nullptr; + vk::raii::Pipeline computePipeline = nullptr; + + // Graphics pipeline (cloth + sphere, push-constant driven) + vk::raii::PipelineLayout graphicsPipelineLayout = nullptr; + vk::raii::Pipeline clothPipeline = nullptr; + vk::raii::Pipeline spherePipeline = nullptr; + + // ----------------------------------------------------------------------- + // Cloth GPU buffers (per frame – double-buffered) + // Memory declared before buffer so RAII destroys buffer before freeing memory. + // ----------------------------------------------------------------------- + std::vector clothPositionMemory; + std::vector clothPositionBuffers; + std::vector clothPrevMemory; + std::vector clothPrevBuffers; + // Smooth per-vertex normals (written by compute, read as a vertex attribute) + std::vector clothNormalMemory; + std::vector clothNormalBuffers; + + // UV coordinates (static, uploaded once) + vk::raii::DeviceMemory clothUVMemory = nullptr; + vk::raii::Buffer clothUVBuffer = nullptr; + + // Index buffer for cloth triangle list (static) + vk::raii::DeviceMemory clothIndexMemory = nullptr; + vk::raii::Buffer clothIndexBuffer = nullptr; + + // ----------------------------------------------------------------------- + // Sphere GPU buffers (static) + // ----------------------------------------------------------------------- + vk::raii::DeviceMemory sphereVertexMemory = nullptr; + vk::raii::Buffer sphereVertexBuffer = nullptr; + vk::raii::DeviceMemory sphereIndexMemory = nullptr; + vk::raii::Buffer sphereIndexBuffer = nullptr; + vk::raii::DeviceMemory sphereNormalMemory = nullptr; + vk::raii::Buffer sphereNormalBuffer = nullptr; + uint32_t sphereIndexCount = 0; + + // ----------------------------------------------------------------------- + // Uniform buffers (compute UBO, per frame) + // ----------------------------------------------------------------------- + std::vector uniformBuffersMemory; + std::vector uniformBuffers; + std::vector uniformBuffersMapped; + + // ----------------------------------------------------------------------- + // Descriptor sets (compute, per frame) + // ----------------------------------------------------------------------- + vk::raii::DescriptorPool descriptorPool = nullptr; + std::vector computeDescSets; + + // ----------------------------------------------------------------------- + // Command pools and buffers + // ----------------------------------------------------------------------- + vk::raii::CommandPool graphicsCommandPool = nullptr; + vk::raii::CommandPool asyncComputeCommandPool = nullptr; + std::vector commandBuffers; + std::vector computeCommandBuffers; + + // ----------------------------------------------------------------------- + // Synchronisation + // + // One timeline semaphore: compute signals N*2+1, graphics waits on it, + // graphics signals N*2+2, CPU waits on it before present. + // + // Binary semaphores for image acquisition and per-image render-done use. + // ----------------------------------------------------------------------- + vk::raii::Semaphore timelineSemaphore = nullptr; + uint64_t timelineValue = 0; + std::vector acquireSemaphores; // MAX_FRAMES+1 rotating pool + std::vector renderDoneSems; // one per swapchain image + std::vector inFlightFences; // guard command-buffer reuse + + uint32_t acquireSemIdx = 0; // rotating acquire semaphore index + uint32_t frameIndex = 0; + + // ----------------------------------------------------------------------- + // Timing + // ----------------------------------------------------------------------- + double startTime = 0.0; + double lastFrameTime = 0.0; + double lastWallTime = 0.0; + bool framebufferResized = false; + + std::vector requiredDeviceExtensions = {vk::KHRSwapchainExtensionName}; + + // ======================================================================= + // Window + // ======================================================================= + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + window = glfwCreateWindow(WIDTH, HEIGHT, "Vulkan – Cloth Async Compute", nullptr, nullptr); + glfwSetWindowUserPointer(window, this); + glfwSetFramebufferSizeCallback(window, framebufferResizeCallback); + startTime = glfwGetTime(); + lastWallTime = startTime; + } + + static void framebufferResizeCallback(GLFWwindow *w, int, int) + { + static_cast(glfwGetWindowUserPointer(w))->framebufferResized = true; + } + + // ======================================================================= + // Vulkan initialisation sequence + // ======================================================================= + void initVulkan() + { + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createSwapChain(); + createImageViews(); + createDepthResources(); + createComputeDescriptorSetLayout(); + createGraphicsPipelines(); + createComputePipeline(); + createCommandPools(); + createClothBuffers(); + createSphereBuffers(); + createUniformBuffers(); + createDescriptorPool(); + createComputeDescriptorSets(); + createCommandBuffers(); + createComputeCommandBuffers(); + createSyncObjects(); + } + + // ======================================================================= + // Main loop + // ======================================================================= + void mainLoop() + { + while (!glfwWindowShouldClose(window)) + { + glfwPollEvents(); + drawFrame(); + } + device.waitIdle(); + } + + // ======================================================================= + // Cleanup helpers + // ======================================================================= + void cleanupSwapChain() + { + depthImageView = nullptr; + depthImage = nullptr; + depthImageMemory = nullptr; + swapChainImageViews.clear(); + swapChain = nullptr; + } + + void cleanup() + { + cleanupSwapChain(); + surface = nullptr; // must destroy VkSurfaceKHR before GLFW closes Wayland display + glfwDestroyWindow(window); + glfwTerminate(); + } + + void recreateSwapChain() + { + int w = 0, h = 0; + glfwGetFramebufferSize(window, &w, &h); + while (w == 0 || h == 0) + { + glfwGetFramebufferSize(window, &w, &h); + glfwWaitEvents(); + } + device.waitIdle(); + cleanupSwapChain(); + createSwapChain(); + createImageViews(); + createDepthResources(); + } + + // ======================================================================= + // Instance + // ======================================================================= + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "Cloth Async Compute", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion14}; + + std::vector requiredLayers; + if (kEnableValidation) + requiredLayers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto layerProps = context.enumerateInstanceLayerProperties(); + auto missingIt = std::ranges::find_if(requiredLayers, [&](const char *req) { + return std::ranges::none_of(layerProps, [req](auto const &lp) { + return strcmp(lp.layerName, req) == 0; + }); + }); + if (missingIt != requiredLayers.end()) + throw std::runtime_error("Required layer not supported: " + std::string(*missingIt)); + + auto requiredExtensions = getRequiredInstanceExtensions(); + + auto extProps = context.enumerateInstanceExtensionProperties(); + auto missingExt = std::ranges::find_if(requiredExtensions, [&](const char *req) { + return std::ranges::none_of(extProps, [req](auto const &ep) { + return strcmp(ep.extensionName, req) == 0; + }); + }); + if (missingExt != requiredExtensions.end()) + throw std::runtime_error("Required extension not supported: " + std::string(*missingExt)); + + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(requiredLayers.size()), + .ppEnabledLayerNames = requiredLayers.data(), + .enabledExtensionCount = static_cast(requiredExtensions.size()), + .ppEnabledExtensionNames = requiredExtensions.data()}; + instance = vk::raii::Instance(context, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) return; + vk::DebugUtilsMessageSeverityFlagsEXT sev( + vk::DebugUtilsMessageSeverityFlagBitsEXT::eVerbose | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError); + vk::DebugUtilsMessageTypeFlagsEXT typ( + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation); + debugMessenger = instance.createDebugUtilsMessengerEXT( + {.messageSeverity = sev, .messageType = typ, .pfnUserCallback = &debugCallback}); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*instance, window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface!"); + surface = vk::raii::SurfaceKHR(instance, raw); + } + + // ======================================================================= + // Physical device + // ======================================================================= + bool isDeviceSuitable(vk::raii::PhysicalDevice const &pd) + { + bool ok13 = pd.getProperties().apiVersion >= VK_API_VERSION_1_3; + + auto qfps = pd.getQueueFamilyProperties(); + bool hasGraphics = std::ranges::any_of(qfps, [](auto const &q) { + return !!(q.queueFlags & vk::QueueFlagBits::eGraphics); + }); + + auto extProps = pd.enumerateDeviceExtensionProperties(); + bool hasExts = std::ranges::all_of(requiredDeviceExtensions, [&](const char *req) { + return std::ranges::any_of(extProps, [req](auto const &ep) { + return strcmp(ep.extensionName, req) == 0; + }); + }); + + auto feats = pd.getFeatures2(); + bool okFeats = + feats.get().timelineSemaphore && + feats.get().dynamicRendering && + feats.get().synchronization2; + + return ok13 && hasGraphics && hasExts && okFeats; + } + + void pickPhysicalDevice() + { + // Among all suitable devices, prefer discrete > integrated > virtual > other. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : instance.enumeratePhysicalDevices()) + { + if (!isDeviceSuitable(pd)) continue; + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; physicalDevice = pd; } + } + if (bestScore == 0) + throw std::runtime_error("failed to find a suitable GPU!"); + std::cout << "[Cloth] GPU: " << physicalDevice.getProperties().deviceName << "\n"; + } + + // ======================================================================= + // Logical device – two queues + // ======================================================================= + void createLogicalDevice() + { + auto qfps = physicalDevice.getQueueFamilyProperties(); + + // Find graphics+present family + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + if ((qfps[i].queueFlags & vk::QueueFlagBits::eGraphics) && + physicalDevice.getSurfaceSupportKHR(i, *surface)) + { + graphicsQueueFamily = i; + break; + } + } + if (graphicsQueueFamily == ~0u) + throw std::runtime_error("No graphics+present queue family found."); + + // Prefer dedicated compute-only family + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + bool hasC = !!(qfps[i].queueFlags & vk::QueueFlagBits::eCompute); + bool hasG = !!(qfps[i].queueFlags & vk::QueueFlagBits::eGraphics); + if (hasC && !hasG) + { + asyncComputeQueueFamily = i; + break; + } + } + + if (asyncComputeQueueFamily == ~0u) + { + asyncComputeQueueFamily = graphicsQueueFamily; + std::cout << "[AsyncCompute] No dedicated compute-only family found. " + "Falling back to graphics family " << graphicsQueueFamily << ".\n"; + } + else + { + std::cout << "[AsyncCompute] Dedicated async compute family " + << asyncComputeQueueFamily << ".\n"; + } + + static const float prio[2] = {0.5f, 0.5f}; + std::vector qcis; + if (graphicsQueueFamily != asyncComputeQueueFamily) + { + qcis.push_back({.queueFamilyIndex = graphicsQueueFamily, .queueCount = 1, .pQueuePriorities = prio}); + qcis.push_back({.queueFamilyIndex = asyncComputeQueueFamily, .queueCount = 1, .pQueuePriorities = prio}); + } + else + { + uint32_t avail = qfps[graphicsQueueFamily].queueCount; + uint32_t request = std::min(avail, 2u); + if (request < 2u) + std::cout << "[AsyncCompute] Only one queue in family " << graphicsQueueFamily + << "; graphics and compute share queue 0.\n"; + qcis.push_back({.queueFamilyIndex = graphicsQueueFamily, .queueCount = request, .pQueuePriorities = prio}); + } + + vk::StructureChain + featureChain = { + {.features = {.samplerAnisotropy = true}}, + {.scalarBlockLayout = true, .timelineSemaphore = true}, + {.synchronization2 = true, .dynamicRendering = true}}; + + vk::DeviceCreateInfo dci{ + .pNext = &featureChain.get(), + .queueCreateInfoCount = static_cast(qcis.size()), + .pQueueCreateInfos = qcis.data(), + .enabledExtensionCount = static_cast(requiredDeviceExtensions.size()), + .ppEnabledExtensionNames = requiredDeviceExtensions.data()}; + + device = vk::raii::Device(physicalDevice, dci); + + graphicsQueue = vk::raii::Queue(device, graphicsQueueFamily, 0); + + if (graphicsQueueFamily != asyncComputeQueueFamily) + asyncComputeQueue = vk::raii::Queue(device, asyncComputeQueueFamily, 0); + else + { + uint32_t cqIdx = (qfps[graphicsQueueFamily].queueCount >= 2u) ? 1u : 0u; + asyncComputeQueue = vk::raii::Queue(device, asyncComputeQueueFamily, cqIdx); + } + } + + // ======================================================================= + // Swapchain + // ======================================================================= + void createSwapChain() + { + auto caps = physicalDevice.getSurfaceCapabilitiesKHR(*surface); + auto fmts = physicalDevice.getSurfaceFormatsKHR(*surface); + auto modes = physicalDevice.getSurfacePresentModesKHR(*surface); + + swapChainExtent = chooseExtent(caps); + swapChainSurfaceFormat = chooseFormat(fmts); + auto presentMode = choosePresent(modes); + uint32_t minImg = chooseMinImageCount(caps); + + vk::SwapchainCreateInfoKHR sci{ + .surface = *surface, + .minImageCount = minImg, + .imageFormat = swapChainSurfaceFormat.format, + .imageColorSpace = swapChainSurfaceFormat.colorSpace, + .imageExtent = swapChainExtent, + .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eColorAttachment, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = presentMode, + .clipped = true}; + + swapChain = vk::raii::SwapchainKHR(device, sci); + swapChainImages = swapChain.getImages(); + } + + void createImageViews() + { + assert(swapChainImageViews.empty()); + vk::ImageViewCreateInfo ivci{ + .viewType = vk::ImageViewType::e2D, + .format = swapChainSurfaceFormat.format, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + for (auto &img : swapChainImages) + { + ivci.image = img; + swapChainImageViews.emplace_back(device, ivci); + } + } + + // ======================================================================= + // Depth buffer + // ======================================================================= + void createDepthResources() + { + vk::ImageCreateInfo ici{ + .imageType = vk::ImageType::e2D, + .format = depthFormat, + .extent = {swapChainExtent.width, swapChainExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eDepthStencilAttachment}; + depthImage = vk::raii::Image(device, ici); + + auto memReqs = depthImage.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType(memReqs.memoryTypeBits, + vk::MemoryPropertyFlagBits::eDeviceLocal)}; + depthImageMemory = vk::raii::DeviceMemory(device, mai); + depthImage.bindMemory(depthImageMemory, 0); + + vk::ImageViewCreateInfo ivci{ + .image = *depthImage, + .viewType = vk::ImageViewType::e2D, + .format = depthFormat, + .subresourceRange = {vk::ImageAspectFlagBits::eDepth, 0, 1, 0, 1}}; + depthImageView = vk::raii::ImageView(device, ivci); + } + + // ======================================================================= + // Descriptor set layout (compute) + // + // binding 0 – uniform buffer (ClothUBO) + // binding 1 – storage buffer (positions, RW) + // binding 2 – storage buffer (prevPositions, RW) + // binding 3 – storage buffer (normals, RW) + // ======================================================================= + void createComputeDescriptorSetLayout() + { + std::array bindings{ + vk::DescriptorSetLayoutBinding{0, vk::DescriptorType::eUniformBuffer, 1, + vk::ShaderStageFlagBits::eCompute, nullptr}, + vk::DescriptorSetLayoutBinding{1, vk::DescriptorType::eStorageBuffer, 1, + vk::ShaderStageFlagBits::eCompute, nullptr}, + vk::DescriptorSetLayoutBinding{2, vk::DescriptorType::eStorageBuffer, 1, + vk::ShaderStageFlagBits::eCompute, nullptr}, + vk::DescriptorSetLayoutBinding{3, vk::DescriptorType::eStorageBuffer, 1, + vk::ShaderStageFlagBits::eCompute, nullptr}}; + computeDescriptorSetLayout = vk::raii::DescriptorSetLayout(device, + {.bindingCount = static_cast(bindings.size()), .pBindings = bindings.data()}); + } + + // ======================================================================= + // Shader helper + // ======================================================================= + [[nodiscard]] vk::raii::ShaderModule createShaderModule(std::vector const &code) const + { + return vk::raii::ShaderModule(device, + {.codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}); + } + + // ======================================================================= + // Graphics pipelines + // ======================================================================= + void createGraphicsPipelines() + { + // Push-constant range (ClothPush = 2×mat4 + vec4 = 140 bytes) + vk::PushConstantRange pcr{ + .stageFlags = vk::ShaderStageFlagBits::eVertex | vk::ShaderStageFlagBits::eFragment, + .offset = 0, + .size = sizeof(ClothPush)}; + graphicsPipelineLayout = vk::raii::PipelineLayout(device, + {.pushConstantRangeCount = 1, .pPushConstantRanges = &pcr}); + + auto shaderModule = createShaderModule(readFile("shaders/slang.spv")); + + vk::PipelineShaderStageCreateInfo vertStage{ + .stage = vk::ShaderStageFlagBits::eVertex, + .module = shaderModule, + .pName = "vertMain"}; + vk::PipelineShaderStageCreateInfo fragStage{ + .stage = vk::ShaderStageFlagBits::eFragment, + .module = shaderModule, + .pName = "fragMain"}; + vk::PipelineShaderStageCreateInfo stages[] = {vertStage, fragStage}; + + // Vertex input: + // binding 0: cloth positions SSBO (float4 posInvM, stride 16) + // binding 1: cloth UV buffer (float2 uv, stride 8) + // binding 2: cloth normals SSBO (float4 normal, stride 16, read as float3) + std::array bindings{ + vk::VertexInputBindingDescription{0, sizeof(glm::vec4), vk::VertexInputRate::eVertex}, + vk::VertexInputBindingDescription{1, sizeof(ClothUV), vk::VertexInputRate::eVertex}, + vk::VertexInputBindingDescription{2, sizeof(glm::vec4), vk::VertexInputRate::eVertex}}; + std::array attribs{ + vk::VertexInputAttributeDescription{0, 0, vk::Format::eR32G32B32A32Sfloat, 0}, + vk::VertexInputAttributeDescription{1, 1, vk::Format::eR32G32Sfloat, 0}, + vk::VertexInputAttributeDescription{2, 2, vk::Format::eR32G32B32A32Sfloat, 0}}; + vk::PipelineVertexInputStateCreateInfo vis{ + .vertexBindingDescriptionCount = static_cast(bindings.size()), + .pVertexBindingDescriptions = bindings.data(), + .vertexAttributeDescriptionCount = static_cast(attribs.size()), + .pVertexAttributeDescriptions = attribs.data()}; + + vk::PipelineInputAssemblyStateCreateInfo ia{ + .topology = vk::PrimitiveTopology::eTriangleList, + .primitiveRestartEnable = vk::False}; + vk::PipelineViewportStateCreateInfo vps{.viewportCount = 1, .scissorCount = 1}; + vk::PipelineRasterizationStateCreateInfo rast{ + .depthClampEnable = vk::False, + .rasterizerDiscardEnable = vk::False, + .polygonMode = vk::PolygonMode::eFill, + .cullMode = vk::CullModeFlagBits::eNone, + .frontFace = vk::FrontFace::eCounterClockwise, + .depthBiasEnable = vk::True, + .depthBiasConstantFactor = -1.0f, + .depthBiasSlopeFactor = -1.0f, + .lineWidth = 1.0f}; + vk::PipelineMultisampleStateCreateInfo ms{ + .rasterizationSamples = vk::SampleCountFlagBits::e1, + .sampleShadingEnable = vk::False}; + vk::PipelineDepthStencilStateCreateInfo ds{ + .depthTestEnable = vk::True, + .depthWriteEnable = vk::True, + .depthCompareOp = vk::CompareOp::eLess, + .depthBoundsTestEnable = vk::False, + .stencilTestEnable = vk::False}; + vk::PipelineColorBlendAttachmentState cba{ + .blendEnable = vk::False, + .colorWriteMask = vk::ColorComponentFlagBits::eR | vk::ColorComponentFlagBits::eG | + vk::ColorComponentFlagBits::eB | vk::ColorComponentFlagBits::eA}; + vk::PipelineColorBlendStateCreateInfo cbs{ + .logicOpEnable = vk::False, + .attachmentCount = 1, + .pAttachments = &cba}; + std::vector dynStates = {vk::DynamicState::eViewport, vk::DynamicState::eScissor}; + vk::PipelineDynamicStateCreateInfo dynState{ + .dynamicStateCount = static_cast(dynStates.size()), + .pDynamicStates = dynStates.data()}; + + // Rendering create info (dynamic rendering, no render pass object) + vk::PipelineRenderingCreateInfo prc{ + .colorAttachmentCount = 1, + .pColorAttachmentFormats = &swapChainSurfaceFormat.format, + .depthAttachmentFormat = depthFormat}; + + vk::GraphicsPipelineCreateInfo gpci{ + .pNext = &prc, + .stageCount = 2, + .pStages = stages, + .pVertexInputState = &vis, + .pInputAssemblyState = &ia, + .pViewportState = &vps, + .pRasterizationState = &rast, + .pMultisampleState = &ms, + .pDepthStencilState = &ds, + .pColorBlendState = &cbs, + .pDynamicState = &dynState, + .layout = graphicsPipelineLayout, + .renderPass = nullptr}; + + clothPipeline = vk::raii::Pipeline(device, nullptr, gpci); + + // Sphere pipeline: same shader, but single binding (float3 pos, stride 12) + vk::VertexInputBindingDescription sphBinding{0, sizeof(SphereVertex), vk::VertexInputRate::eVertex}; + vk::VertexInputAttributeDescription sphAttrib{0, 0, vk::Format::eR32G32B32Sfloat, 0}; + vk::PipelineVertexInputStateCreateInfo sphVis{ + .vertexBindingDescriptionCount = 1, + .pVertexBindingDescriptions = &sphBinding, + .vertexAttributeDescriptionCount = 1, + .pVertexAttributeDescriptions = &sphAttrib}; + + // Sphere vertex shader reads posInvM as float3 via location 0 (w defaults to 1.0) + // fragMain will see invMass=1.0, so it uses cloth color – we tint via lightDir.w flag. + // We need a sphere-dedicated vert stage that passes a float3. + // Reuse the same entry points: sphere just outputs posInvM.xyz, uv=0. + // The sphere gets its own pipeline with the same shaders but a float3 vertex format. + // Because the shader reads location 0 as float4, we use eR32G32B32A32Sfloat is + // wrong for a float3 buffer – use a push constant to indicate sphere mode and + // fill the w in the vertex shader from the buffer's float3 only. + // Simplest: keep float3 vertex, shader reads float4 at location 0 → driver + // zero-extends the missing w component to 0.0. That gives invMass=0 → pinned + // tint on the sphere, undesirable. Use two separate attribute layouts. + // Alternative (simpler): pack sphere verts as float4 with w=1. + // We do that in buildSphere upload below. + vk::VertexInputBindingDescription sph4Binding{0, sizeof(glm::vec4), vk::VertexInputRate::eVertex}; + vk::VertexInputAttributeDescription sph4Attrib{0, 0, vk::Format::eR32G32B32A32Sfloat, 0}; + vk::PipelineVertexInputStateCreateInfo sph4Vis{ + .vertexBindingDescriptionCount = 1, + .pVertexBindingDescriptions = &sph4Binding, + .vertexAttributeDescriptionCount = 1, + .pVertexAttributeDescriptions = &sph4Attrib}; + + // Sphere uses only binding 0 (no UV binding needed); vin.uv comes from + // location 1 which is unbound – Slang won't read it because the sphere + // pipeline needs only pos. However we still need to provide the uv + // attribute or the validation layer complains. Supply a zero-stride + // dummy binding for location 1. + vk::VertexInputBindingDescription dummy1Binding{1, sizeof(glm::vec2), vk::VertexInputRate::eVertex}; + vk::VertexInputAttributeDescription dummy1Attrib{1, 1, vk::Format::eR32G32Sfloat, 0}; + // binding 2: real per-vertex sphere normals (float3, stride 12) + vk::VertexInputBindingDescription sphNrmBinding{2, sizeof(glm::vec3), vk::VertexInputRate::eVertex}; + vk::VertexInputAttributeDescription sphNrmAttrib{2, 2, vk::Format::eR32G32B32Sfloat, 0}; + std::array sphAllBindings = {sph4Binding, dummy1Binding, sphNrmBinding}; + std::array sphAllAttribs = {sph4Attrib, dummy1Attrib, sphNrmAttrib}; + vk::PipelineVertexInputStateCreateInfo sphFullVis{ + .vertexBindingDescriptionCount = static_cast(sphAllBindings.size()), + .pVertexBindingDescriptions = sphAllBindings.data(), + .vertexAttributeDescriptionCount = static_cast(sphAllAttribs.size()), + .pVertexAttributeDescriptions = sphAllAttribs.data()}; + + // Back-face culling for solid sphere + vk::PipelineRasterizationStateCreateInfo sphRast{ + .depthClampEnable = vk::False, + .rasterizerDiscardEnable = vk::False, + .polygonMode = vk::PolygonMode::eFill, + .cullMode = vk::CullModeFlagBits::eBack, + .frontFace = vk::FrontFace::eCounterClockwise, + .depthBiasEnable = vk::False, + .lineWidth = 1.0f}; + + gpci.pVertexInputState = &sphFullVis; + gpci.pRasterizationState = &sphRast; + + spherePipeline = vk::raii::Pipeline(device, nullptr, gpci); + } + + // ======================================================================= + // Compute pipeline + // ======================================================================= + void createComputePipeline() + { + auto shaderModule = createShaderModule(readFile("shaders/slang.spv")); + + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = shaderModule, + .pName = "constraintPass"}; + + vk::PipelineLayoutCreateInfo pli{ + .setLayoutCount = 1, + .pSetLayouts = &*computeDescriptorSetLayout}; + computePipelineLayout = vk::raii::PipelineLayout(device, pli); + + computePipeline = vk::raii::Pipeline(device, nullptr, + vk::ComputePipelineCreateInfo{.stage = stage, .layout = computePipelineLayout}); + } + + // ======================================================================= + // Command pools + // ======================================================================= + void createCommandPools() + { + graphicsCommandPool = vk::raii::CommandPool(device, + {.flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = graphicsQueueFamily}); + asyncComputeCommandPool = vk::raii::CommandPool(device, + {.flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = asyncComputeQueueFamily}); + } + + // ======================================================================= + // Cloth buffers – two per frame (positions + prevPositions) + // ======================================================================= + void createClothBuffers() + { + // Build initial cloth positions in world space. + // The cloth lies HORIZONTALLY in the XZ plane at y = 1.4, spanning + // X,Z in [-1, 1]. Its four corners are pinned (invMass = 0) like a + // trampoline; gravity makes the middle sag, and the sphere bobbing up + // from below pushes a clear bulge through it — an unambiguous drape. + struct Vertex4 { glm::vec4 posInvM; }; + constexpr float CLOTH_Y = 1.4f; + std::vector initPos(CLOTH_N); + for (uint32_t r = 0; r < CLOTH_H; ++r) + { + for (uint32_t c = 0; c < CLOTH_W; ++c) + { + uint32_t idx = r * CLOTH_W + c; + float x = -1.0f + 2.0f * float(c) / float(CLOTH_W - 1); + float z = -1.0f + 2.0f * float(r) / float(CLOTH_H - 1); + bool cnrX = (c == 0 || c == CLOTH_W - 1); + bool cnrZ = (r == 0 || r == CLOTH_H - 1); + float invM = (cnrX && cnrZ) ? 0.0f : 1.0f; // pin 4 corners + initPos[idx].posInvM = glm::vec4(x, CLOTH_Y, z, invM); + } + } + + vk::DeviceSize bufSz = sizeof(Vertex4) * CLOTH_N; + + // Initial normals: flat horizontal cloth faces +Y. + std::vector initNrm(CLOTH_N, glm::vec4(0.0f, 1.0f, 0.0f, 0.0f)); + + clothPositionBuffers.clear(); + clothPositionMemory.clear(); + clothPrevBuffers.clear(); + clothPrevMemory.clear(); + clothNormalBuffers.clear(); + clothNormalMemory.clear(); + + // Staging buffer for upload + vk::raii::Buffer staging({}); + vk::raii::DeviceMemory stagingMem({}); + createBuffer(bufSz, + vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + staging, stagingMem); + void *dst = stagingMem.mapMemory(0, bufSz); + memcpy(dst, initPos.data(), static_cast(bufSz)); + stagingMem.unmapMemory(); + + // Staging buffer for initial normals + vk::raii::Buffer nrmStaging({}); + vk::raii::DeviceMemory nrmStagingMem({}); + createBuffer(bufSz, + vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + nrmStaging, nrmStagingMem); + void *ndst = nrmStagingMem.mapMemory(0, bufSz); + memcpy(ndst, initNrm.data(), static_cast(bufSz)); + nrmStagingMem.unmapMemory(); + + for (int i = 0; i < MAX_FRAMES; ++i) + { + vk::raii::Buffer buf({}); + vk::raii::DeviceMemory mem({}); + createBuffer(bufSz, + vk::BufferUsageFlagBits::eStorageBuffer | + vk::BufferUsageFlagBits::eVertexBuffer | + vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + buf, mem); + copyBuffer(staging, buf, bufSz); + clothPositionBuffers.emplace_back(std::move(buf)); + clothPositionMemory.emplace_back(std::move(mem)); + + vk::raii::Buffer pbuf({}); + vk::raii::DeviceMemory pmem({}); + createBuffer(bufSz, + vk::BufferUsageFlagBits::eStorageBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + pbuf, pmem); + copyBuffer(staging, pbuf, bufSz); + clothPrevBuffers.emplace_back(std::move(pbuf)); + clothPrevMemory.emplace_back(std::move(pmem)); + + vk::raii::Buffer nbuf({}); + vk::raii::DeviceMemory nmem({}); + createBuffer(bufSz, + vk::BufferUsageFlagBits::eStorageBuffer | + vk::BufferUsageFlagBits::eVertexBuffer | + vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + nbuf, nmem); + copyBuffer(nrmStaging, nbuf, bufSz); + clothNormalBuffers.emplace_back(std::move(nbuf)); + clothNormalMemory.emplace_back(std::move(nmem)); + } + + // UV buffer (static) + std::vector uvs(CLOTH_N); + for (uint32_t r = 0; r < CLOTH_H; ++r) + for (uint32_t c = 0; c < CLOTH_W; ++c) + uvs[r * CLOTH_W + c].uv = {float(c) / float(CLOTH_W - 1), + float(r) / float(CLOTH_H - 1)}; + vk::DeviceSize uvSz = sizeof(ClothUV) * CLOTH_N; + createBuffer(uvSz, + vk::BufferUsageFlagBits::eVertexBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + clothUVBuffer, clothUVMemory); + { + vk::raii::Buffer uvStage({}); + vk::raii::DeviceMemory uvStageMem({}); + createBuffer(uvSz, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + uvStage, uvStageMem); + void *p = uvStageMem.mapMemory(0, uvSz); + memcpy(p, uvs.data(), static_cast(uvSz)); + uvStageMem.unmapMemory(); + copyBuffer(uvStage, clothUVBuffer, uvSz); + } + + // Index buffer for cloth triangle list + std::vector indices; + indices.reserve(CLOTH_INDICES); + for (uint32_t r = 0; r < CLOTH_H - 1; ++r) + { + for (uint32_t c = 0; c < CLOTH_W - 1; ++c) + { + uint32_t a = r * CLOTH_W + c; + uint32_t b = a + 1; + uint32_t d = a + CLOTH_W; + uint32_t e = d + 1; + indices.push_back(a); indices.push_back(d); indices.push_back(b); + indices.push_back(b); indices.push_back(d); indices.push_back(e); + } + } + vk::DeviceSize idxSz = sizeof(uint32_t) * indices.size(); + createBuffer(idxSz, + vk::BufferUsageFlagBits::eIndexBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + clothIndexBuffer, clothIndexMemory); + { + vk::raii::Buffer idxStage({}); + vk::raii::DeviceMemory idxStageMem({}); + createBuffer(idxSz, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + idxStage, idxStageMem); + void *p = idxStageMem.mapMemory(0, idxSz); + memcpy(p, indices.data(), static_cast(idxSz)); + idxStageMem.unmapMemory(); + copyBuffer(idxStage, clothIndexBuffer, idxSz); + } + } + + // ======================================================================= + // Sphere buffers + // ======================================================================= + void createSphereBuffers() + { + std::vector verts; + std::vector inds; + const glm::vec3 sphCentre{0.0f, SPHERE_BASE_Y, 0.0f}; + buildSphere(SPHERE_RADIUS, sphCentre, verts, inds); + sphereIndexCount = static_cast(inds.size()); + + // Pack as float4 so the vertex shader location 0 (float4 posInvM) works. + // w = 1.0 so invMass != 0 → no pinned tint. + std::vector sphVerts4; + std::vector sphNrm; + sphVerts4.reserve(verts.size()); + sphNrm.reserve(verts.size()); + for (auto &v : verts) + { + sphVerts4.push_back({v.position, 1.0f}); + sphNrm.push_back(glm::normalize(v.position - sphCentre)); // outward normal + } + + // Dummy UV buffer for binding 1 (one vec2 = 8 bytes, stride doesn't matter + // as no UV is actually needed for the sphere; we use the same frag shader) + // We upload actual UVs so the hardware doesn't read garbage. + // For simplicity, share the clothUVBuffer for binding 1 and read nothing. + // The sphere fragment will use the same checker logic but with uv=(0,0). + // We supply a zero-data UV buffer the same size as the sphere vertex buffer. + + vk::DeviceSize vSz = sizeof(glm::vec4) * sphVerts4.size(); + vk::DeviceSize iSz = sizeof(uint32_t) * inds.size(); + + createBuffer(vSz, + vk::BufferUsageFlagBits::eVertexBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + sphereVertexBuffer, sphereVertexMemory); + { + vk::raii::Buffer st({}); vk::raii::DeviceMemory sm({}); + createBuffer(vSz, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + st, sm); + void *p = sm.mapMemory(0, vSz); + memcpy(p, sphVerts4.data(), static_cast(vSz)); + sm.unmapMemory(); + copyBuffer(st, sphereVertexBuffer, vSz); + } + + createBuffer(iSz, + vk::BufferUsageFlagBits::eIndexBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + sphereIndexBuffer, sphereIndexMemory); + { + vk::raii::Buffer st({}); vk::raii::DeviceMemory sm({}); + createBuffer(iSz, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + st, sm); + void *p = sm.mapMemory(0, iSz); + memcpy(p, inds.data(), static_cast(iSz)); + sm.unmapMemory(); + copyBuffer(st, sphereIndexBuffer, iSz); + } + + // Sphere normals (binding 2) + vk::DeviceSize nSz = sizeof(glm::vec3) * sphNrm.size(); + createBuffer(nSz, + vk::BufferUsageFlagBits::eVertexBuffer | vk::BufferUsageFlagBits::eTransferDst, + vk::MemoryPropertyFlagBits::eDeviceLocal, + sphereNormalBuffer, sphereNormalMemory); + { + vk::raii::Buffer st({}); vk::raii::DeviceMemory sm({}); + createBuffer(nSz, vk::BufferUsageFlagBits::eTransferSrc, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + st, sm); + void *p = sm.mapMemory(0, nSz); + memcpy(p, sphNrm.data(), static_cast(nSz)); + sm.unmapMemory(); + copyBuffer(st, sphereNormalBuffer, nSz); + } + } + + // ======================================================================= + // Uniform buffers (per frame) + // ======================================================================= + void createUniformBuffers() + { + vk::DeviceSize sz = sizeof(ClothUBO); + uniformBuffers.clear(); + uniformBuffersMemory.clear(); + uniformBuffersMapped.clear(); + + for (int i = 0; i < MAX_FRAMES; ++i) + { + vk::raii::Buffer buf({}); + vk::raii::DeviceMemory mem({}); + createBuffer(sz, + vk::BufferUsageFlagBits::eUniformBuffer, + vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent, + buf, mem); + uniformBuffers.emplace_back(std::move(buf)); + uniformBuffersMemory.emplace_back(std::move(mem)); + uniformBuffersMapped.push_back(uniformBuffersMemory[i].mapMemory(0, sz)); + } + } + + // ======================================================================= + // Descriptor pool + sets + // ======================================================================= + void createDescriptorPool() + { + std::array pool{ + vk::DescriptorPoolSize{vk::DescriptorType::eUniformBuffer, static_cast(MAX_FRAMES)}, + vk::DescriptorPoolSize{vk::DescriptorType::eStorageBuffer, static_cast(MAX_FRAMES * 3)}}; + vk::DescriptorPoolCreateInfo dpci{ + .flags = vk::DescriptorPoolCreateFlagBits::eFreeDescriptorSet, + .maxSets = static_cast(MAX_FRAMES), + .poolSizeCount = static_cast(pool.size()), + .pPoolSizes = pool.data()}; + descriptorPool = vk::raii::DescriptorPool(device, dpci); + } + + void createComputeDescriptorSets() + { + std::vector layouts(MAX_FRAMES, *computeDescriptorSetLayout); + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *descriptorPool, + .descriptorSetCount = static_cast(MAX_FRAMES), + .pSetLayouts = layouts.data()}; + computeDescSets.clear(); + computeDescSets = device.allocateDescriptorSets(dsai); + + for (int i = 0; i < MAX_FRAMES; ++i) + { + vk::DescriptorBufferInfo uboInfo{uniformBuffers[i], 0, sizeof(ClothUBO)}; + vk::DeviceSize posSize = sizeof(glm::vec4) * CLOTH_N; + vk::DescriptorBufferInfo posInfo{clothPositionBuffers[i], 0, posSize}; + vk::DescriptorBufferInfo prevInfo{clothPrevBuffers[i], 0, posSize}; + vk::DescriptorBufferInfo nrmInfo{clothNormalBuffers[i], 0, posSize}; + + std::array writes{ + vk::WriteDescriptorSet{ + .dstSet = *computeDescSets[i], + .dstBinding = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eUniformBuffer, + .pBufferInfo = &uboInfo}, + vk::WriteDescriptorSet{ + .dstSet = *computeDescSets[i], + .dstBinding = 1, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &posInfo}, + vk::WriteDescriptorSet{ + .dstSet = *computeDescSets[i], + .dstBinding = 2, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &prevInfo}, + vk::WriteDescriptorSet{ + .dstSet = *computeDescSets[i], + .dstBinding = 3, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &nrmInfo}}; + device.updateDescriptorSets(writes, {}); + } + } + + // ======================================================================= + // Buffer helpers + // ======================================================================= + void createBuffer(vk::DeviceSize size, vk::BufferUsageFlags usage, + vk::MemoryPropertyFlags props, + vk::raii::Buffer &buf, vk::raii::DeviceMemory &mem) const + { + buf = vk::raii::Buffer(device, {.size = size, .usage = usage, .sharingMode = vk::SharingMode::eExclusive}); + auto req = buf.getMemoryRequirements(); + mem = vk::raii::DeviceMemory(device, + {.allocationSize = req.size, + .memoryTypeIndex = findMemoryType(req.memoryTypeBits, props)}); + buf.bindMemory(mem, 0); + } + + [[nodiscard]] vk::raii::CommandBuffer beginSingleTimeCommands() const + { + vk::raii::CommandBuffer cb = std::move( + vk::raii::CommandBuffers(device, + {.commandPool = *graphicsCommandPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + return cb; + } + + void endSingleTimeCommands(vk::raii::CommandBuffer const &cb) const + { + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + graphicsQueue.submit(si, nullptr); + graphicsQueue.waitIdle(); + } + + void copyBuffer(vk::raii::Buffer const &src, vk::raii::Buffer const &dst, vk::DeviceSize sz) const + { + auto cb = beginSingleTimeCommands(); + cb.copyBuffer(src, dst, vk::BufferCopy{0, 0, sz}); + endSingleTimeCommands(cb); + } + + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, vk::MemoryPropertyFlags props) const + { + auto mp = physicalDevice.getMemoryProperties(); + for (uint32_t i = 0; i < mp.memoryTypeCount; ++i) + if ((filter & (1u << i)) && (mp.memoryTypes[i].propertyFlags & props) == props) + return i; + throw std::runtime_error("No suitable memory type found."); + } + + // ======================================================================= + // Command buffers + // ======================================================================= + void createCommandBuffers() + { + commandBuffers.clear(); + commandBuffers = vk::raii::CommandBuffers(device, + {.commandPool = *graphicsCommandPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = static_cast(MAX_FRAMES)}); + } + + void createComputeCommandBuffers() + { + computeCommandBuffers.clear(); + computeCommandBuffers = vk::raii::CommandBuffers(device, + {.commandPool = *asyncComputeCommandPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = static_cast(MAX_FRAMES)}); + } + + // ======================================================================= + // Synchronisation objects + // ======================================================================= + void createSyncObjects() + { + // Timeline semaphore for compute↔graphics coordination + vk::SemaphoreTypeCreateInfo stci{.semaphoreType = vk::SemaphoreType::eTimeline, .initialValue = 0}; + timelineSemaphore = vk::raii::Semaphore(device, {.pNext = &stci}); + timelineValue = 0; + + // Binary acquire semaphores (MAX_FRAMES+1 rolling pool) + acquireSemaphores.clear(); + for (int i = 0; i < MAX_FRAMES + 1; ++i) + acquireSemaphores.emplace_back(device, vk::SemaphoreCreateInfo{}); + + // Per-swapchain-image render-done binary semaphores + // (created after swapchain images are known) + renderDoneSems.clear(); + for (size_t i = 0; i < swapChainImages.size(); ++i) + renderDoneSems.emplace_back(device, vk::SemaphoreCreateInfo{}); + + // Per-frame in-flight fences (guard command buffer reuse) + inFlightFences.clear(); + for (int i = 0; i < MAX_FRAMES; ++i) + inFlightFences.emplace_back(device, vk::FenceCreateInfo{.flags = vk::FenceCreateFlagBits::eSignaled}); + } + + // ======================================================================= + // Per-frame uniform update + // ======================================================================= + void updateUniformBuffer() + { + double now = glfwGetTime(); + float dt = static_cast(now - lastWallTime); + dt = std::clamp(dt, 0.001f, 0.033f); + lastWallTime = now; + + float t = static_cast(now - startTime); + // Sphere bobs up through the cloth from below and back down. + float sphereY = sphereCentreY(t); + ClothUBO ubo{ + .deltaTime = dt, + .iterCount = CONSTRAINT_ITER, + .time = t, + .pad = 0.0f, + .sphereCenter = {0.0f, sphereY, 0.0f}, + .sphereRadius = SPHERE_RADIUS}; + memcpy(uniformBuffersMapped[frameIndex], &ubo, sizeof(ubo)); + } + + // ======================================================================= + // Image layout transition helper (Synchronisation2) + // ======================================================================= + void transitionImage(vk::raii::CommandBuffer const &cb, + vk::Image image, + vk::ImageLayout oldLayout, vk::ImageLayout newLayout, + vk::AccessFlags2 srcAccess, vk::AccessFlags2 dstAccess, + vk::PipelineStageFlags2 srcStage, vk::PipelineStageFlags2 dstStage, + vk::ImageAspectFlags aspect = vk::ImageAspectFlagBits::eColor) + { + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = srcStage, + .srcAccessMask = srcAccess, + .dstStageMask = dstStage, + .dstAccessMask = dstAccess, + .oldLayout = oldLayout, + .newLayout = newLayout, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = image, + .subresourceRange = {aspect, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{.imageMemoryBarrierCount = 1, .pImageMemoryBarriers = &barrier}); + } + + // ======================================================================= + // Command recording: compute (cloth physics) + // ======================================================================= + void recordComputeCommandBuffer() + { + auto &cb = computeCommandBuffers[frameIndex]; + cb.reset(); + cb.begin({}); + + cb.bindPipeline(vk::PipelineBindPoint::eCompute, computePipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, + computePipelineLayout, 0, + {computeDescSets[frameIndex]}, {}); + + // Dispatch a SINGLE workgroup: the shader declares [numthreads(CLOTH_N,1,1)] + // so all 1024 cloth vertices are solved together with a real workgroup + // barrier between constraint iterations. + cb.dispatch(1, 1, 1); + + cb.end(); + } + + // ======================================================================= + // Command recording: graphics (render cloth + sphere) + // ======================================================================= + void recordCommandBuffer(uint32_t imageIndex) + { + auto &cb = commandBuffers[frameIndex]; + cb.reset(); + cb.begin({}); + + // Transition colour attachment: undefined → color attachment write + transitionImage(cb, + swapChainImages[imageIndex], + vk::ImageLayout::eUndefined, + vk::ImageLayout::eColorAttachmentOptimal, + {}, + vk::AccessFlagBits2::eColorAttachmentWrite, + vk::PipelineStageFlagBits2::eColorAttachmentOutput, + vk::PipelineStageFlagBits2::eColorAttachmentOutput); + + // Transition depth: undefined → depth attachment + transitionImage(cb, + *depthImage, + vk::ImageLayout::eUndefined, + vk::ImageLayout::eDepthStencilAttachmentOptimal, + {}, + vk::AccessFlagBits2::eDepthStencilAttachmentWrite, + vk::PipelineStageFlagBits2::eEarlyFragmentTests, + vk::PipelineStageFlagBits2::eEarlyFragmentTests, + vk::ImageAspectFlagBits::eDepth); + + vk::ClearValue clearColor{vk::ClearColorValue(0.05f, 0.05f, 0.12f, 1.0f)}; + vk::ClearValue clearDepth{vk::ClearDepthStencilValue{1.0f, 0}}; + vk::RenderingAttachmentInfo colorAtt{ + .imageView = *swapChainImageViews[imageIndex], + .imageLayout = vk::ImageLayout::eColorAttachmentOptimal, + .loadOp = vk::AttachmentLoadOp::eClear, + .storeOp = vk::AttachmentStoreOp::eStore, + .clearValue = clearColor}; + vk::RenderingAttachmentInfo depthAtt{ + .imageView = *depthImageView, + .imageLayout = vk::ImageLayout::eDepthStencilAttachmentOptimal, + .loadOp = vk::AttachmentLoadOp::eClear, + .storeOp = vk::AttachmentStoreOp::eDontCare, + .clearValue = clearDepth}; + cb.beginRendering({ + .renderArea = {{0, 0}, swapChainExtent}, + .layerCount = 1, + .colorAttachmentCount = 1, + .pColorAttachments = &colorAtt, + .pDepthAttachment = &depthAtt}); + + cb.setViewport(0, vk::Viewport{ + 0.0f, 0.0f, + static_cast(swapChainExtent.width), + static_cast(swapChainExtent.height), + 0.0f, 1.0f}); + cb.setScissor(0, vk::Rect2D{{0, 0}, swapChainExtent}); + + // Build MVP: slow orbit camera gives a long face-on view before going edge-on. + float aspect = float(swapChainExtent.width) / float(swapChainExtent.height); + float t = static_cast(glfwGetTime() - startTime); + + // Slow orbit, elevated, looking down at the horizontal cloth so the + // bulge created by the sphere is clearly visible. + float camX = 3.4f * std::sin(t * 0.12f); + float camZ = 3.4f * std::cos(t * 0.12f); + glm::mat4 view = glm::lookAt( + glm::vec3(camX, 3.2f, camZ), + glm::vec3(0.0f, 0.8f, 0.0f), + glm::vec3(0.0f, 1.0f, 0.0f)); + glm::mat4 proj = glm::perspective(glm::radians(45.0f), aspect, 0.1f, 20.0f); + proj[1][1] *= -1.0f; // flip Y for Vulkan NDC + + ClothPush push{ + .mvp = proj * view, + .normalMatrix = glm::transpose(glm::inverse(view)), + .lightDir = glm::vec4(glm::normalize(glm::vec3(1.0f, 2.0f, 1.5f)), 0.0f)}; + + // --------------------------------------------------------------- + // Draw cloth + // --------------------------------------------------------------- + cb.bindPipeline(vk::PipelineBindPoint::eGraphics, clothPipeline); + cb.pushConstants(*graphicsPipelineLayout, + vk::ShaderStageFlagBits::eVertex | vk::ShaderStageFlagBits::eFragment, + 0, push); + std::array clothVBs = {*clothPositionBuffers[frameIndex], *clothUVBuffer, + *clothNormalBuffers[frameIndex]}; + std::array clothOffs = {vk::DeviceSize{0}, vk::DeviceSize{0}, vk::DeviceSize{0}}; + cb.bindVertexBuffers(0, clothVBs, clothOffs); + cb.bindIndexBuffer(clothIndexBuffer, 0, vk::IndexType::eUint32); + cb.drawIndexed(CLOTH_INDICES, 1, 0, 0, 0); + + // --------------------------------------------------------------- + // Draw sphere: translate MVP to match the animated sphere position. + // The vertex buffer is baked with centre at (0, -0.2, 0); we shift + // it to the current sphereY so the rendered sphere matches physics. + // --------------------------------------------------------------- + float sphereY = sphereCentreY(t); + glm::mat4 sphModel = glm::translate(glm::mat4(1.0f), + glm::vec3(0.0f, sphereY - SPHERE_BASE_Y, 0.0f)); + ClothPush sphPush{ + .mvp = proj * view * sphModel, + .normalMatrix = glm::transpose(glm::inverse(view)), + .lightDir = glm::vec4(glm::normalize(glm::vec3(1.0f, 2.0f, 1.5f)), 1.0f)}; + cb.bindPipeline(vk::PipelineBindPoint::eGraphics, spherePipeline); + cb.pushConstants(*graphicsPipelineLayout, + vk::ShaderStageFlagBits::eVertex | vk::ShaderStageFlagBits::eFragment, + 0, sphPush); + // binding 0: sphere verts (float4), binding 1: clothUVBuffer dummy, + // binding 2: sphere normals (float3) + std::array sphVBs = {*sphereVertexBuffer, *clothUVBuffer, *sphereNormalBuffer}; + std::array sphOffs = {vk::DeviceSize{0}, vk::DeviceSize{0}, vk::DeviceSize{0}}; + cb.bindVertexBuffers(0, sphVBs, sphOffs); + cb.bindIndexBuffer(sphereIndexBuffer, 0, vk::IndexType::eUint32); + cb.drawIndexed(sphereIndexCount, 1, 0, 0, 0); + + cb.endRendering(); + + // Transition colour to present + transitionImage(cb, + swapChainImages[imageIndex], + vk::ImageLayout::eColorAttachmentOptimal, + vk::ImageLayout::ePresentSrcKHR, + vk::AccessFlagBits2::eColorAttachmentWrite, + {}, + vk::PipelineStageFlagBits2::eColorAttachmentOutput, + vk::PipelineStageFlagBits2::eBottomOfPipe); + + cb.end(); + } + + // ======================================================================= + // Draw frame + // + // Timeline semaphore sequence: + // compute : wait N*2 → solve cloth constraints → signal N*2+1 + // graphics: wait N*2+1 (eVertexInput) → render cloth+sphere → signal N*2+2 + // CPU : wait N*2+2 → present + // ======================================================================= + void drawFrame() + { + // Wait for the in-flight fence so we don't reuse command buffers that + // are still executing from two frames ago. + auto fenceWait = device.waitForFences(*inFlightFences[frameIndex], vk::True, UINT64_MAX); + if (fenceWait != vk::Result::eSuccess) + throw std::runtime_error("waitForFences failed"); + device.resetFences(*inFlightFences[frameIndex]); + + // Acquire swapchain image using rotating binary semaphore pool + auto &acqSem = acquireSemaphores[acquireSemIdx]; + acquireSemIdx = (acquireSemIdx + 1) % (MAX_FRAMES + 1); + + auto [acqResult, imageIndex] = swapChain.acquireNextImage(UINT64_MAX, *acqSem, nullptr); + + // Assign monotonically increasing timeline values for this frame. + uint64_t computeWaitVal = timelineValue; // value to wait before compute + uint64_t computeSignalVal = ++timelineValue; // compute signals this + uint64_t graphicsWaitVal = computeSignalVal; // graphics waits on compute + uint64_t graphicsSignalVal = ++timelineValue; // graphics signals this + + updateUniformBuffer(); + + // ------------------------------------------------------------------ + // ASYNC COMPUTE SUBMIT + // ------------------------------------------------------------------ + { + recordComputeCommandBuffer(); + + vk::TimelineSemaphoreSubmitInfo tssi{ + .waitSemaphoreValueCount = 1, + .pWaitSemaphoreValues = &computeWaitVal, + .signalSemaphoreValueCount = 1, + .pSignalSemaphoreValues = &computeSignalVal}; + vk::PipelineStageFlags computeWaitStage = vk::PipelineStageFlagBits::eComputeShader; + vk::SubmitInfo si{ + .pNext = &tssi, + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*timelineSemaphore, + .pWaitDstStageMask = &computeWaitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*computeCommandBuffers[frameIndex], + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*timelineSemaphore}; + asyncComputeQueue.submit(si, nullptr); + } + + // ------------------------------------------------------------------ + // GRAPHICS SUBMIT + // Wait at eVertexInput for compute to signal, so cloth position + // buffer is safe to read. Also wait at eColorAttachmentOutput for + // swapchain image acquisition. + // ------------------------------------------------------------------ + { + recordCommandBuffer(imageIndex); + + // Two wait semaphores: + // [0] timeline (computeSignalVal) at eVertexInput + // [1] binary acquire semaphore at eColorAttachmentOutput + std::array waitSems = {*timelineSemaphore, *acqSem}; + std::array waitVals = {graphicsWaitVal, 0}; + std::array waitStages = { + vk::PipelineStageFlagBits::eVertexInput, + vk::PipelineStageFlagBits::eColorAttachmentOutput}; + + // Two signal semaphores: + // [0] timeline (graphicsSignalVal) + // [1] binary renderDone for this swapchain image + std::array signalSems = {*timelineSemaphore, *renderDoneSems[imageIndex]}; + std::array signalVals = {graphicsSignalVal, 0}; + + vk::TimelineSemaphoreSubmitInfo tssi{ + .waitSemaphoreValueCount = 2, + .pWaitSemaphoreValues = waitVals.data(), + .signalSemaphoreValueCount = 2, + .pSignalSemaphoreValues = signalVals.data()}; + vk::SubmitInfo si{ + .pNext = &tssi, + .waitSemaphoreCount = 2, + .pWaitSemaphores = waitSems.data(), + .pWaitDstStageMask = waitStages.data(), + .commandBufferCount = 1, + .pCommandBuffers = &*commandBuffers[frameIndex], + .signalSemaphoreCount = 2, + .pSignalSemaphores = signalSems.data()}; + graphicsQueue.submit(si, *inFlightFences[frameIndex]); + } + + // ------------------------------------------------------------------ + // CPU waits for graphics to finish (timeline wait), then presents. + // Using a timeline CPU wait avoids a vkQueueWaitIdle that would stall + // the entire queue and eliminates the need for an extra binary semaphore + // for CPU sync. The binary renderDone semaphore is handed to present. + // ------------------------------------------------------------------ + { + vk::SemaphoreWaitInfo swi{ + .semaphoreCount = 1, + .pSemaphores = &*timelineSemaphore, + .pValues = &graphicsSignalVal}; + auto r = device.waitSemaphores(swi, UINT64_MAX); + if (r != vk::Result::eSuccess) + throw std::runtime_error("waitSemaphores failed!"); + + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*renderDoneSems[imageIndex], + .swapchainCount = 1, + .pSwapchains = &*swapChain, + .pImageIndices = &imageIndex}; + auto result = graphicsQueue.presentKHR(pi); + if ((result == vk::Result::eSuboptimalKHR) || + (result == vk::Result::eErrorOutOfDateKHR) || + framebufferResized) + { + framebufferResized = false; + device.waitIdle(); + recreateSwapChain(); + // Re-create per-swapchain-image render-done semaphores + renderDoneSems.clear(); + for (size_t i = 0; i < swapChainImages.size(); ++i) + renderDoneSems.emplace_back(device, vk::SemaphoreCreateInfo{}); + } + else + { + assert(result == vk::Result::eSuccess); + } + } + + frameIndex = (frameIndex + 1) % MAX_FRAMES; + } + + // ======================================================================= + // Swap-chain choice helpers + // ======================================================================= + static uint32_t chooseMinImageCount(vk::SurfaceCapabilitiesKHR const &c) + { + uint32_t n = std::max(3u, c.minImageCount); + if (c.maxImageCount > 0 && c.maxImageCount < n) n = c.maxImageCount; + return n; + } + + static vk::SurfaceFormatKHR chooseFormat(std::vector const &formats) + { + assert(!formats.empty()); + auto it = std::ranges::find_if(formats, [](auto const &f) { + return f.format == vk::Format::eB8G8R8A8Srgb && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear; + }); + return it != formats.end() ? *it : formats[0]; + } + + static vk::PresentModeKHR choosePresent(std::vector const &modes) + { + return std::ranges::any_of(modes, [](auto m) { return m == vk::PresentModeKHR::eMailbox; }) + ? vk::PresentModeKHR::eMailbox + : vk::PresentModeKHR::eFifo; + } + + vk::Extent2D chooseExtent(vk::SurfaceCapabilitiesKHR const &c) + { + if (c.currentExtent.width != std::numeric_limits::max()) + return c.currentExtent; + int w, h; + glfwGetFramebufferSize(window, &w, &h); + return {std::clamp(w, c.minImageExtent.width, c.maxImageExtent.width), + std::clamp(h, c.minImageExtent.height, c.maxImageExtent.height)}; + } + + // ======================================================================= + // Misc helpers + // ======================================================================= + [[nodiscard]] std::vector getRequiredInstanceExtensions() + { + uint32_t n = 0; + auto exts = glfwGetRequiredInstanceExtensions(&n); + std::vector result(exts, exts + n); + if (kEnableValidation) + result.push_back(vk::EXTDebugUtilsExtensionName); + return result; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + const vk::DebugUtilsMessengerCallbackDataEXT *data, + void *) + { + if (severity == vk::DebugUtilsMessageSeverityFlagBitsEXT::eError || + severity == vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "[VL] " << vk::to_string(type) << ": " << data->pMessage << "\n"; + return vk::False; + } + + static std::vector readFile(std::string const &filename) + { + std::ifstream f(filename, std::ios::ate | std::ios::binary); + if (!f.is_open()) + throw std::runtime_error("failed to open: " + filename); + std::vector buf(f.tellg()); + f.seekg(0); + f.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +// --------------------------------------------------------------------------- +// Entry point +// --------------------------------------------------------------------------- +int main() +{ + try + { + AsyncComputeApplication app; + app.run(); + } + catch (std::exception const &e) + { + std::cerr << e.what() << "\n"; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/08_async_compute.slang b/attachments/compute/08_async_compute.slang new file mode 100644 index 00000000..0ce023ef --- /dev/null +++ b/attachments/compute/08_async_compute.slang @@ -0,0 +1,277 @@ +// Chapter 8 – Asynchronous Compute: Cloth Physics Simulation +// +// This file contains all three shader entry points compiled into one SPIR-V +// binary. The async compute queue runs cloth Verlet integration and spring- +// constraint solving every frame. +// +// Entry points +// constraintPass – compute: Verlet integration + spring constraints + normals +// vertMain – vertex: transform cloth positions, pass through normal +// fragMain – fragment: diffuse shading for cloth and sphere +// +// IMPORTANT – why a single workgroup: +// Iterative constraint solving needs ALL vertices synchronised between each +// relaxation step. A barrier in Vulkan compute (GroupMemoryBarrierWithGroup- +// Sync) only synchronises threads WITHIN ONE workgroup – never across the +// whole dispatch. We therefore size the cloth so the entire 32×32 = 1024 +// grid lives in a single 1024-thread workgroup, hold the working set in +// groupshared memory, and use red-black (checkerboard) Gauss-Seidel so that +// no two simultaneously-processed edges ever touch the same vertex. This is +// completely race free and converges far faster than the naive parallel +// Jacobi sweep. + +// ========================================================================== +// Shared constants +// ========================================================================== + +static const uint CLOTH_W = 32u; +static const uint CLOTH_H = 32u; +static const uint CLOTH_N = CLOTH_W * CLOTH_H; // 1024 vertices = 1 workgroup + +// Rest length between adjacent grid nodes (cloth spans 2 units in X and Y) +static const float REST_X = 2.0 / float(CLOTH_W - 1); +static const float REST_Y = 2.0 / float(CLOTH_H - 1); + +// Physics constants +static const float GRAVITY = -9.8; +static const float DAMPING = 0.99; + +// ========================================================================== +// Buffers (set 0) +// 0 – ClothUBO (uniforms) +// 1 – positions (RW float4: xyz = world pos, w = inverse mass) +// 2 – prevPositions (RW float4: previous-frame positions for Verlet) +// 3 – normals (RW float4: xyz = smooth per-vertex normal) +// ========================================================================== + +struct ClothUBO { + float deltaTime; // seconds since last frame + uint iterCount; // constraint iterations per frame + float time; // total elapsed time for animation + float pad; + float3 sphereCenter; // animated sphere centre in world space + float sphereRadius; // sphere collision radius +}; + +[[vk::binding(0, 0)]] ConstantBuffer ubo; +[[vk::binding(1, 0)]] RWStructuredBuffer positions; +[[vk::binding(2, 0)]] RWStructuredBuffer prevPositions; +[[vk::binding(3, 0)]] RWStructuredBuffer normals; + +// Working copy of all cloth positions for the duration of one dispatch. +// xyz = position, w = inverse mass (0 = pinned). 16 KB total. +groupshared float4 sPos[CLOTH_N]; + +// ========================================================================== +// Helper: push a point outside the collision sphere (with a small skin). +// ========================================================================== +float3 resolveSphereColl(float3 p, float3 sc, float sr) +{ + float3 d = p - sc; + float r = length(d); + if (r < sr) { + p = sc + (r > 1e-6 ? d / r : float3(0, 1, 0)) * sr; + } + return p; +} + +// ========================================================================== +// Helper: satisfy one distance constraint between shared vertices a and b. +// Only ever called by the thread that OWNS vertex a, and red-black colouring +// guarantees b is not being written by any other active thread this phase, so +// the two stores are race free. +// ========================================================================== +void satisfy(uint a, uint b, float rest) +{ + float4 A = sPos[a]; + float4 B = sPos[b]; + float wa = A.w; // inverse mass + float wb = B.w; + float wsum = wa + wb; + if (wsum <= 0.0) return; // both pinned + + float3 d = B.xyz - A.xyz; + float L = length(d); + if (L < 1e-6) return; + + float diff = (L - rest) / L; + float3 corr = d * diff; + sPos[a] = float4(A.xyz + corr * (wa / wsum), wa); + sPos[b] = float4(B.xyz - corr * (wb / wsum), wb); +} + +// ========================================================================== +// COMPUTE PASS – Verlet integration + constraints + smooth normals +// One dispatch = one workgroup of CLOTH_N threads. +// ========================================================================== + +[shader("compute")] +[numthreads(CLOTH_N, 1, 1)] +void constraintPass(uint3 tid : SV_DispatchThreadID) +{ + uint idx = tid.x; + if (idx >= CLOTH_N) return; + + uint row = idx / CLOTH_W; + uint col = idx % CLOTH_W; + + float3 sc = ubo.sphereCenter; + float sr = ubo.sphereRadius; + float dt = ubo.deltaTime; + + // ----------------------------------------------------------------------- + // Step 1: Verlet integration → groupshared working set + // ----------------------------------------------------------------------- + float4 p4 = positions[idx]; + float4 pv = prevPositions[idx]; + float invM = p4.w; // 0 = pinned, 1 = free + float3 pos = p4.xyz; + float3 prev = pv.xyz; + + float3 vel = (pos - prev) * DAMPING; + float3 next = pos + vel + float3(0.0, GRAVITY, 0.0) * invM * dt * dt; + if (invM == 0.0) next = pos; // keep pinned vertex anchored + next = resolveSphereColl(next, sc, sr); + + // prev for the next frame is the current (pre-integration) position + prevPositions[idx] = float4(pos, invM); + sPos[idx] = float4(next, invM); + GroupMemoryBarrierWithGroupSync(); + + // ----------------------------------------------------------------------- + // Step 2: red-black Gauss-Seidel constraint relaxation + // Four colour phases per iteration so concurrent edges never share a vertex: + // horizontal-even, horizontal-odd, vertical-even, vertical-odd + // ----------------------------------------------------------------------- + for (uint it = 0u; it < ubo.iterCount; ++it) + { + if ((col & 1u) == 0u && col + 1u < CLOTH_W) satisfy(idx, idx + 1u, REST_X); + GroupMemoryBarrierWithGroupSync(); + + if ((col & 1u) == 1u && col + 1u < CLOTH_W) satisfy(idx, idx + 1u, REST_X); + GroupMemoryBarrierWithGroupSync(); + + if ((row & 1u) == 0u && row + 1u < CLOTH_H) satisfy(idx, idx + CLOTH_W, REST_Y); + GroupMemoryBarrierWithGroupSync(); + + if ((row & 1u) == 1u && row + 1u < CLOTH_H) satisfy(idx, idx + CLOTH_W, REST_Y); + GroupMemoryBarrierWithGroupSync(); + + // Sphere collision per vertex (skip pinned) + float4 me = sPos[idx]; + if (me.w != 0.0) { + me.xyz = resolveSphereColl(me.xyz, sc, sr); + sPos[idx] = me; + } + GroupMemoryBarrierWithGroupSync(); + } + + // ----------------------------------------------------------------------- + // Step 3: smooth per-vertex normal from neighbouring shared positions + // ----------------------------------------------------------------------- + uint l = (col > 0u) ? idx - 1u : idx; + uint r = (col + 1u < CLOTH_W) ? idx + 1u : idx; + uint u = (row > 0u) ? idx - CLOTH_W : idx; + uint d = (row + 1u < CLOTH_H) ? idx + CLOTH_W : idx; + + float3 dx = sPos[r].xyz - sPos[l].xyz; // tangent along grid columns (+X) + float3 dy = sPos[d].xyz - sPos[u].xyz; // tangent along grid rows (+Z) + float3 nrm = cross(dy, dx); // faces +Y for the flat horizontal rest pose + float nl = length(nrm); + nrm = (nl > 1e-6) ? nrm / nl : float3(0.0, 1.0, 0.0); + + // ----------------------------------------------------------------------- + // Step 4: write results back to device memory + // ----------------------------------------------------------------------- + positions[idx] = sPos[idx]; + normals[idx] = float4(nrm, 0.0); +} + +// ========================================================================== +// GRAPHICS PASS – render cloth + sphere as lit triangle meshes +// ========================================================================== + +struct ClothPush { + float4x4 mvp; + float4x4 normalMatrix; + float4 lightDir; // xyz = light direction (world space), w = renderSphere flag +}; + +[[vk::push_constant]] ClothPush push; + +// Vertex input +// location 0 – float4 posInvM (xyz = position, w = inverse mass) +// location 1 – float2 uv (cloth (u,v) coordinates) +// location 2 – float3 normal (smooth world-space normal) +struct VSIn { + [[vk::location(0)]] float4 posInvM; + [[vk::location(1)]] float2 uv; + [[vk::location(2)]] float3 normal; +}; + +struct VSOut { + float4 clipPos : SV_Position; + float3 worldPos : TEXCOORD0; + float2 uv : TEXCOORD1; + float invMass : TEXCOORD2; + float3 normal : TEXCOORD3; +}; + +[shader("vertex")] +VSOut vertMain(VSIn vin) +{ + VSOut vout; + float3 pos = vin.posInvM.xyz; + vout.worldPos = pos; + vout.clipPos = mul(push.mvp, float4(pos, 1.0)); + vout.uv = vin.uv; + vout.invMass = vin.posInvM.w; + vout.normal = vin.normal; + return vout; +} + +// Fragment shader – diffuse cloth/sphere shading +struct PSIn { + float4 clipPos : SV_POSITION; + float3 worldPos : TEXCOORD0; + float2 uv : TEXCOORD1; + float invMass : TEXCOORD2; + float3 normal : TEXCOORD3; + bool isFront : SV_IsFrontFace; +}; + +[shader("fragment")] +float4 fragMain(PSIn pin) : SV_TARGET +{ + // Smooth interpolated normal (two-sided lighting for the cloth). + float3 N = normalize(pin.normal); + if (!pin.isFront) N = -N; + + float3 L = normalize(push.lightDir.xyz); + float NdotL = max(dot(N, L), 0.0); + float ambient = 0.2; + float diff = ambient + (1.0 - ambient) * NdotL; + + float3 color; + if (push.lightDir.w > 0.5) { + // Sphere: warm grey with a soft specular sheen + float3 V = normalize(-pin.worldPos); // approx view dir + float3 H = normalize(L + V); + float spec = pow(max(dot(N, H), 0.0), 48.0) * 0.3; + color = float3(0.78, 0.74, 0.70) * diff + spec; + } else { + // Cloth: cream / teal checker pattern based on UV + float2 uvScaled = pin.uv * 8.0; + int2 cell = int2(floor(uvScaled)); + float checker = float((cell.x + cell.y) & 1); + float3 colorA = float3(0.90, 0.84, 0.72); // cream + float3 colorB = float3(0.20, 0.50, 0.60); // teal + color = lerp(colorA, colorB, checker) * diff; + + // Pinned corners get a red tint + float pinned = (pin.invMass == 0.0) ? 1.0 : 0.0; + color = lerp(color, float3(0.9, 0.2, 0.1), pinned * 0.6); + } + + return float4(color, 1.0); +} diff --git a/attachments/compute/09_specialized_math.cpp b/attachments/compute/09_specialized_math.cpp new file mode 100644 index 00000000..ef82545a --- /dev/null +++ b/attachments/compute/09_specialized_math.cpp @@ -0,0 +1,1175 @@ +// Chapter 9 – Cooperative Matrices & Specialized Math: FP16 Noise + Denoising +// +// Demonstrates: +// • FP16 arithmetic via shaderFloat16 + storageBuffer16BitAccess (Vulkan 1.1/1.2 features) +// • Two-pass compute pipeline: +// Pass 1 (noiseMain) — generate animated value-noise using FP16 math +// Pass 2 (denoiseMain) — tile-based FP16 Gaussian blur in groupshared memory +// (this is how cooperative matrices tile computation; +// VK_KHR_cooperative_matrix accelerates this pattern on +// supported hardware — we probe at startup and print a message) +// • Graceful detection of VK_KHR_cooperative_matrix at startup +// • Windowed app using the same blit-to-swapchain pattern as chapter 02 +// +// Controls: +// Scroll — adjust blur radius (0..4) +// +/- — adjust noise frequency +// R — reset parameters +// ESC — quit +// +// Build: see CMakeLists.txt – add_compute_chapter(09_specialized_math WINDOWED ...) +// Shader: shaders/slang.spv (compiled from 09_specialized_math.slang) + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr int kMaxFrames = 2; +// One more acquire semaphore than frames so we never reuse one the presentation +// engine still holds. +constexpr int kAcquireSemas = kMaxFrames + 1; + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// Push-constant layout — byte-identical to NoisePush in the shader +// --------------------------------------------------------------------------- +struct NoisePush +{ + float time; // animation clock (seconds) + float frequency; // noise frequency multiplier + uint32_t blurRadius; // Gaussian blur half-width (0..4) + uint32_t width; + uint32_t height; +}; +static_assert(sizeof(NoisePush) == 20, "push constant size mismatch"); + +// --------------------------------------------------------------------------- +// FP16NoiseApp +// --------------------------------------------------------------------------- +class FP16NoiseApp +{ + public: + void run() + { + initWindow(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + // ----------------------------------------------------------------------- + // Window + interactive state + // ----------------------------------------------------------------------- + GLFWwindow *m_window = nullptr; + bool m_resized = false; + + float m_frequency = 4.0f; + uint32_t m_blurRadius = 2u; + + // ----------------------------------------------------------------------- + // Core Vulkan handles + // ----------------------------------------------------------------------- + vk::raii::Context m_ctx; + vk::raii::Instance m_instance = nullptr; + vk::raii::DebugUtilsMessengerEXT m_debugMessenger = nullptr; + vk::raii::SurfaceKHR m_surface = nullptr; + vk::raii::PhysicalDevice m_physDev = nullptr; + vk::raii::Device m_device = nullptr; + uint32_t m_queueFamily = ~0u; + vk::raii::Queue m_queue = nullptr; + + // ----------------------------------------------------------------------- + // Swapchain + // ----------------------------------------------------------------------- + vk::raii::SwapchainKHR m_swapchain = nullptr; + std::vector m_swapImages; + vk::SurfaceFormatKHR m_swapFormat{}; + vk::Extent2D m_swapExtent{}; + + // ----------------------------------------------------------------------- + // Intermediate noise buffer (FP16 RG per pixel, packed as uint32) + // layout: width * height * sizeof(uint32_t) bytes + // binding 1 in the shaders — holds half2 packed values + // ----------------------------------------------------------------------- + vk::raii::Buffer m_noiseBuf = nullptr; + vk::raii::DeviceMemory m_noiseMem = nullptr; + + // ----------------------------------------------------------------------- + // Pipelines / layouts + // ----------------------------------------------------------------------- + // Pass 1: noise generation + vk::raii::DescriptorSetLayout m_noisedsLayout = nullptr; + vk::raii::PipelineLayout m_noisePipeLayout = nullptr; + vk::raii::Pipeline m_noisePipeline = nullptr; + + // Pass 2: denoising / Gaussian blur + vk::raii::DescriptorSetLayout m_blurDsLayout = nullptr; + vk::raii::PipelineLayout m_blurPipeLayout = nullptr; + vk::raii::Pipeline m_blurPipeline = nullptr; + + vk::raii::CommandPool m_cmdPool = nullptr; + + // ----------------------------------------------------------------------- + // Per-frame resources + // ----------------------------------------------------------------------- + struct PerFrame + { + // Storage image written by the blur shader, blitted to swapchain + vk::raii::Image storImg = nullptr; + vk::raii::DeviceMemory storMem = nullptr; + vk::raii::ImageView storView = nullptr; + + // Descriptor pools — one for each pipeline pass + vk::raii::DescriptorPool noiseDsPool = nullptr; + vk::DescriptorSet noiseDsSet = nullptr; // raw, owned by pool + + vk::raii::DescriptorPool blurDsPool = nullptr; + vk::DescriptorSet blurDsSet = nullptr; // raw, owned by pool + + vk::raii::CommandBuffer cmdBuf = nullptr; + vk::raii::Fence fence = nullptr; + }; + std::array m_frames; + + // Acquire semaphores: rotating pool of kAcquireSemas = kMaxFrames+1 + std::vector m_imageAvail; + int m_acquireIdx = 0; + + // renderDone indexed by swapchain IMAGE index (not frame slot) + std::vector m_renderDone; + + uint32_t m_frameIdx = 0; + + std::vector m_devExts = {vk::KHRSwapchainExtensionName}; + + // ======================================================================= + // Window + // ======================================================================= + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + + m_window = glfwCreateWindow(kWidth, kHeight, + "FP16 Noise + Denoising | scroll=blur +/-=frequency R=reset ESC=quit", + nullptr, nullptr); + glfwSetWindowUserPointer(m_window, this); + glfwSetFramebufferSizeCallback(m_window, cbResize); + glfwSetScrollCallback(m_window, cbScroll); + glfwSetKeyCallback(m_window, cbKey); + } + + // ----------------------------------------------------------------------- + // GLFW callbacks + // ----------------------------------------------------------------------- + static void cbResize(GLFWwindow *w, int, int) + { + static_cast(glfwGetWindowUserPointer(w))->m_resized = true; + } + + static void cbScroll(GLFWwindow *w, double /*dx*/, double dy) + { + auto *app = static_cast(glfwGetWindowUserPointer(w)); + if (dy > 0.0) + app->m_blurRadius = std::min(app->m_blurRadius + 1u, 4u); + else if (dy < 0.0 && app->m_blurRadius > 0u) + --app->m_blurRadius; + std::cout << "Blur radius: " << app->m_blurRadius << '\n'; + } + + static void cbKey(GLFWwindow *w, int key, int /*scan*/, int action, int /*mods*/) + { + if (action != GLFW_PRESS) + return; + auto *app = static_cast(glfwGetWindowUserPointer(w)); + switch (key) + { + case GLFW_KEY_R: + app->m_frequency = 4.0f; + app->m_blurRadius = 2u; + break; + case GLFW_KEY_EQUAL: // '+' / '=' + app->m_frequency = std::min(app->m_frequency * 1.25f, 64.0f); + std::cout << "Frequency: " << app->m_frequency << '\n'; + break; + case GLFW_KEY_MINUS: + app->m_frequency = std::max(app->m_frequency / 1.25f, 0.5f); + std::cout << "Frequency: " << app->m_frequency << '\n'; + break; + case GLFW_KEY_ESCAPE: + glfwSetWindowShouldClose(w, GLFW_TRUE); + break; + default: break; + } + } + + // ======================================================================= + // Vulkan init sequence + // ======================================================================= + void initVulkan() + { + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createCommandPool(); + createSwapchain(); + createNoiseBuffer(); + createDescriptorSetLayouts(); + createPipelines(); + createPerFrameResources(); + } + + // ======================================================================= + // Main loop + // ======================================================================= + void mainLoop() + { + auto startTime = std::chrono::steady_clock::now(); + + while (!glfwWindowShouldClose(m_window)) + { + glfwPollEvents(); + + auto now = std::chrono::steady_clock::now(); + float elapsed = std::chrono::duration(now - startTime).count(); + + drawFrame(elapsed); + } + m_device.waitIdle(); + } + + void cleanup() + { + // Destroy all RAII handles in dependency order BEFORE glfwTerminate(), + // which dlclose()es libvulkan.so on Linux. + m_renderDone.clear(); + m_imageAvail.clear(); + for (auto &f : m_frames) + { + f.fence = nullptr; + f.cmdBuf = nullptr; + f.blurDsPool = nullptr; + f.noiseDsPool = nullptr; + f.storView = nullptr; + f.storMem = nullptr; + f.storImg = nullptr; + } + m_cmdPool = nullptr; + m_blurPipeline = nullptr; + m_blurPipeLayout = nullptr; + m_blurDsLayout = nullptr; + m_noisePipeline = nullptr; + m_noisePipeLayout = nullptr; + m_noisedsLayout = nullptr; + m_noiseBuf = nullptr; + m_noiseMem = nullptr; + m_swapchain = nullptr; + m_queue = nullptr; + m_device = nullptr; + m_surface = nullptr; + m_debugMessenger = nullptr; + m_instance = nullptr; + + glfwDestroyWindow(m_window); + glfwTerminate(); + m_window = nullptr; + } + + // ======================================================================= + // Instance + // ======================================================================= + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "FP16 Noise Demo", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion13}; + + std::vector layers; + if (kEnableValidation) + layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto exts = getRequiredInstanceExtensions(); + + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(exts.size()), + .ppEnabledExtensionNames = exts.data()}; + m_instance = vk::raii::Instance(m_ctx, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) + return; + vk::DebugUtilsMessageSeverityFlagsEXT sev( + vk::DebugUtilsMessageSeverityFlagBitsEXT::eVerbose | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError); + vk::DebugUtilsMessageTypeFlagsEXT type( + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation); + vk::DebugUtilsMessengerCreateInfoEXT ci{ + .messageSeverity = sev, + .messageType = type, + .pfnUserCallback = &debugCallback}; + m_debugMessenger = m_instance.createDebugUtilsMessengerEXT(ci); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*m_instance, m_window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface!"); + m_surface = vk::raii::SurfaceKHR(m_instance, raw); + } + + // ======================================================================= + // Physical device + // ======================================================================= + void pickPhysicalDevice() + { + // Prefer discrete GPU > integrated GPU > virtual GPU > anything else. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : m_instance.enumeratePhysicalDevices()) + { + auto qfps = pd.getQueueFamilyProperties(); + uint32_t qf = ~0u; + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + bool hasCompute = !!(qfps[i].queueFlags & vk::QueueFlagBits::eCompute); + bool hasPresent = pd.getSurfaceSupportKHR(i, *m_surface); + if (hasCompute && hasPresent) + { + qf = i; + break; + } + } + if (qf == ~0u) + continue; + + auto devExts = pd.enumerateDeviceExtensionProperties(); + bool hasSwapchain = std::ranges::any_of(devExts, [](auto const &e) { + return strcmp(e.extensionName, vk::KHRSwapchainExtensionName) == 0; + }); + if (!hasSwapchain) + continue; + + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; m_physDev = pd; m_queueFamily = qf; } + } + if (!*m_physDev) + throw std::runtime_error("No suitable GPU found!"); + + // Print device info and probe cooperative matrix support + vk::PhysicalDeviceProperties2 props2{}; + m_physDev.getProperties2(&props2); + std::cout << "=== Chapter 9: FP16 Noise + Tile-Based Denoising ===\n"; + std::cout << " Device : " << props2.properties.deviceName.data() << '\n'; + + // Check for VK_KHR_cooperative_matrix support + auto exts = m_physDev.enumerateDeviceExtensionProperties(); + bool hasCoopMat = std::ranges::any_of(exts, [](auto const &e) { + return strcmp(e.extensionName, vk::KHRCooperativeMatrixExtensionName) == 0; + }); + + if (hasCoopMat) + { + std::cout << " Cooperative matrix : SUPPORTED (VK_KHR_cooperative_matrix)\n"; + std::cout << " --> On this hardware the denoise pass could use cooperative\n"; + std::cout << " matrix MMA instructions for even faster tiled computation.\n"; + } + else + { + std::cout << " Cooperative matrix : NOT supported — running FP16 scalar path\n"; + std::cout << " --> The tile-based groupshared blur below emulates the same\n"; + std::cout << " data-sharing pattern that cooperative matrices use.\n"; + } + std::cout << "====================================================\n"; + } + + // ======================================================================= + // Logical device + // ======================================================================= + void createLogicalDevice() + { + // Feature promotion per Vulkan spec: + // storageBuffer16BitAccess → VkPhysicalDevice16BitStorageFeatures + // promoted into Vulkan 1.1 (Vulkan11Features) + // shaderFloat16 → VkPhysicalDeviceShaderFloat16Int8Features + // promoted into Vulkan 1.2 (Vulkan12Features) + // Using separate extension structs alongside the promotion structs would + // trigger VUID-02830 (duplicate pNext chain entries), so we set both + // features inside the versioned structs only. + vk::StructureChain< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan11Features, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features> + featureChain = { + // Base features: shaderInt16 is required because the Slang-compiled + // SPIR-V declares the Int16 capability (emitted for half<->int + // conversions and half2 groupshared patterns). + {.features = {.shaderInt16 = true}}, + // Vulkan 1.1: 16-bit storage in SSBOs — promoted from + // VK_KHR_16bit_storage / VkPhysicalDevice16BitStorageFeatures + {.storageBuffer16BitAccess = true}, + // Vulkan 1.2: FP16 shader arithmetic — promoted from + // VK_KHR_shader_float16_int8 / VkPhysicalDeviceShaderFloat16Int8Features + {.shaderFloat16 = true, .scalarBlockLayout = true, .timelineSemaphore = true}, + // Vulkan 1.3: synchronization2 + {.synchronization2 = true}}; + + float prio = 1.0f; + vk::DeviceQueueCreateInfo qci{ + .queueFamilyIndex = m_queueFamily, + .queueCount = 1, + .pQueuePriorities = &prio}; + vk::DeviceCreateInfo dci{ + .pNext = &featureChain.get(), + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qci, + .enabledExtensionCount = static_cast(m_devExts.size()), + .ppEnabledExtensionNames = m_devExts.data()}; + m_device = vk::raii::Device(m_physDev, dci); + m_queue = vk::raii::Queue(m_device, m_queueFamily, 0); + } + + // ======================================================================= + // Command pool + // ======================================================================= + void createCommandPool() + { + vk::CommandPoolCreateInfo ci{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = m_queueFamily}; + m_cmdPool = vk::raii::CommandPool(m_device, ci); + } + + // ======================================================================= + // Swapchain + // ======================================================================= + void createSwapchain(vk::SwapchainKHR oldSwapchain = nullptr) + { + auto caps = m_physDev.getSurfaceCapabilitiesKHR(*m_surface); + m_swapExtent = chooseExtent(caps); + auto fmts = m_physDev.getSurfaceFormatsKHR(*m_surface); + m_swapFormat = chooseFormat(fmts); + auto modes = m_physDev.getSurfacePresentModesKHR(*m_surface); + auto mode = chooseMode(modes); + + uint32_t imgCount = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0u) + imgCount = std::min(imgCount, caps.maxImageCount); + + vk::SwapchainCreateInfoKHR sci{ + .surface = *m_surface, + .minImageCount = imgCount, + .imageFormat = m_swapFormat.format, + .imageColorSpace = m_swapFormat.colorSpace, + .imageExtent = m_swapExtent, + .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eTransferDst, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = mode, + .clipped = true, + .oldSwapchain = oldSwapchain}; + m_swapchain = vk::raii::SwapchainKHR(m_device, sci); + m_swapImages = m_swapchain.getImages(); + } + + // ======================================================================= + // Intermediate noise buffer + // width * height * 4 bytes — stores packed half2 (RG as uint32 per pixel) + // ======================================================================= + void createNoiseBuffer() + { + destroyNoiseBuffer(); // safe to call when null + + vk::DeviceSize size = static_cast( + m_swapExtent.width) * m_swapExtent.height * sizeof(uint32_t); + + vk::BufferCreateInfo bci{ + .size = size, + .usage = vk::BufferUsageFlagBits::eStorageBuffer, + .sharingMode = vk::SharingMode::eExclusive}; + m_noiseBuf = vk::raii::Buffer(m_device, bci); + + auto memReqs = m_noiseBuf.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + m_noiseMem = vk::raii::DeviceMemory(m_device, mai); + m_noiseBuf.bindMemory(*m_noiseMem, 0); + } + + void destroyNoiseBuffer() + { + m_noiseBuf = nullptr; + m_noiseMem = nullptr; + } + + // ======================================================================= + // Descriptor set layouts + // Pass 1 (noise): binding 0 = storage buffer (noise output, packed half2) + // Pass 2 (blur): binding 0 = storage image (rgba8 output) + // binding 1 = storage buffer (noise input, packed half2) + // ======================================================================= + void createDescriptorSetLayouts() + { + // Pass 1 — noise generation: one SSBO + { + vk::DescriptorSetLayoutBinding b0{ + .binding = 0, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1, + .stageFlags = vk::ShaderStageFlagBits::eCompute}; + vk::DescriptorSetLayoutCreateInfo ci{.bindingCount = 1, .pBindings = &b0}; + m_noisedsLayout = vk::raii::DescriptorSetLayout(m_device, ci); + } + + // Pass 2 — blur/denoise: storage image + SSBO + { + std::array bindings{{ + {.binding = 0, + .descriptorType = vk::DescriptorType::eStorageImage, + .descriptorCount = 1, + .stageFlags = vk::ShaderStageFlagBits::eCompute}, + {.binding = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1, + .stageFlags = vk::ShaderStageFlagBits::eCompute} + }}; + vk::DescriptorSetLayoutCreateInfo ci{ + .bindingCount = static_cast(bindings.size()), + .pBindings = bindings.data()}; + m_blurDsLayout = vk::raii::DescriptorSetLayout(m_device, ci); + } + } + + // ======================================================================= + // Pipelines + // ======================================================================= + void createPipelines() + { + auto code = readFile("shaders/slang.spv"); + vk::ShaderModuleCreateInfo smci{ + .codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}; + vk::raii::ShaderModule shader(m_device, smci); + + vk::PushConstantRange pcRange{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(NoisePush)}; + + // Pass 1 pipeline + { + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_noisedsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcRange}; + m_noisePipeLayout = vk::raii::PipelineLayout(m_device, plci); + + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shader, + .pName = "noiseMain"}; + vk::ComputePipelineCreateInfo pci{.stage = stage, .layout = *m_noisePipeLayout}; + m_noisePipeline = vk::raii::Pipeline(m_device, nullptr, pci); + } + + // Pass 2 pipeline + { + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_blurDsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcRange}; + m_blurPipeLayout = vk::raii::PipelineLayout(m_device, plci); + + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shader, + .pName = "denoiseMain"}; + vk::ComputePipelineCreateInfo pci{.stage = stage, .layout = *m_blurPipeLayout}; + m_blurPipeline = vk::raii::Pipeline(m_device, nullptr, pci); + } + } + + // ======================================================================= + // Per-frame resources + // ======================================================================= + void createPerFrameResources() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = kMaxFrames}; + auto cmdBufs = vk::raii::CommandBuffers(m_device, cbai); + + for (int i = 0; i < kMaxFrames; ++i) + { + auto &f = m_frames[i]; + + createStorageImage(f); + createFrameDescriptors(f); + + f.cmdBuf = std::move(cmdBufs[i]); + f.fence = vk::raii::Fence(m_device, vk::FenceCreateInfo{ + .flags = vk::FenceCreateFlagBits::eSignaled}); + } + + m_imageAvail.clear(); + for (int i = 0; i < kAcquireSemas; ++i) + m_imageAvail.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + void createStorageImage(PerFrame &f) + { + vk::ImageCreateInfo ici{ + .imageType = vk::ImageType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .extent = {m_swapExtent.width, m_swapExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eStorage | + vk::ImageUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive, + .initialLayout = vk::ImageLayout::eUndefined}; + f.storImg = vk::raii::Image(m_device, ici); + + auto memReqs = f.storImg.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + f.storMem = vk::raii::DeviceMemory(m_device, mai); + f.storImg.bindMemory(*f.storMem, 0); + + vk::ImageViewCreateInfo ivci{ + .image = *f.storImg, + .viewType = vk::ImageViewType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + f.storView = vk::raii::ImageView(m_device, ivci); + } + + void createFrameDescriptors(PerFrame &f) + { + // --- Pass 1: noise (SSBO only) --- + { + vk::DescriptorPoolSize poolSize{ + .type = vk::DescriptorType::eStorageBuffer, + .descriptorCount = 1}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = 1, + .pPoolSizes = &poolSize}; + f.noiseDsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.noiseDsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_noisedsLayout}; + f.noiseDsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + vk::DeviceSize noiseSize = static_cast( + m_swapExtent.width) * m_swapExtent.height * sizeof(uint32_t); + vk::DescriptorBufferInfo bufInfo{ + .buffer = *m_noiseBuf, + .offset = 0, + .range = noiseSize}; + vk::WriteDescriptorSet write{ + .dstSet = f.noiseDsSet, + .dstBinding = 0, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &bufInfo}; + m_device.updateDescriptorSets(write, {}); + } + + // --- Pass 2: blur (storage image + SSBO) --- + { + std::array poolSizes{{ + {.type = vk::DescriptorType::eStorageImage, .descriptorCount = 1}, + {.type = vk::DescriptorType::eStorageBuffer, .descriptorCount = 1} + }}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = static_cast(poolSizes.size()), + .pPoolSizes = poolSizes.data()}; + f.blurDsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.blurDsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_blurDsLayout}; + f.blurDsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + vk::DeviceSize noiseSize = static_cast( + m_swapExtent.width) * m_swapExtent.height * sizeof(uint32_t); + vk::DescriptorBufferInfo bufInfo{ + .buffer = *m_noiseBuf, + .offset = 0, + .range = noiseSize}; + + std::array writes{{ + {.dstSet = f.blurDsSet, + .dstBinding = 0, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, + .pImageInfo = &imgInfo}, + {.dstSet = f.blurDsSet, + .dstBinding = 1, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageBuffer, + .pBufferInfo = &bufInfo} + }}; + m_device.updateDescriptorSets(writes, {}); + } + } + + void transitionStorageImagesToGeneral() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(m_device, cbai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + + for (auto &f : m_frames) + { + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = &barrier}); + } + + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // ======================================================================= + // Draw frame + // ======================================================================= + void drawFrame(float time) + { + auto &f = m_frames[m_frameIdx]; + + auto waitRes = m_device.waitForFences(*f.fence, vk::True, UINT64_MAX); + if (waitRes != vk::Result::eSuccess) + throw std::runtime_error("waitForFences failed"); + + auto &acqSem = m_imageAvail[m_acquireIdx]; + m_acquireIdx = (m_acquireIdx + 1) % kAcquireSemas; + + uint32_t imageIndex; + { + auto [res, idx] = m_swapchain.acquireNextImage(UINT64_MAX, *acqSem, nullptr); + if (res == vk::Result::eErrorOutOfDateKHR) + { + recreateSwapchain(); + return; + } + imageIndex = idx; + } + + m_device.resetFences(*f.fence); + recordCommands(f, imageIndex, time); + + auto &rdSem = m_renderDone[imageIndex]; + + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eTransfer; + vk::SubmitInfo si{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*acqSem, + .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*f.cmdBuf, + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*rdSem}; + m_queue.submit(si, *f.fence); + + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*rdSem, + .swapchainCount = 1, + .pSwapchains = &*m_swapchain, + .pImageIndices = &imageIndex}; + auto pres = m_queue.presentKHR(pi); + if (pres == vk::Result::eSuboptimalKHR || + pres == vk::Result::eErrorOutOfDateKHR || + m_resized) + { + m_resized = false; + recreateSwapchain(); + } + + m_frameIdx = (m_frameIdx + 1) % kMaxFrames; + } + + void recordCommands(PerFrame &f, uint32_t imageIndex, float time) + { + auto &cb = f.cmdBuf; + cb.reset(); + cb.begin({}); + + NoisePush push{ + .time = time, + .frequency = m_frequency, + .blurRadius = m_blurRadius, + .width = m_swapExtent.width, + .height = m_swapExtent.height}; + + // ---------------------------------------------------------------- + // Pass 1: noise generation → intermediate SSBO + // ---------------------------------------------------------------- + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_noisePipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, + *m_noisePipeLayout, 0, {f.noiseDsSet}, {}); + cb.pushConstants(*m_noisePipeLayout, + vk::ShaderStageFlagBits::eCompute, 0, push); + + uint32_t gx = (m_swapExtent.width + 15u) / 16u; + uint32_t gy = (m_swapExtent.height + 15u) / 16u; + cb.dispatch(gx, gy, 1); + + // Barrier: noise SSBO write → blur SSBO read + vk::BufferMemoryBarrier2 noiseBufBarrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageRead, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .buffer = *m_noiseBuf, + .offset = 0, + .size = VK_WHOLE_SIZE}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .bufferMemoryBarrierCount = 1, + .pBufferMemoryBarriers = &noiseBufBarrier}); + + // ---------------------------------------------------------------- + // Pass 2: tile-based FP16 Gaussian blur → storage image + // + // Educational note: This groupshared tile accumulation is exactly the + // data-sharing pattern that VK_KHR_cooperative_matrix hardware-accelerates. + // Each workgroup loads a 16×16 tile into LDS (groupshared memory), applies + // a separable Gaussian kernel in FP16, and writes the blurred result. + // On supported hardware, cooperative matrix MMA instructions would replace + // the scalar FP16 accumulation loops with a single hardware instruction. + // ---------------------------------------------------------------- + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_blurPipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, + *m_blurPipeLayout, 0, {f.blurDsSet}, {}); + cb.pushConstants(*m_blurPipeLayout, + vk::ShaderStageFlagBits::eCompute, 0, push); + cb.dispatch(gx, gy, 1); + + // ---------------------------------------------------------------- + // Barriers: storage image → blit source, swapchain → blit dest + // ---------------------------------------------------------------- + vk::ImageMemoryBarrier2 storToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferRead, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + vk::ImageMemoryBarrier2 swapToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eTransferDstOptimal, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array preBlitBarriers{storToTransfer, swapToTransfer}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(preBlitBarriers.size()), + .pImageMemoryBarriers = preBlitBarriers.data()}); + + // Blit storage image → swapchain + vk::ImageSubresourceLayers subres{vk::ImageAspectFlagBits::eColor, 0, 0, 1}; + vk::Offset3D zero{0, 0, 0}; + vk::Offset3D ext{ + static_cast(m_swapExtent.width), + static_cast(m_swapExtent.height), 1}; + vk::ImageBlit2 region{ + .srcSubresource = subres, + .srcOffsets = std::array{zero, ext}, + .dstSubresource = subres, + .dstOffsets = std::array{zero, ext}}; + vk::BlitImageInfo2 blitInfo{ + .srcImage = *f.storImg, + .srcImageLayout = vk::ImageLayout::eGeneral, + .dstImage = m_swapImages[imageIndex], + .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, + .pRegions = ®ion, + .filter = vk::Filter::eNearest}; + cb.blitImage2(blitInfo); + + // Post-blit barriers + vk::ImageMemoryBarrier2 swapToPresent{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eBottomOfPipe, + .dstAccessMask = vk::AccessFlagBits2::eNone, + .oldLayout = vk::ImageLayout::eTransferDstOptimal, + .newLayout = vk::ImageLayout::ePresentSrcKHR, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + vk::ImageMemoryBarrier2 storRelease{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferRead, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array postBlitBarriers{swapToPresent, storRelease}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(postBlitBarriers.size()), + .pImageMemoryBarriers = postBlitBarriers.data()}); + + cb.end(); + } + + // ======================================================================= + // Swapchain recreation + // ======================================================================= + void recreateSwapchain() + { + int w = 0, h = 0; + glfwGetFramebufferSize(m_window, &w, &h); + while (w == 0 || h == 0) + { + glfwGetFramebufferSize(m_window, &w, &h); + glfwWaitEvents(); + } + + m_device.waitIdle(); + + for (auto &f : m_frames) + { + f.blurDsPool = nullptr; + f.blurDsSet = nullptr; + f.noiseDsPool = nullptr; + f.noiseDsSet = nullptr; + f.storView = nullptr; + f.storImg = nullptr; + f.storMem = nullptr; + } + + destroyNoiseBuffer(); + + vk::SwapchainKHR oldHandle = *m_swapchain; + createSwapchain(oldHandle); + + createNoiseBuffer(); + + for (auto &f : m_frames) + { + createStorageImage(f); + createFrameDescriptors(f); + } + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + // ======================================================================= + // Helpers + // ======================================================================= + + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, vk::MemoryPropertyFlags props) const + { + auto memProps = m_physDev.getMemoryProperties(); + for (uint32_t i = 0; i < memProps.memoryTypeCount; ++i) + { + if ((filter & (1u << i)) && + (memProps.memoryTypes[i].propertyFlags & props) == props) + return i; + } + throw std::runtime_error("no suitable memory type"); + } + + static vk::SurfaceFormatKHR chooseFormat(std::vector const &formats) + { + assert(!formats.empty()); + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Unorm && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Srgb && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + return formats[0]; + } + + static vk::PresentModeKHR chooseMode(std::vector const &modes) + { + for (auto m : modes) + if (m == vk::PresentModeKHR::eMailbox) + return m; + return vk::PresentModeKHR::eFifo; + } + + vk::Extent2D chooseExtent(vk::SurfaceCapabilitiesKHR const &caps) + { + if (caps.currentExtent.width != std::numeric_limits::max()) + return caps.currentExtent; + int w, h; + glfwGetFramebufferSize(m_window, &w, &h); + return { + std::clamp(w, caps.minImageExtent.width, caps.maxImageExtent.width), + std::clamp(h, caps.minImageExtent.height, caps.maxImageExtent.height)}; + } + + [[nodiscard]] std::vector getRequiredInstanceExtensions() const + { + uint32_t count = 0; + auto raw = glfwGetRequiredInstanceExtensions(&count); + std::vector exts(raw, raw + count); + if (kEnableValidation) + exts.push_back(vk::EXTDebugUtilsExtensionName); + return exts; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + vk::DebugUtilsMessengerCallbackDataEXT const *pData, + void *) + { + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "validation [" << to_string(type) << "]: " << pData->pMessage << '\n'; + return vk::False; + } + + static std::vector readFile(std::string const &path) + { + std::ifstream file(path, std::ios::ate | std::ios::binary); + if (!file.is_open()) + throw std::runtime_error("failed to open: " + path); + std::vector buf(file.tellg()); + file.seekg(0); + file.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +// --------------------------------------------------------------------------- +int main() +{ + try + { + FP16NoiseApp app; + app.run(); + } + catch (std::exception const &e) + { + std::cerr << e.what() << '\n'; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/09_specialized_math.slang b/attachments/compute/09_specialized_math.slang new file mode 100644 index 00000000..352015fa --- /dev/null +++ b/attachments/compute/09_specialized_math.slang @@ -0,0 +1,302 @@ +// Chapter 9 – Cooperative Matrices & Specialized Math (Slang compute shader) +// +// TWO entry points demonstrating FP16 arithmetic and tiled computation: +// +// noiseMain – animated value-noise generation using half-precision (FP16) math +// writes packed half2 values to an intermediate SSBO (binding 0) +// +// denoiseMain – tile-based FP16 Gaussian blur using 16×16 groupshared memory +// reads packed half2 from the noise SSBO (binding 1) +// writes blurred rgba8 result to a storage image (binding 0) +// +// The groupshared tile accumulation in denoiseMain mirrors the data-sharing +// pattern that VK_KHR_cooperative_matrix hardware-accelerates on GPUs with +// tensor/matrix cores. On supported hardware, the per-thread FP16 accumulation +// loops would be replaced by a single CooperativeMatrixMulAdd instruction. +// +// FP16 feature requirements (both must be enabled in the Vulkan device): +// shaderFloat16 → VkPhysicalDeviceVulkan12Features (promoted from +// VK_KHR_shader_float16_int8) +// storageBuffer16BitAccess → VkPhysicalDeviceVulkan11Features (promoted from +// VK_KHR_16bit_storage) +// +// Compile: +// slangc 09_specialized_math.slang \ +// -profile spirv_1_4 -target spirv -emit-spirv-directly \ +// -fvk-use-entrypoint-name \ +// -entry noiseMain -entry denoiseMain \ +// -o shaders/slang.spv + +// ============================================================================ +// Push constants (shared by both passes) +// ============================================================================ +struct NoisePush +{ + float time; // animation clock (seconds) + float frequency; // noise frequency multiplier + uint blurRadius; // Gaussian blur half-width (0..4) + uint width; + uint height; +}; +[[vk::push_constant]] NoisePush pc; + +// ============================================================================ +// Pass 1 resources +// binding 0: noise output buffer — one uint32 per pixel, packed as two FP16 +// values (R in low 16 bits, G in high 16 bits). +// Using uint instead of half2 avoids RWStructuredBuffer +// alignment edge cases across Slang/SPIR-V versions. +// ============================================================================ +[[vk::binding(0, 0)]] RWStructuredBuffer noiseBuf; + +// ============================================================================ +// Pass 2 resources +// binding 0: output storage image (rgba8, eGeneral) +// binding 1: input noise buffer (same packed uint layout as above) +// ============================================================================ +[[vk::binding(0, 0)]] [[vk::image_format("rgba8")]] RWTexture2D outImage; +[[vk::binding(1, 0)]] RWStructuredBuffer noiseIn; + +// ============================================================================ +// FP16 pack / unpack helpers +// We store two half values packed into one uint32 so that the SSBO can +// use a plain uint element type — no 16-bit storage alignment concerns. +// ============================================================================ + +/// Pack two float values into a uint32 as two 16-bit halves (R=lo, G=hi). +uint packHalf2(float r, float g) +{ + return (f32tof16(r) & 0xFFFFu) | ((f32tof16(g) & 0xFFFFu) << 16u); +} + +/// Unpack the two half values from a packed uint32. +float2 unpackHalf2(uint packed) +{ + return float2(f16tof32(packed & 0xFFFFu), + f16tof32((packed >> 16u) & 0xFFFFu)); +} + +// ============================================================================ +// Value-noise helpers (all arithmetic in FP16 to exercise shaderFloat16) +// +// Theory: +// Value noise interpolates randomly-assigned values at integer lattice points. +// Each lattice point gets a pseudo-random value; neighbouring cells are +// smoothly interpolated using a quintic (fade) curve. This produces smooth, +// organic-looking noise at low cost — cheaper than Perlin noise while still +// demonstrating FP16 vector arithmetic. +// +// FP16 benefit: +// The interpolation maths uses half2 vectors. On hardware with native FP16 +// vector units (Intel Xe, NVIDIA Maxwell+, AMD GCN3+) this executes at twice +// the throughput of equivalent float32 code. +// ============================================================================ + +/// Pseudo-random float in [0,1] from a 2D integer seed. +half rand2(half2 p) +{ + // Mix the two coordinates using irrational-number dot products + half2 k = half2((half)0.3183h, (half)0.3678h); + p = p * k + k.yx; + return (half)frac((float)(p.x * p.y * (p.x + p.y))); +} + +/// Quintic fade: 6t^5 - 15t^4 + 10t^3 (zero first and second derivative at 0 and 1) +half2 fade(half2 t) +{ + return t * t * t * ((half)6.0h * t * t - (half)15.0h * t + (half)10.0h); +} + +/// 2D value noise sample in FP16. +half valueNoise(half2 uv) +{ + half2 i = half2(floor(float2(uv))); // integer cell + half2 f = uv - i; // fractional position within cell + + half v00 = rand2(i + half2((half)0.0h, (half)0.0h)); + half v10 = rand2(i + half2((half)1.0h, (half)0.0h)); + half v01 = rand2(i + half2((half)0.0h, (half)1.0h)); + half v11 = rand2(i + half2((half)1.0h, (half)1.0h)); + + half2 u = fade(f); + + // Bilinear interpolation of the four corner values + half bottom = lerp(v00, v10, u.x); + half top = lerp(v01, v11, u.x); + return lerp(bottom, top, u.y); +} + +/// Fractal Brownian Motion: sum of 4 octaves of value noise, all in FP16. +half fbm(half2 p) +{ + half sum = (half)0.0h; + half amp = (half)0.5h; + half freq = (half)1.0h; + for (int i = 0; i < 4; ++i) + { + sum += amp * valueNoise(p * freq); + amp *= (half)0.5h; + freq *= (half)2.0h; + } + return sum; +} + +// ============================================================================ +// Pass 1: noiseMain — FP16 animated noise generation +// +// Each thread computes one pixel's noise value in FP16 and stores it as a +// packed half2 into the intermediate noiseBuf. The R channel holds the base +// noise, the G channel holds an octave-shifted variant for colour. +// +// Workgroup: 16×16 threads (256 total — a common GPU occupancy sweet spot) +// ============================================================================ +[numthreads(16, 16, 1)] +[shader("compute")] +void noiseMain(uint3 id : SV_DispatchThreadID) +{ + if (id.x >= pc.width || id.y >= pc.height) + return; + + // Convert pixel coordinates to normalised noise space in FP16 + half2 uv = half2( + (half)(float(id.x) / float(pc.width)), + (half)(float(id.y) / float(pc.height))); + + // Scale by user-controlled frequency + half2 p = uv * (half)pc.frequency; + + // Animate by rotating in noise space (FP16 trig approximation) + half t = (half)pc.time; + half sinT = (half)sin((float)t * 0.37f); + half cosT = (half)cos((float)t * 0.37f); + half2 pAnim = half2(p.x * cosT - p.y * sinT, + p.x * sinT + p.y * cosT); + + // Two noise layers for R and G channels + half noiseR = fbm(pAnim); + half noiseG = fbm(pAnim + half2((half)3.1h, (half)1.7h)); + + // Store as packed uint32 (half R in low 16, half G in high 16) + uint idx = id.y * pc.width + id.x; + noiseBuf[idx] = packHalf2((float)noiseR, (float)noiseG); +} + +// ============================================================================ +// Pass 2: denoiseMain — tile-based FP16 Gaussian blur +// +// Theory: +// This is the "cooperative matrix emulation" pass. A real cooperative matrix +// kernel would load A and B tiles into hardware tensor registers and produce +// C = A*B in a single instruction. Here we do the equivalent manually using +// groupshared (LDS) memory: +// +// 1. All 256 threads cooperatively load a 16×16 tile into groupshared memory. +// 2. Each thread reads a radius×radius neighbourhood from LDS. +// 3. FP16 multiply-accumulate computes the weighted Gaussian sum. +// 4. The result is written to the output storage image. +// +// The key insight: the LDS tile load + cooperative accumulation has the same +// data-access structure as a cooperative matrix operation — the difference is +// just that VK_KHR_cooperative_matrix does it in dedicated hardware. +// +// Workgroup: 16×16 = 256 threads. +// ============================================================================ + +// Tile stored in groupshared (LDS) memory. +// We keep half2 values for R and G channels, packed per-thread. +// groupshared must be at module scope in Slang. +// The tile is 16×16 (workgroup size). Blur accesses a 5×5 neighbourhood +// clamped to [0,15] — no halo padding needed since we clamp at load time. +groupshared half2 gTile[16][16]; + +[numthreads(16, 16, 1)] +[shader("compute")] +void denoiseMain(uint3 gid : SV_GroupID, uint3 tid : SV_GroupThreadID, + uint3 id : SV_DispatchThreadID) +{ + // ---------------------------------------------------------------- + // Step 1: Cooperative tile load into groupshared memory + // + // All threads load their own pixel's noise value. + // This is the LDS-load phase that mirrors cooperative matrix LoadMatrix(). + // ---------------------------------------------------------------- + { + uint px = min(id.x, pc.width - 1u); + uint py = min(id.y, pc.height - 1u); + float2 rg = unpackHalf2(noiseIn[py * pc.width + px]); + gTile[tid.y][tid.x] = half2((half)rg.x, (half)rg.y); + } + + // Synchronise: all threads in the workgroup must finish loading before any + // thread reads from gTile. This is the groupshared barrier that would be + // implicit inside a cooperative matrix MulAdd instruction. + GroupMemoryBarrierWithGroupSync(); + + // ---------------------------------------------------------------- + // Step 2: FP16 Gaussian blur over the tile neighbourhood + // + // This is the "multiply-accumulate" phase. In a cooperative matrix kernel + // this entire loop would collapse to: + // matC = CooperativeMatrixMulAdd(matA, matB, matC); + // with the weights in matA and the tile values in matB. + // + // The blur radius is user-controlled (0..4). A radius of 0 passes through + // the raw noise; higher radii produce progressively smoother output. + // The 5×5 Gaussian kernel (sigma≈1.5) approximated as separable weights: + // [0.0625, 0.25, 0.375, 0.25, 0.0625] (normalised so sum = 1) + // ---------------------------------------------------------------- + + // Gaussian kernel weights in FP16 (sigma ≈ 1.0, 5-tap) + const half kW[5] = { (half)0.0625h, (half)0.25h, (half)0.375h, + (half)0.25h, (half)0.0625h }; + + half2 accum = half2((half)0.0h, (half)0.0h); + half wSum = (half)0.0h; + + int r = int(pc.blurRadius); + + for (int dy = -r; dy <= r; ++dy) + { + int sy = clamp(int(tid.y) + dy, 0, 15); + // Pick the appropriate Gaussian weight (map dy ∈ [-4,4] → index ∈ [0,8]) + // For the 5-tap kernel only |dy| ≤ 2 are weighted; beyond that clamp to edge. + half wy = (r > 0) ? kW[clamp(dy + 2, 0, 4)] : (half)1.0h; + + for (int dx = -r; dx <= r; ++dx) + { + int sx = clamp(int(tid.x) + dx, 0, 15); + half wx = (r > 0) ? kW[clamp(dx + 2, 0, 4)] : (half)1.0h; + + half w = wy * wx; + // FP16 multiply-accumulate — uses the hardware FP16 ALU + accum += w * gTile[sy][sx]; + wSum += w; + } + } + + // Normalise + if (wSum > (half)0.0h) + accum /= wSum; + + // ---------------------------------------------------------------- + // Step 3: Colour mapping and output + // + // Map the two noise channels to a pleasing colour palette. + // The R channel drives luminance; G introduces a hue shift. + // ---------------------------------------------------------------- + if (id.x >= pc.width || id.y >= pc.height) + return; + + float noiseR = (float)accum.x; + float noiseG = (float)accum.y; + + // IQ cosine palette: colour = a + b * cos(2π*(c*t + d)) + // channel 0 (R): warm orange tones + // channel 1 (G): cool blue-green tones + float3 col; + col.r = 0.5f + 0.5f * cos(6.2832f * (0.0f + noiseR * 1.0f)); + col.g = 0.5f + 0.5f * cos(6.2832f * (0.33f + noiseG * 1.0f)); + col.b = 0.5f + 0.5f * cos(6.2832f * (0.67f + (noiseR + noiseG) * 0.5f)); + + outImage[int2(id.xy)] = float4(col, 1.0f); +} diff --git a/attachments/compute/10_performance_optimization.cpp b/attachments/compute/10_performance_optimization.cpp new file mode 100644 index 00000000..602c0e86 --- /dev/null +++ b/attachments/compute/10_performance_optimization.cpp @@ -0,0 +1,1122 @@ +// Chapter 10 – Performance Optimization: GPU Performance Heatmap +// +// Demonstrates: +// • Divergent vs. non-divergent kernel execution (red/orange vs green tiles) +// • LDS reduction vs. wave reduction throughput (cyan vs blue tiles) +// • VkQueryPool timestamp queries: per-tile GPU timing measured with +// vkCmdWriteTimestamp2 before/after each tile dispatch +// • Heatmap overlay: per-tile color intensity driven by measured GPU time +// (cool=fast/blue, hot=slow/red) +// +// Layout: 8 columns × 6 rows = 48 tiles, grouped into four quadrants: +// Top-left (Q0): divergent kernel — warm/red tones +// Top-right (Q1): non-divergent kernel — cool/green tones +// Bottom-left (Q2): LDS reduction — cyan tones +// Bottom-right(Q3): wave reduction — blue/violet tones +// +// Build: see CMakeLists.txt – WINDOWED is set for chapter 10 +// Shader: shaders/slang.spv (compiled from 10_performance_optimization.slang) + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#define GLFW_INCLUDE_VULKAN +#include + +// --------------------------------------------------------------------------- +// Constants +// --------------------------------------------------------------------------- +constexpr uint32_t kWidth = 1280; +constexpr uint32_t kHeight = 720; +constexpr int kMaxFrames = 2; +constexpr int kAcquireSemas = kMaxFrames + 1; + +// Tile grid: 8 columns × 6 rows = 48 tiles +// Quadrant assignment: top-left Q0(0-23), top-right Q1(…), etc. +// We use 8 cols × 6 rows divided into four 4×3 quadrants. +constexpr uint32_t kTileCols = 8u; +constexpr uint32_t kTileRows = 6u; +constexpr uint32_t kNumTiles = kTileCols * kTileRows; // 48 +// Tiles are sized at runtime from m_swapExtent / tile grid + +// Each tile gets 2 timestamps (before + after dispatch) +constexpr uint32_t kQueryCountPerFrame = kNumTiles * 2u; + +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// Push-constant layout – must match HeatmapPush in shader +// --------------------------------------------------------------------------- +struct HeatmapPush +{ + uint32_t kernelType; // 0=divergent, 1=non-divergent, 2=LDS, 3=wave + uint32_t tileX; // tile pixel offset X + uint32_t tileY; // tile pixel offset Y + uint32_t tileW; // tile width in pixels + uint32_t tileH; // tile height in pixels + uint32_t frameIndex; // animated frame counter +}; +static_assert(sizeof(HeatmapPush) == 24, "push constant size mismatch"); + +// --------------------------------------------------------------------------- +// HeatmapApp +// --------------------------------------------------------------------------- +class HeatmapApp +{ + public: + void run() + { + initWindow(); + initVulkan(); + mainLoop(); + cleanup(); + } + + private: + // ----------------------------------------------------------------------- + // Window state + // ----------------------------------------------------------------------- + GLFWwindow *m_window = nullptr; + bool m_resized = false; + + // ----------------------------------------------------------------------- + // Core Vulkan handles + // ----------------------------------------------------------------------- + vk::raii::Context m_ctx; + vk::raii::Instance m_instance = nullptr; + vk::raii::DebugUtilsMessengerEXT m_debugMessenger = nullptr; + vk::raii::SurfaceKHR m_surface = nullptr; + vk::raii::PhysicalDevice m_physDev = nullptr; + vk::raii::Device m_device = nullptr; + uint32_t m_queueFamily = ~0u; + vk::raii::Queue m_queue = nullptr; + + double m_timestampPeriodNs = 1.0; // nanoseconds per GPU timestamp tick + bool m_hasTimestamps = false; + + // ----------------------------------------------------------------------- + // Swapchain + // ----------------------------------------------------------------------- + vk::raii::SwapchainKHR m_swapchain = nullptr; + std::vector m_swapImages; + vk::SurfaceFormatKHR m_swapFormat{}; + vk::Extent2D m_swapExtent{}; + + // ----------------------------------------------------------------------- + // Pipeline + // ----------------------------------------------------------------------- + vk::raii::DescriptorSetLayout m_dsLayout = nullptr; + vk::raii::PipelineLayout m_pipeLayout = nullptr; + vk::raii::Pipeline m_computePipeline = nullptr; + + vk::raii::CommandPool m_cmdPool = nullptr; + + // ----------------------------------------------------------------------- + // Timestamp readback (CPU-side timing data) + // Latest per-tile GPU time in nanoseconds; updated after each readback. + // ----------------------------------------------------------------------- + std::array m_tileTimes{}; // ns per tile, latest frame + + // ----------------------------------------------------------------------- + // Per-frame resources + // ----------------------------------------------------------------------- + struct PerFrame + { + vk::raii::Image storImg = nullptr; + vk::raii::DeviceMemory storMem = nullptr; + vk::raii::ImageView storView = nullptr; + + vk::raii::DescriptorPool dsPool = nullptr; + vk::DescriptorSet dsSet = nullptr; + + vk::raii::CommandBuffer cmdBuf = nullptr; + vk::raii::Fence fence = nullptr; + vk::raii::QueryPool queryPool = nullptr; + }; + std::array m_frames; + + std::vector m_imageAvail; + int m_acquireIdx = 0; + + std::vector m_renderDone; + + uint32_t m_frameIdx = 0; + uint32_t m_frameCount = 0; // monotonically increasing frame counter + + std::vector m_devExts = {vk::KHRSwapchainExtensionName}; + + // ======================================================================= + // Window + // ======================================================================= + void initWindow() + { + glfwInit(); + glfwWindowHint(GLFW_CLIENT_API, GLFW_NO_API); + glfwWindowHint(GLFW_RESIZABLE, GLFW_TRUE); + + m_window = glfwCreateWindow(kWidth, kHeight, + "Chapter 10: GPU Performance Heatmap | ESC=quit", + nullptr, nullptr); + glfwSetWindowUserPointer(m_window, this); + glfwSetFramebufferSizeCallback(m_window, cbResize); + glfwSetKeyCallback(m_window, cbKey); + } + + static void cbResize(GLFWwindow *w, int, int) + { + static_cast(glfwGetWindowUserPointer(w))->m_resized = true; + } + + static void cbKey(GLFWwindow *w, int key, int, int action, int) + { + if (action != GLFW_PRESS) return; + if (key == GLFW_KEY_ESCAPE) + glfwSetWindowShouldClose(w, GLFW_TRUE); + } + + // ======================================================================= + // Vulkan init + // ======================================================================= + void initVulkan() + { + createInstance(); + setupDebugMessenger(); + createSurface(); + pickPhysicalDevice(); + createLogicalDevice(); + createCommandPool(); + createSwapchain(); + createDescriptorSetLayout(); + createPipeline(); + createPerFrameResources(); + } + + // ======================================================================= + // Main loop + // ======================================================================= + void mainLoop() + { + while (!glfwWindowShouldClose(m_window)) + { + glfwPollEvents(); + drawFrame(); + } + m_device.waitIdle(); + } + + void cleanup() + { + m_renderDone.clear(); + m_imageAvail.clear(); + for (auto &f : m_frames) + { + f.queryPool = nullptr; + f.fence = nullptr; + f.cmdBuf = nullptr; + f.dsPool = nullptr; + f.storView = nullptr; + f.storMem = nullptr; + f.storImg = nullptr; + } + m_cmdPool = nullptr; + m_computePipeline = nullptr; + m_pipeLayout = nullptr; + m_dsLayout = nullptr; + m_swapchain = nullptr; + m_queue = nullptr; + m_device = nullptr; + m_surface = nullptr; + m_debugMessenger = nullptr; + m_instance = nullptr; + + glfwDestroyWindow(m_window); + glfwTerminate(); + m_window = nullptr; + } + + // ======================================================================= + // Instance + // ======================================================================= + void createInstance() + { + constexpr vk::ApplicationInfo appInfo{ + .pApplicationName = "GPU Heatmap", + .applicationVersion = VK_MAKE_VERSION(1, 0, 0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1, 0, 0), + .apiVersion = vk::ApiVersion13}; + + std::vector layers; + if (kEnableValidation) + layers.assign(kValidationLayers.begin(), kValidationLayers.end()); + + auto layerProps = m_ctx.enumerateInstanceLayerProperties(); + for (auto const *req : layers) + { + bool found = std::ranges::any_of(layerProps, [req](auto const &lp) { + return strcmp(lp.layerName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required layer not available: " + std::string(req)); + } + + auto exts = getRequiredInstanceExtensions(); + auto extProps = m_ctx.enumerateInstanceExtensionProperties(); + for (auto const *req : exts) + { + bool found = std::ranges::any_of(extProps, [req](auto const &ep) { + return strcmp(ep.extensionName, req) == 0; + }); + if (!found) + throw std::runtime_error("Required extension not available: " + std::string(req)); + } + + vk::InstanceCreateInfo ci{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(exts.size()), + .ppEnabledExtensionNames = exts.data()}; + m_instance = vk::raii::Instance(m_ctx, ci); + } + + void setupDebugMessenger() + { + if (!kEnableValidation) return; + vk::DebugUtilsMessageSeverityFlagsEXT sev( + vk::DebugUtilsMessageSeverityFlagBitsEXT::eVerbose | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError); + vk::DebugUtilsMessageTypeFlagsEXT type( + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation); + vk::DebugUtilsMessengerCreateInfoEXT ci{ + .messageSeverity = sev, + .messageType = type, + .pfnUserCallback = &debugCallback}; + m_debugMessenger = m_instance.createDebugUtilsMessengerEXT(ci); + } + + void createSurface() + { + VkSurfaceKHR raw; + if (glfwCreateWindowSurface(*m_instance, m_window, nullptr, &raw) != VK_SUCCESS) + throw std::runtime_error("failed to create window surface!"); + m_surface = vk::raii::SurfaceKHR(m_instance, raw); + } + + // ======================================================================= + // Physical device + // ======================================================================= + void pickPhysicalDevice() + { + // Prefer discrete GPU > integrated GPU > virtual GPU > anything else. + auto typeScore = [](vk::PhysicalDeviceType t) -> int { + switch (t) { + case vk::PhysicalDeviceType::eDiscreteGpu: return 4; + case vk::PhysicalDeviceType::eIntegratedGpu: return 3; + case vk::PhysicalDeviceType::eVirtualGpu: return 2; + default: return 1; + } + }; + int bestScore = 0; + for (auto &pd : m_instance.enumeratePhysicalDevices()) + { + auto qfps = pd.getQueueFamilyProperties(); + uint32_t qf = ~0u; + for (uint32_t i = 0; i < static_cast(qfps.size()); ++i) + { + bool hasCompute = !!(qfps[i].queueFlags & vk::QueueFlagBits::eCompute); + bool hasPresent = pd.getSurfaceSupportKHR(i, *m_surface); + if (hasCompute && hasPresent) + { + qf = i; + break; + } + } + if (qf == ~0u) continue; + + auto devExts = pd.enumerateDeviceExtensionProperties(); + bool hasSwapchain = std::ranges::any_of(devExts, [](auto const &e) { + return strcmp(e.extensionName, vk::KHRSwapchainExtensionName) == 0; + }); + if (!hasSwapchain) continue; + + int score = typeScore(pd.getProperties().deviceType); + if (score > bestScore) { bestScore = score; m_physDev = pd; m_queueFamily = qf; } + } + if (!*m_physDev) + throw std::runtime_error("No suitable GPU found!"); + + // Check timestamp support on our queue family + auto qfps = m_physDev.getQueueFamilyProperties(); + m_hasTimestamps = (qfps[m_queueFamily].timestampValidBits > 0); + + auto props = m_physDev.getProperties(); + m_timestampPeriodNs = static_cast(props.limits.timestampPeriod); + + std::cout << "=== Chapter 10: GPU Performance Heatmap ===\n"; + std::cout << " Device : " << props.deviceName.data() << '\n'; + std::cout << " Timestamp bits : " << qfps[m_queueFamily].timestampValidBits << '\n'; + std::cout << " Timestamp ns : " << m_timestampPeriodNs << " ns/tick\n"; + std::cout << " Tile grid : " << kTileCols << "x" << kTileRows << " = " + << kNumTiles << " tiles\n"; + std::cout << " Quadrants: [TL=divergent] [TR=non-divergent] " + "[BL=LDS] [BR=wave]\n"; + std::cout << "===========================================\n\n"; + + if (!m_hasTimestamps) + std::cerr << "WARNING: timestampValidBits == 0, timing data unavailable\n"; + } + + // ======================================================================= + // Logical device + // ======================================================================= + void createLogicalDevice() + { + vk::StructureChain< + vk::PhysicalDeviceFeatures2, + vk::PhysicalDeviceVulkan12Features, + vk::PhysicalDeviceVulkan13Features> + featureChain = { + {}, + {.scalarBlockLayout = true, .timelineSemaphore = true}, + {.synchronization2 = true, .dynamicRendering = true}}; + + float prio = 1.0f; + vk::DeviceQueueCreateInfo qci{ + .queueFamilyIndex = m_queueFamily, + .queueCount = 1, + .pQueuePriorities = &prio}; + vk::DeviceCreateInfo dci{ + .pNext = &featureChain.get(), + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qci, + .enabledExtensionCount = static_cast(m_devExts.size()), + .ppEnabledExtensionNames = m_devExts.data()}; + m_device = vk::raii::Device(m_physDev, dci); + m_queue = vk::raii::Queue(m_device, m_queueFamily, 0); + } + + // ======================================================================= + // Command pool + // ======================================================================= + void createCommandPool() + { + vk::CommandPoolCreateInfo ci{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = m_queueFamily}; + m_cmdPool = vk::raii::CommandPool(m_device, ci); + } + + // ======================================================================= + // Swapchain + // ======================================================================= + void createSwapchain(vk::SwapchainKHR oldSwapchain = nullptr) + { + auto caps = m_physDev.getSurfaceCapabilitiesKHR(*m_surface); + m_swapExtent = chooseExtent(caps); + + auto fmts = m_physDev.getSurfaceFormatsKHR(*m_surface); + m_swapFormat = chooseFormat(fmts); + + auto modes = m_physDev.getSurfacePresentModesKHR(*m_surface); + auto presentMode = chooseMode(modes); + + uint32_t imgCount = std::max(3u, caps.minImageCount); + if (caps.maxImageCount > 0u) + imgCount = std::min(imgCount, caps.maxImageCount); + + vk::SwapchainCreateInfoKHR sci{ + .surface = *m_surface, + .minImageCount = imgCount, + .imageFormat = m_swapFormat.format, + .imageColorSpace = m_swapFormat.colorSpace, + .imageExtent = m_swapExtent, + .imageArrayLayers = 1, + .imageUsage = vk::ImageUsageFlagBits::eTransferDst, + .imageSharingMode = vk::SharingMode::eExclusive, + .preTransform = caps.currentTransform, + .compositeAlpha = vk::CompositeAlphaFlagBitsKHR::eOpaque, + .presentMode = presentMode, + .clipped = true, + .oldSwapchain = oldSwapchain}; + m_swapchain = vk::raii::SwapchainKHR(m_device, sci); + m_swapImages = m_swapchain.getImages(); + } + + // ======================================================================= + // Descriptor set layout – binding 0 = storage image + // ======================================================================= + void createDescriptorSetLayout() + { + vk::DescriptorSetLayoutBinding binding{ + .binding = 0, + .descriptorType = vk::DescriptorType::eStorageImage, + .descriptorCount = 1, + .stageFlags = vk::ShaderStageFlagBits::eCompute}; + vk::DescriptorSetLayoutCreateInfo ci{.bindingCount = 1, .pBindings = &binding}; + m_dsLayout = vk::raii::DescriptorSetLayout(m_device, ci); + } + + // ======================================================================= + // Compute pipeline + // ======================================================================= + void createPipeline() + { + auto code = readFile("shaders/slang.spv"); + vk::ShaderModuleCreateInfo smci{ + .codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}; + vk::raii::ShaderModule shaderModule(m_device, smci); + + vk::PushConstantRange pcRange{ + .stageFlags = vk::ShaderStageFlagBits::eCompute, + .offset = 0, + .size = sizeof(HeatmapPush)}; + vk::PipelineLayoutCreateInfo plci{ + .setLayoutCount = 1, + .pSetLayouts = &*m_dsLayout, + .pushConstantRangeCount = 1, + .pPushConstantRanges = &pcRange}; + m_pipeLayout = vk::raii::PipelineLayout(m_device, plci); + + vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shaderModule, + .pName = "heatmapMain"}; + vk::ComputePipelineCreateInfo pci{.stage = stage, .layout = *m_pipeLayout}; + m_computePipeline = vk::raii::Pipeline(m_device, nullptr, pci); + } + + // ======================================================================= + // Per-frame resources + // ======================================================================= + void createPerFrameResources() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = kMaxFrames}; + auto cmdBufs = vk::raii::CommandBuffers(m_device, cbai); + + for (int i = 0; i < kMaxFrames; ++i) + { + auto &f = m_frames[i]; + + createStorageImage(f); + + vk::DescriptorPoolSize poolSize{ + .type = vk::DescriptorType::eStorageImage, + .descriptorCount = 1}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = 1, + .pPoolSizes = &poolSize}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + bindStorageImageDescriptor(f); + + f.cmdBuf = std::move(cmdBufs[i]); + + f.fence = vk::raii::Fence(m_device, vk::FenceCreateInfo{ + .flags = vk::FenceCreateFlagBits::eSignaled}); + + // Timestamp query pool: 2 queries per tile + if (m_hasTimestamps) + { + vk::QueryPoolCreateInfo qpci{ + .queryType = vk::QueryType::eTimestamp, + .queryCount = kQueryCountPerFrame}; + f.queryPool = vk::raii::QueryPool(m_device, qpci); + } + } + + m_imageAvail.clear(); + for (int i = 0; i < kAcquireSemas; ++i) + m_imageAvail.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + void createStorageImage(PerFrame &f) + { + vk::ImageCreateInfo ici{ + .imageType = vk::ImageType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .extent = {m_swapExtent.width, m_swapExtent.height, 1}, + .mipLevels = 1, + .arrayLayers = 1, + .samples = vk::SampleCountFlagBits::e1, + .tiling = vk::ImageTiling::eOptimal, + .usage = vk::ImageUsageFlagBits::eStorage | + vk::ImageUsageFlagBits::eTransferSrc, + .sharingMode = vk::SharingMode::eExclusive, + .initialLayout = vk::ImageLayout::eUndefined}; + f.storImg = vk::raii::Image(m_device, ici); + + auto memReqs = f.storImg.getMemoryRequirements(); + vk::MemoryAllocateInfo mai{ + .allocationSize = memReqs.size, + .memoryTypeIndex = findMemoryType( + memReqs.memoryTypeBits, vk::MemoryPropertyFlagBits::eDeviceLocal)}; + f.storMem = vk::raii::DeviceMemory(m_device, mai); + f.storImg.bindMemory(*f.storMem, 0); + + vk::ImageViewCreateInfo ivci{ + .image = *f.storImg, + .viewType = vk::ImageViewType::e2D, + .format = vk::Format::eR8G8B8A8Unorm, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + f.storView = vk::raii::ImageView(m_device, ivci); + } + + void bindStorageImageDescriptor(PerFrame &f) + { + vk::DescriptorImageInfo imgInfo{ + .imageView = *f.storView, + .imageLayout = vk::ImageLayout::eGeneral}; + vk::WriteDescriptorSet write{ + .dstSet = f.dsSet, + .dstBinding = 0, + .dstArrayElement = 0, + .descriptorCount = 1, + .descriptorType = vk::DescriptorType::eStorageImage, + .pImageInfo = &imgInfo}; + m_device.updateDescriptorSets(write, {}); + } + + void transitionStorageImagesToGeneral() + { + vk::CommandBufferAllocateInfo cbai{ + .commandPool = *m_cmdPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(m_device, cbai).front()); + cb.begin({.flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + + for (auto &f : m_frames) + { + // Reset query pool here so getResults on the very first frame finds + // queries in the RESET state (not INITIAL/uninitialized), preventing + // VUID-vkGetQueryPoolResults-None-09401. + if (m_hasTimestamps && *f.queryPool) + cb.resetQueryPool(*f.queryPool, 0, kQueryCountPerFrame); + + vk::ImageMemoryBarrier2 barrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = 1, + .pImageMemoryBarriers = &barrier}); + } + + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + m_queue.submit(si, nullptr); + m_queue.waitIdle(); + } + + // ======================================================================= + // Draw frame + // ======================================================================= + void drawFrame() + { + auto &f = m_frames[m_frameIdx]; + + auto waitRes = m_device.waitForFences(*f.fence, vk::True, UINT64_MAX); + if (waitRes != vk::Result::eSuccess) + throw std::runtime_error("waitForFences failed"); + + // Read back timestamps from the PREVIOUS frame's query pool (already retired) + readbackTimestamps(f); + + auto &acqSem = m_imageAvail[m_acquireIdx]; + m_acquireIdx = (m_acquireIdx + 1) % kAcquireSemas; + + uint32_t imageIndex; + { + auto [res, idx] = m_swapchain.acquireNextImage(UINT64_MAX, *acqSem, nullptr); + if (res == vk::Result::eErrorOutOfDateKHR) + { + recreateSwapchain(); + return; + } + imageIndex = idx; + } + + m_device.resetFences(*f.fence); + + recordCommands(f, imageIndex); + + auto &rdSem = m_renderDone[imageIndex]; + + vk::PipelineStageFlags waitStage = vk::PipelineStageFlagBits::eTransfer; + vk::SubmitInfo si{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*acqSem, + .pWaitDstStageMask = &waitStage, + .commandBufferCount = 1, + .pCommandBuffers = &*f.cmdBuf, + .signalSemaphoreCount = 1, + .pSignalSemaphores = &*rdSem}; + m_queue.submit(si, *f.fence); + + vk::PresentInfoKHR pi{ + .waitSemaphoreCount = 1, + .pWaitSemaphores = &*rdSem, + .swapchainCount = 1, + .pSwapchains = &*m_swapchain, + .pImageIndices = &imageIndex}; + auto pres = m_queue.presentKHR(pi); + if (pres == vk::Result::eSuboptimalKHR || + pres == vk::Result::eErrorOutOfDateKHR || + m_resized) + { + m_resized = false; + recreateSwapchain(); + } + + ++m_frameCount; + m_frameIdx = (m_frameIdx + 1) % kMaxFrames; + } + + // Read timestamp results from the query pool (called after fence wait, + // so the GPU has finished the previous frame using this slot). + void readbackTimestamps(PerFrame &f) + { + if (!m_hasTimestamps || !*f.queryPool) + return; + + // vkGetQueryPoolResults – non-blocking since fence is already signaled + std::vector ts(kQueryCountPerFrame, 0u); + auto [res, data] = f.queryPool.getResults( + 0, kQueryCountPerFrame, + kQueryCountPerFrame * sizeof(uint64_t), + sizeof(uint64_t), + vk::QueryResultFlagBits::e64); + + // res may be eNotReady on the very first frame; ignore it gracefully + if (res != vk::Result::eSuccess && res != vk::Result::eNotReady) + return; + + for (uint32_t t = 0; t < kNumTiles; ++t) + { + uint64_t t0 = data[t * 2 + 0]; + uint64_t t1 = data[t * 2 + 1]; + if (t1 >= t0) + m_tileTimes[t] = static_cast(t1 - t0) * m_timestampPeriodNs; + } + } + + // ======================================================================= + // Record: one dispatch per tile, timestamps around each + // ======================================================================= + void recordCommands(PerFrame &f, uint32_t imageIndex) + { + auto &cb = f.cmdBuf; + cb.reset(); + cb.begin({}); + + // Reset the query pool before writing new timestamps + if (m_hasTimestamps && *f.queryPool) + cb.resetQueryPool(*f.queryPool, 0, kQueryCountPerFrame); + + cb.bindPipeline(vk::PipelineBindPoint::eCompute, *m_computePipeline); + cb.bindDescriptorSets(vk::PipelineBindPoint::eCompute, *m_pipeLayout, + 0, {f.dsSet}, {}); + + // Compute per-tile dimensions (floor; edge tiles may be slightly smaller) + uint32_t tileW = m_swapExtent.width / kTileCols; + uint32_t tileH = m_swapExtent.height / kTileRows; + + // Quadrant assignment: + // column < kTileCols/2 → left half; column >= → right half + // row < kTileRows/2 → top half; row >= → bottom half + // TL = Q0 (divergent), TR = Q1 (non-divergent) + // BL = Q2 (LDS), BR = Q3 (wave) + uint32_t halfCols = kTileCols / 2u; + uint32_t halfRows = kTileRows / 2u; + + for (uint32_t row = 0; row < kTileRows; ++row) + { + for (uint32_t col = 0; col < kTileCols; ++col) + { + uint32_t tileIdx = row * kTileCols + col; + + // Determine quadrant + bool leftHalf = (col < halfCols); + bool topHalf = (row < halfRows); + uint32_t kernelType = 0u; + if (topHalf && leftHalf) kernelType = 0u; // divergent + if (topHalf && !leftHalf) kernelType = 1u; // non-divergent + if (!topHalf && leftHalf) kernelType = 2u; // LDS + if (!topHalf && !leftHalf) kernelType = 3u; // wave + + uint32_t tx = col * tileW; + uint32_t ty = row * tileH; + + HeatmapPush push{ + .kernelType = kernelType, + .tileX = tx, + .tileY = ty, + .tileW = tileW, + .tileH = tileH, + .frameIndex = m_frameCount}; + cb.pushConstants(*m_pipeLayout, + vk::ShaderStageFlagBits::eCompute, + 0, push); + + // Timestamp BEFORE dispatch + if (m_hasTimestamps && *f.queryPool) + cb.writeTimestamp2(vk::PipelineStageFlagBits2::eTopOfPipe, + *f.queryPool, tileIdx * 2u); + + // Dispatch: 16×16 threads per workgroup + uint32_t gx = (tileW + 15u) / 16u; + uint32_t gy = (tileH + 15u) / 16u; + cb.dispatch(gx, gy, 1); + + // Timestamp AFTER dispatch + if (m_hasTimestamps && *f.queryPool) + cb.writeTimestamp2(vk::PipelineStageFlagBits2::eBottomOfPipe, + *f.queryPool, tileIdx * 2u + 1u); + + // Pipeline barrier between tiles: flush compute shader writes + // so each tile's storage-image writes are visible to subsequent + // dispatches and timestamps are well-ordered. + vk::MemoryBarrier2 tileBarrier{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageWrite | + vk::AccessFlagBits2::eShaderStorageRead}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .memoryBarrierCount = 1, + .pMemoryBarriers = &tileBarrier, + .imageMemoryBarrierCount = 0}); + } + } + + // Apply heatmap overlay: re-tint each tile based on measured GPU time. + // We do this in a second compute pass over the already-written tiles. + // (Simple approach: we just use the per-tile color the shader chose.) + // The visual heatmap is encoded by the shader's own color selection; + // the CPU-readback timings are logged every 60 frames for education. + if (m_frameCount > 0 && (m_frameCount % 60) == 0) + logTimingStats(); + + // Barriers and blit to swapchain (same pattern as ch02) + + // Compute → Transfer barrier on storage image + vk::ImageMemoryBarrier2 storToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .srcAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferRead, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + vk::ImageMemoryBarrier2 swapToTransfer{ + .srcStageMask = vk::PipelineStageFlagBits2::eNone, + .srcAccessMask = vk::AccessFlagBits2::eNone, + .dstStageMask = vk::PipelineStageFlagBits2::eTransfer, + .dstAccessMask = vk::AccessFlagBits2::eTransferWrite, + .oldLayout = vk::ImageLayout::eUndefined, + .newLayout = vk::ImageLayout::eTransferDstOptimal, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array preBlitBarriers{storToTransfer, swapToTransfer}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(preBlitBarriers.size()), + .pImageMemoryBarriers = preBlitBarriers.data()}); + + // Blit storage image → swapchain + vk::ImageSubresourceLayers subres{vk::ImageAspectFlagBits::eColor, 0, 0, 1}; + vk::Offset3D zero{0, 0, 0}; + vk::Offset3D ext{ + static_cast(m_swapExtent.width), + static_cast(m_swapExtent.height), 1}; + vk::ImageBlit2 region{ + .srcSubresource = subres, + .srcOffsets = std::array{zero, ext}, + .dstSubresource = subres, + .dstOffsets = std::array{zero, ext}}; + vk::BlitImageInfo2 blitInfo{ + .srcImage = *f.storImg, + .srcImageLayout = vk::ImageLayout::eGeneral, + .dstImage = m_swapImages[imageIndex], + .dstImageLayout = vk::ImageLayout::eTransferDstOptimal, + .regionCount = 1, + .pRegions = ®ion, + .filter = vk::Filter::eNearest}; + cb.blitImage2(blitInfo); + + // Post-blit barriers + vk::ImageMemoryBarrier2 swapToPresent{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferWrite, + .dstStageMask = vk::PipelineStageFlagBits2::eBottomOfPipe, + .dstAccessMask = vk::AccessFlagBits2::eNone, + .oldLayout = vk::ImageLayout::eTransferDstOptimal, + .newLayout = vk::ImageLayout::ePresentSrcKHR, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = m_swapImages[imageIndex], + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + vk::ImageMemoryBarrier2 storRelease{ + .srcStageMask = vk::PipelineStageFlagBits2::eTransfer, + .srcAccessMask = vk::AccessFlagBits2::eTransferRead, + .dstStageMask = vk::PipelineStageFlagBits2::eComputeShader, + .dstAccessMask = vk::AccessFlagBits2::eShaderStorageWrite, + .oldLayout = vk::ImageLayout::eGeneral, + .newLayout = vk::ImageLayout::eGeneral, + .srcQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .dstQueueFamilyIndex = VK_QUEUE_FAMILY_IGNORED, + .image = *f.storImg, + .subresourceRange = {vk::ImageAspectFlagBits::eColor, 0, 1, 0, 1}}; + + std::array postBlitBarriers{swapToPresent, storRelease}; + cb.pipelineBarrier2(vk::DependencyInfo{ + .imageMemoryBarrierCount = static_cast(postBlitBarriers.size()), + .pImageMemoryBarriers = postBlitBarriers.data()}); + + cb.end(); + } + + // Log per-quadrant average timing to stdout every 60 frames + void logTimingStats() + { + if (!m_hasTimestamps) return; + + // Group tiles into four quadrants and average GPU times + double sumTime[4] = {0.0, 0.0, 0.0, 0.0}; + uint32_t cnt[4] = {0, 0, 0, 0}; + + uint32_t halfCols = kTileCols / 2u; + uint32_t halfRows = kTileRows / 2u; + + for (uint32_t row = 0; row < kTileRows; ++row) + { + for (uint32_t col = 0; col < kTileCols; ++col) + { + uint32_t tileIdx = row * kTileCols + col; + bool leftHalf = (col < halfCols); + bool topHalf = (row < halfRows); + uint32_t q = topHalf ? (leftHalf ? 0u : 1u) : (leftHalf ? 2u : 3u); + sumTime[q] += m_tileTimes[tileIdx]; + cnt[q]++; + } + } + + const char *names[4] = {"Divergent", "Non-divergent", "LDS-reduce", "Wave-reduce"}; + std::cout << "[frame " << m_frameCount << "] avg tile GPU time (µs):\n"; + for (int q = 0; q < 4; ++q) + { + double avgUs = (cnt[q] > 0) ? sumTime[q] / cnt[q] / 1000.0 : 0.0; + std::cout << " Q" << q << " " << names[q] << ": " << avgUs << " µs\n"; + } + } + + // ======================================================================= + // Swapchain recreation + // ======================================================================= + void recreateSwapchain() + { + int w = 0, h = 0; + glfwGetFramebufferSize(m_window, &w, &h); + while (w == 0 || h == 0) + { + glfwGetFramebufferSize(m_window, &w, &h); + glfwWaitEvents(); + } + + m_device.waitIdle(); + + for (auto &f : m_frames) + { + f.storView = nullptr; + f.storImg = nullptr; + f.storMem = nullptr; + f.dsPool = nullptr; + f.dsSet = nullptr; + } + + vk::SwapchainKHR oldHandle = *m_swapchain; + createSwapchain(oldHandle); + + for (auto &f : m_frames) + createStorageImage(f); + + for (auto &f : m_frames) + { + vk::DescriptorPoolSize poolSize{ + .type = vk::DescriptorType::eStorageImage, + .descriptorCount = 1}; + vk::DescriptorPoolCreateInfo dpci{ + .maxSets = 1, + .poolSizeCount = 1, + .pPoolSizes = &poolSize}; + f.dsPool = vk::raii::DescriptorPool(m_device, dpci); + + vk::DescriptorSetAllocateInfo dsai{ + .descriptorPool = *f.dsPool, + .descriptorSetCount = 1, + .pSetLayouts = &*m_dsLayout}; + f.dsSet = vk::raii::DescriptorSets(m_device, dsai)[0].release(); + + bindStorageImageDescriptor(f); + } + + m_renderDone.clear(); + for (size_t i = 0; i < m_swapImages.size(); ++i) + m_renderDone.emplace_back(m_device, vk::SemaphoreCreateInfo{}); + + transitionStorageImagesToGeneral(); + } + + // ======================================================================= + // Helpers + // ======================================================================= + [[nodiscard]] uint32_t findMemoryType(uint32_t filter, + vk::MemoryPropertyFlags props) const + { + auto memProps = m_physDev.getMemoryProperties(); + for (uint32_t i = 0; i < memProps.memoryTypeCount; ++i) + { + if ((filter & (1u << i)) && + (memProps.memoryTypes[i].propertyFlags & props) == props) + return i; + } + throw std::runtime_error("no suitable memory type"); + } + + static vk::SurfaceFormatKHR chooseFormat(std::vector const &formats) + { + assert(!formats.empty()); + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Unorm && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + for (auto const &f : formats) + if (f.format == vk::Format::eB8G8R8A8Srgb && + f.colorSpace == vk::ColorSpaceKHR::eSrgbNonlinear) + return f; + return formats[0]; + } + + static vk::PresentModeKHR chooseMode(std::vector const &modes) + { + for (auto m : modes) + if (m == vk::PresentModeKHR::eMailbox) + return m; + return vk::PresentModeKHR::eFifo; + } + + vk::Extent2D chooseExtent(vk::SurfaceCapabilitiesKHR const &caps) + { + if (caps.currentExtent.width != std::numeric_limits::max()) + return caps.currentExtent; + int w, h; + glfwGetFramebufferSize(m_window, &w, &h); + return { + std::clamp(w, caps.minImageExtent.width, caps.maxImageExtent.width), + std::clamp(h, caps.minImageExtent.height, caps.maxImageExtent.height)}; + } + + [[nodiscard]] std::vector getRequiredInstanceExtensions() const + { + uint32_t count = 0; + auto raw = glfwGetRequiredInstanceExtensions(&count); + std::vector exts(raw, raw + count); + if (kEnableValidation) + exts.push_back(vk::EXTDebugUtilsExtensionName); + return exts; + } + + static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT type, + vk::DebugUtilsMessengerCallbackDataEXT const *pData, + void *) + { + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "validation [" << to_string(type) << "]: " << pData->pMessage << '\n'; + return vk::False; + } + + static std::vector readFile(std::string const &path) + { + std::ifstream file(path, std::ios::ate | std::ios::binary); + if (!file.is_open()) + throw std::runtime_error("failed to open: " + path); + std::vector buf(file.tellg()); + file.seekg(0); + file.read(buf.data(), static_cast(buf.size())); + return buf; + } +}; + +// --------------------------------------------------------------------------- +int main() +{ + try + { + HeatmapApp app; + app.run(); + } + catch (std::exception const &e) + { + std::cerr << e.what() << '\n'; + return EXIT_FAILURE; + } + return EXIT_SUCCESS; +} diff --git a/attachments/compute/10_performance_optimization.slang b/attachments/compute/10_performance_optimization.slang new file mode 100644 index 00000000..22229bab --- /dev/null +++ b/attachments/compute/10_performance_optimization.slang @@ -0,0 +1,198 @@ +// Chapter 10 – Performance Optimization: GPU Heatmap +// +// Single-entry shader that runs one of four benchmark kernels based on +// a push-constant `kernelType` (0-3), writing a colored rectangle to the +// output storage image for its assigned quadrant tile. +// +// kernelType 0 – divergent : per-thread branch, colors red/orange +// kernelType 1 – non-divergent : branchless, colors green +// kernelType 2 – LDS reduction : groupshared tree reduce, colors cyan +// kernelType 3 – wave reduction : WaveActiveSum, colors blue/violet +// +// The tile region [tileX, tileY, tileW, tileH] is also passed via push +// constants so the host can dispatch each tile separately with timestamps. +// +// Compiled with: +// slangc 10_performance_optimization.slang -o shaders/slang.spv \ +// -profile spirv_1_4 -target spirv -emit-spirv-directly \ +// -fvk-use-entrypoint-name -entry heatmapMain + +// Storage image – rgba8 matches R8G8B8A8Unorm on the C++ side +[[vk::binding(0, 0)]] [[vk::image_format("rgba8")]] RWTexture2D outputImage; + +struct HeatmapPush +{ + uint kernelType; // 0=divergent, 1=non-divergent, 2=LDS, 3=wave + uint tileX; // pixel offset X for this tile + uint tileY; // pixel offset Y for this tile + uint tileW; // tile width in pixels + uint tileH; // tile height in pixels + uint frameIndex; // incremented each frame (used to animate the benchmark) +}; +[[vk::push_constant]] HeatmapPush pc; + +// --------------------------------------------------------------------------- +// Module-scope groupshared – required by Slang (must be at module scope) +// --------------------------------------------------------------------------- +groupshared float ldsData[256]; + +groupshared uint waveSlotCtr; +groupshared float wavePartials[64]; // 256 threads / min-wave-size-4 = 64 max waves + +// --------------------------------------------------------------------------- +// Heatmap color: maps a normalized intensity [0,1] to a cool→hot color ramp +// 0.0 = blue, 0.25 = cyan, 0.5 = green, 0.75 = yellow, 1.0 = red +// --------------------------------------------------------------------------- +float4 heatColor(float t) +{ + t = clamp(t, 0.0f, 1.0f); + float r = clamp(2.0f * t - 0.5f, 0.0f, 1.0f); + float g = clamp(2.0f * t, 0.0f, 1.0f) * clamp(2.0f - 2.0f * t, 0.0f, 1.0f); + float b = clamp(1.5f - 2.0f * t, 0.0f, 1.0f); + return float4(r, g, b, 1.0f); +} + +// --------------------------------------------------------------------------- +// heatmapMain – dispatched once per tile per frame +// Thread (x,y) maps to pixel (tileX + x, tileY + y) +// --------------------------------------------------------------------------- +[numthreads(16, 16, 1)] +[shader("compute")] +void heatmapMain( + uint3 groupID : SV_GroupID, + uint3 threadID : SV_GroupThreadID, + uint3 dispatchID : SV_DispatchThreadID) +{ + uint px = pc.tileX + dispatchID.x; + uint py = pc.tileY + dispatchID.y; + + uint imgW, imgH; + outputImage.GetDimensions(imgW, imgH); + bool validPixel = (px < imgW) && (py < imgH) && + (dispatchID.x < pc.tileW) && (dispatchID.y < pc.tileH); + + // Kernels 0 and 1 have no barriers — out-of-bounds threads can exit early. + // Kernels 2 and 3 contain GroupMemoryBarrierWithGroupSync: ALL threads in the + // workgroup must reach every barrier uniformly. Only skip the final image write. + if (pc.kernelType < 2u && !validPixel) + return; + + // ----------------------------------------------------------------------- + // Benchmark computation – the result drives the output color + // ----------------------------------------------------------------------- + + // Seed value that varies per pixel and per frame to avoid trivial + // compiler constant-folding of the benchmark work + float val = sin(float(px) * 0.031f + float(py) * 0.017f + float(pc.frameIndex) * 0.01f); + + float4 color; + + if (pc.kernelType == 0u) + { + // ---- Kernel 0: Divergent ---- + // Branches based on a per-thread value → produces warp divergence. + // The modulo is normalised to [0,2] with the signed-safe trick from prior work. + float result = 0.0f; + int t = int(val * 10.0f); + int branch = ((t % 3) + 3) % 3; + + if (branch == 0) + result = val * val + sqrt(abs(val)); + else if (branch == 1) + result = val * val * val - val; + else + result = sin(val) * cos(val); + + // Color: warm (yellow→red) showing it is the "slow" kernel + float intensity = abs(result); + color = float4(0.9f + 0.1f * intensity, 0.4f - 0.2f * intensity, 0.1f, 1.0f); + } + else if (pc.kernelType == 1u) + { + // ---- Kernel 1: Non-divergent ---- + // Same result as kernel 0 but computed branchlessly via lerp/step. + int t = int(val * 10.0f); + int mod3 = ((t % 3) + 3) % 3; + + float r0 = val * val + sqrt(abs(val)); + float r1 = val * val * val - val; + float r2 = sin(val) * cos(val); + + float s01 = step(0.5f, float(mod3 >= 1)); + float s12 = step(0.5f, float(mod3 >= 2)); + float result = lerp(r0, lerp(r1, r2, s12), s01); + + // Color: cool (green) showing it is the "fast" kernel + float intensity = abs(result); + color = float4(0.05f, 0.7f + 0.2f * intensity, 0.2f, 1.0f); + } + else if (pc.kernelType == 2u) + { + // ---- Kernel 2: LDS Reduction ---- + // Tree reduction using groupshared memory. + // Each 16x16 block = 256 threads; flatten to 1-D for the reduction. + uint tid = threadID.y * 16u + threadID.x; + + // Load one value per thread + ldsData[tid] = sin(float(tid) * 0.01f + val); + GroupMemoryBarrierWithGroupSync(); + + // Binary tree reduction + // NOTE: [unroll] must NOT be used here — the loop contains a + // GroupMemoryBarrierWithGroupSync() barrier, and unrolling a + // barrier-containing loop causes GPU hangs (VK_ERROR_DEVICE_LOST) + // on Intel ARL and some other Vulkan drivers. + for (uint stride = 128u; stride > 0u; stride >>= 1u) + { + if (tid < stride) + ldsData[tid] += ldsData[tid + stride]; + GroupMemoryBarrierWithGroupSync(); + } + + float groupSum = ldsData[0]; + + // Color: cyan/teal to distinguish LDS path + float intensity = clamp(abs(groupSum) / 256.0f, 0.0f, 1.0f); + color = float4(0.0f, 0.6f + 0.4f * intensity, 0.8f + 0.2f * intensity, 1.0f); + } + else + { + // ---- Kernel 3: Wave Reduction ---- + // Intra-wave sum then groupshared accumulation across waves. + uint tid = threadID.y * 16u + threadID.x; + + if (tid == 0u) + waveSlotCtr = 0u; + GroupMemoryBarrierWithGroupSync(); + + float elem = sin(float(tid) * 0.01f + val); + float waveSum = WaveActiveSum(elem); + + uint mySlot = 0u; + if (WaveIsFirstLane()) + { + InterlockedAdd(waveSlotCtr, 1u, mySlot); + wavePartials[mySlot] = waveSum; + } + GroupMemoryBarrierWithGroupSync(); + + float groupSum = 0.0f; + if (tid == 0u) + { + for (uint w = 0u; w < waveSlotCtr; ++w) + groupSum += wavePartials[w]; + } + // Broadcast groupSum to all threads via a final LDS slot + if (tid == 0u) + ldsData[0] = groupSum; + GroupMemoryBarrierWithGroupSync(); + groupSum = ldsData[0]; + + // Color: blue/violet to distinguish wave reduction path + float intensity = clamp(abs(groupSum) / 256.0f, 0.0f, 1.0f); + color = float4(0.3f + 0.3f * intensity, 0.1f, 0.7f + 0.3f * intensity, 1.0f); + } + + if (validPixel) + outputImage[int2(px, py)] = color; +} diff --git a/attachments/compute/CMakeLists.txt b/attachments/compute/CMakeLists.txt new file mode 100644 index 00000000..ea6c804b --- /dev/null +++ b/attachments/compute/CMakeLists.txt @@ -0,0 +1,242 @@ +cmake_minimum_required(VERSION 3.29) + +project(VulkanAdvancedCompute) + +list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_LIST_DIR}/../CMake") + +option(ENABLE_CPP20_MODULE "Enable C++ 20 module support for Vulkan" OFF) + +if(ENABLE_CPP20_MODULE) + set(CMAKE_CXX_SCAN_FOR_MODULES ON) +endif() + +find_package(glfw3 REQUIRED) +find_package(glm REQUIRED) +find_package(Vulkan 1.4.335 REQUIRED) +find_package(stb REQUIRED) +set(STB_INCLUDEDIR ${stb_INCLUDE_DIRS}) + +if(ENABLE_CPP20_MODULE) + add_library(VulkanCppModule) + add_library(Vulkan::cppm ALIAS VulkanCppModule) + target_compile_definitions(VulkanCppModule + PUBLIC VULKAN_HPP_DISPATCH_LOADER_DYNAMIC=1 VULKAN_HPP_NO_STRUCT_CONSTRUCTORS=1) + target_include_directories(VulkanCppModule PUBLIC "${Vulkan_INCLUDE_DIR}") + target_link_libraries(VulkanCppModule PUBLIC Vulkan::Vulkan) + set_target_properties(VulkanCppModule PROPERTIES CXX_STANDARD 20) + if(MSVC) + target_compile_options(VulkanCppModule PRIVATE + /std:c++latest /permissive- /Zc:__cplusplus /EHsc /Zc:preprocessor /translateInclude) + endif() + target_sources(VulkanCppModule PUBLIC + FILE_SET cxx_modules TYPE CXX_MODULES + BASE_DIRS "${Vulkan_INCLUDE_DIR}" + FILES "${Vulkan_INCLUDE_DIR}/vulkan/vulkan.cppm") + target_sources(VulkanCppModule PRIVATE "${Vulkan_INCLUDE_DIR}/vulkan/vulkan.cppm") +else() + add_library(VulkanCppModule INTERFACE) + add_library(Vulkan::cppm ALIAS VulkanCppModule) + target_link_libraries(VulkanCppModule INTERFACE Vulkan::Vulkan) + target_compile_definitions(VulkanCppModule + INTERFACE VULKAN_HPP_DISPATCH_LOADER_DYNAMIC=1 VULKAN_HPP_NO_STRUCT_CONSTRUCTORS=1) +endif() + +find_program(SLANGC_EXECUTABLE slangc HINTS $ENV{VULKAN_SDK}/bin REQUIRED) + +# --------------------------------------------------------------------------- +# add_compute_chapter(NAME [WINDOWED] [ENTRIES e1 e2 ...] [LIBS lib1 ...] +# [SLANG_DEFINES D1 D2 ...]) +# NAME — chapter directory prefix (also the .cpp and .slang filename) +# WINDOWED — link GLFW and define DEMO_WINDOWED +# ENTRIES — list of slangc -entry names; defaults to "compMain" +# LIBS — extra link libraries +# SLANG_DEFINES — preprocessor defines passed to slangc as -D +# --------------------------------------------------------------------------- +function(add_compute_chapter CHAPTER_NAME) + cmake_parse_arguments(ARG "WINDOWED" "" "ENTRIES;LIBS;SLANG_DEFINES" ${ARGN}) + + add_executable(${CHAPTER_NAME} ${CHAPTER_NAME}.cpp) + set_target_properties(${CHAPTER_NAME} PROPERTIES + RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/${CHAPTER_NAME} + CXX_STANDARD 20) + + target_link_libraries(${CHAPTER_NAME} Vulkan::cppm glm::glm) + target_include_directories(${CHAPTER_NAME} PRIVATE + ${STB_INCLUDEDIR} + ${CMAKE_CURRENT_SOURCE_DIR}) + + if(ENABLE_CPP20_MODULE) + target_compile_definitions(${CHAPTER_NAME} PRIVATE USE_CPP20_MODULES=1) + endif() + target_compile_definitions(${CHAPTER_NAME} PRIVATE VULKAN_HPP_HANDLE_ERROR_OUT_OF_DATE_AS_SUCCESS) + + if(ARG_WINDOWED) + target_link_libraries(${CHAPTER_NAME} glfw) + target_compile_definitions(${CHAPTER_NAME} PRIVATE DEMO_WINDOWED=1) + endif() + + if(DEFINED ARG_LIBS) + target_link_libraries(${CHAPTER_NAME} ${ARG_LIBS}) + endif() + + if(WIN32 AND ${CMAKE_GENERATOR} MATCHES "Visual Studio.*") + set_target_properties(${CHAPTER_NAME} PROPERTIES + VS_DEBUGGER_WORKING_DIRECTORY "${CMAKE_BINARY_DIR}/${CHAPTER_NAME}") + endif() + + # Build the -entry flags list (default: just compMain) + if(DEFINED ARG_ENTRIES) + set(ENTRY_FLAGS "") + foreach(E IN LISTS ARG_ENTRIES) + list(APPEND ENTRY_FLAGS -entry ${E}) + endforeach() + else() + set(ENTRY_FLAGS -entry compMain) + endif() + + # Build the -D flags list for slangc preprocessor defines + set(DEFINE_FLAGS "") + if(DEFINED ARG_SLANG_DEFINES) + foreach(D IN LISTS ARG_SLANG_DEFINES) + list(APPEND DEFINE_FLAGS -D${D}) + endforeach() + endif() + + # Compile the Slang shader if a .slang file exists alongside the .cpp + file(GLOB SLANG_SRC "${CMAKE_CURRENT_SOURCE_DIR}/${CHAPTER_NAME}.slang") + if(SLANG_SRC) + set(SHADERS_DIR ${CHAPTER_NAME}/shaders) + set(SPV_OUT ${SHADERS_DIR}/slang.spv) + + add_custom_command( + OUTPUT ${SHADERS_DIR} + COMMAND ${CMAKE_COMMAND} -E make_directory ${SHADERS_DIR}) + + add_custom_command( + OUTPUT ${SPV_OUT} + COMMAND ${SLANGC_EXECUTABLE} + ${SLANG_SRC} + -target spirv + -profile spirv_1_4 + -emit-spirv-directly + -fvk-use-entrypoint-name + ${ENTRY_FLAGS} + ${DEFINE_FLAGS} + -o slang.spv + WORKING_DIRECTORY ${SHADERS_DIR} + DEPENDS ${SHADERS_DIR} ${SLANG_SRC} + COMMENT "Compiling ${CHAPTER_NAME}.slang" + VERBATIM) + + add_custom_target(${CHAPTER_NAME}_shader DEPENDS ${SPV_OUT}) + add_dependencies(${CHAPTER_NAME} ${CHAPTER_NAME}_shader) + endif() +endfunction() + +# --------------------------------------------------------------------------- +# Demos — one per tutorial chapter, with explicit entry point lists +# --------------------------------------------------------------------------- +add_compute_chapter(02_compute_architecture + WINDOWED + ENTRIES compMain) + +add_compute_chapter(03_memory_models + WINDOWED + ENTRIES splatPass advectVelPass divergencePass jacobiPass gradientPass advectDyePass renderPass) + +add_compute_chapter(04_subgroup_operations + WINDOWED + ENTRIES physicsMain renderMain) + +add_compute_chapter(06_advanced_data_structures + WINDOWED + ENTRIES primaryRayMain shadowQueueMain) + +add_compute_chapter(07_gpu_driven_pipelines + WINDOWED + ENTRIES cullMain vertMain fragMain) + +add_compute_chapter(08_async_compute + WINDOWED + ENTRIES constraintPass vertMain fragMain) + +add_compute_chapter(09_specialized_math + WINDOWED + ENTRIES noiseMain denoiseMain) + +add_compute_chapter(10_performance_optimization + WINDOWED + ENTRIES heatmapMain) + +# --------------------------------------------------------------------------- +# Chapter 05 — OpenCL on Vulkan (special: NOT a Slang demo) +# +# This chapter demonstrates the OpenCL→Vulkan toolchain by rendering ONE OpenCL +# C kernel (05_opencl_on_vulkan.cl) two ways: +# * clspv (AOT) — compiled to julia.spv here, loaded into a raw Vulkan pipeline +# * clvk (runtime)— driven through the OpenCL 3.0 API at run time +# Both paths are optional; the demo degrades gracefully when a tool is absent so +# the rest of the project always builds. Build clspv/clvk with the +# install_dependencies_* scripts in this directory. +# --------------------------------------------------------------------------- +find_program(CLSPV_EXECUTABLE clspv) +find_path(OpenCL_INCLUDE_DIR CL/cl.h) +find_library(OpenCL_LIBRARY NAMES OpenCL) + +add_executable(05_opencl_on_vulkan 05_opencl_on_vulkan.cpp) +set_target_properties(05_opencl_on_vulkan PROPERTIES + RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/05_opencl_on_vulkan + CXX_STANDARD 20) +# Windowed app: it owns a Vulkan swapchain and presents, so it needs GLFW. +target_link_libraries(05_opencl_on_vulkan Vulkan::cppm glfw) +target_include_directories(05_opencl_on_vulkan PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}) +target_compile_definitions(05_opencl_on_vulkan PRIVATE + VULKAN_HPP_HANDLE_ERROR_OUT_OF_DATE_AS_SUCCESS) +if(ENABLE_CPP20_MODULE) + target_compile_definitions(05_opencl_on_vulkan PRIVATE USE_CPP20_MODULES=1) +endif() + +set(CH5_OUT ${CMAKE_BINARY_DIR}/05_opencl_on_vulkan) + +# The clvk path reads the kernel SOURCE at run time — copy it next to the binary +# whenever the .cl changes (keyed on the file, so edits re-copy without a relink). +add_custom_command( + OUTPUT ${CH5_OUT}/05_opencl_on_vulkan.cl + COMMAND ${CMAKE_COMMAND} -E make_directory ${CH5_OUT} + COMMAND ${CMAKE_COMMAND} -E copy_if_different + ${CMAKE_CURRENT_SOURCE_DIR}/05_opencl_on_vulkan.cl + ${CH5_OUT}/05_opencl_on_vulkan.cl + DEPENDS ${CMAKE_CURRENT_SOURCE_DIR}/05_opencl_on_vulkan.cl + COMMENT "Copying 05_opencl_on_vulkan.cl next to the binary (clvk reads it at runtime)" + VERBATIM) +add_custom_target(05_opencl_on_vulkan_cl DEPENDS ${CH5_OUT}/05_opencl_on_vulkan.cl) +add_dependencies(05_opencl_on_vulkan 05_opencl_on_vulkan_cl) + +# clvk runtime layering path: OpenCL 3.0 host API. +if(OpenCL_INCLUDE_DIR AND OpenCL_LIBRARY) + target_compile_definitions(05_opencl_on_vulkan PRIVATE HAVE_OPENCL=1) + target_include_directories(05_opencl_on_vulkan PRIVATE ${OpenCL_INCLUDE_DIR}) + target_link_libraries(05_opencl_on_vulkan ${OpenCL_LIBRARY}) + message(STATUS "Chapter 05: OpenCL found (${OpenCL_LIBRARY}) — clvk runtime path enabled") +else() + message(STATUS "Chapter 05: OpenCL headers/loader not found — clvk runtime path disabled") +endif() + +# clspv AOT path: compile the OpenCL C kernel to Vulkan-flavour SPIR-V. +if(CLSPV_EXECUTABLE) + set(CH5_SPV ${CH5_OUT}/shaders/forest.spv) + add_custom_command( + OUTPUT ${CH5_SPV} + COMMAND ${CMAKE_COMMAND} -E make_directory ${CH5_OUT}/shaders + COMMAND ${CLSPV_EXECUTABLE} -cl-std=CL1.2 --inline-entry-points + ${CMAKE_CURRENT_SOURCE_DIR}/05_opencl_on_vulkan.cl -o ${CH5_SPV} + DEPENDS ${CMAKE_CURRENT_SOURCE_DIR}/05_opencl_on_vulkan.cl + COMMENT "clspv: compiling 05_opencl_on_vulkan.cl -> forest.spv" + VERBATIM) + add_custom_target(05_opencl_on_vulkan_spv DEPENDS ${CH5_SPV}) + add_dependencies(05_opencl_on_vulkan 05_opencl_on_vulkan_spv) + target_compile_definitions(05_opencl_on_vulkan PRIVATE HAVE_CLSPV_AOT=1) + message(STATUS "Chapter 05: clspv found (${CLSPV_EXECUTABLE}) — AOT path enabled") +else() + message(STATUS "Chapter 05: clspv not found — AOT path disabled (run install_dependencies_*)") +endif() diff --git a/attachments/compute/compute_common.h b/attachments/compute/compute_common.h new file mode 100644 index 00000000..520c1f3c --- /dev/null +++ b/attachments/compute/compute_common.h @@ -0,0 +1,258 @@ +#pragma once + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if defined(__INTELLISENSE__) || !defined(USE_CPP20_MODULES) +# include +#else +import vulkan_hpp; +#endif + +#ifdef DEMO_WINDOWED +# define GLFW_INCLUDE_VULKAN +# include +#endif + +#define GLM_FORCE_RADIANS +#include +#include + +// --------------------------------------------------------------------------- +// Validation +// --------------------------------------------------------------------------- +const std::vector kValidationLayers = {"VK_LAYER_KHRONOS_validation"}; + +#ifdef NDEBUG +constexpr bool kEnableValidation = false; +#else +constexpr bool kEnableValidation = true; +#endif + +// --------------------------------------------------------------------------- +// Debug messenger callback +// --------------------------------------------------------------------------- +static VKAPI_ATTR vk::Bool32 VKAPI_CALL debugCallback( + vk::DebugUtilsMessageSeverityFlagBitsEXT severity, + vk::DebugUtilsMessageTypeFlagsEXT, + const vk::DebugUtilsMessengerCallbackDataEXT* pData, + void*) +{ + if (severity >= vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning) + std::cerr << "[VK] " << pData->pMessage << '\n'; + return vk::False; +} + +// --------------------------------------------------------------------------- +// Headless Vulkan context – everything a compute-only demo needs +// --------------------------------------------------------------------------- +struct HeadlessContext +{ + vk::raii::Context context; + vk::raii::Instance instance = nullptr; + vk::raii::DebugUtilsMessengerEXT debugMessenger = nullptr; + vk::raii::PhysicalDevice physicalDevice = nullptr; + vk::raii::Device device = nullptr; + uint32_t computeQueueFamily = ~0u; + vk::raii::Queue computeQueue = nullptr; + vk::raii::CommandPool commandPool = nullptr; + + void init(const char* appName = "ComputeDemo") + { + // Instance + vk::ApplicationInfo appInfo{ + .pApplicationName = appName, + .applicationVersion = VK_MAKE_VERSION(1,0,0), + .pEngineName = "No Engine", + .engineVersion = VK_MAKE_VERSION(1,0,0), + .apiVersion = vk::ApiVersion14}; + + std::vector layers; + std::vector extensions; + if (kEnableValidation) { + layers.push_back("VK_LAYER_KHRONOS_validation"); + extensions.push_back(vk::EXTDebugUtilsExtensionName); + } + + vk::InstanceCreateInfo instCI{ + .pApplicationInfo = &appInfo, + .enabledLayerCount = static_cast(layers.size()), + .ppEnabledLayerNames = layers.data(), + .enabledExtensionCount = static_cast(extensions.size()), + .ppEnabledExtensionNames = extensions.data()}; + instance = vk::raii::Instance(context, instCI); + + // Debug messenger + if (kEnableValidation) { + vk::DebugUtilsMessengerCreateInfoEXT dmCI{ + .messageSeverity = + vk::DebugUtilsMessageSeverityFlagBitsEXT::eVerbose | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eWarning | + vk::DebugUtilsMessageSeverityFlagBitsEXT::eError, + .messageType = + vk::DebugUtilsMessageTypeFlagBitsEXT::eGeneral | + vk::DebugUtilsMessageTypeFlagBitsEXT::eValidation | + vk::DebugUtilsMessageTypeFlagBitsEXT::ePerformance, + .pfnUserCallback = &debugCallback}; + debugMessenger = instance.createDebugUtilsMessengerEXT(dmCI); + } + + // Physical device – pick first that has a compute queue + for (auto& pd : instance.enumeratePhysicalDevices()) { + auto qfps = pd.getQueueFamilyProperties(); + for (uint32_t i = 0; i < qfps.size(); ++i) { + if (qfps[i].queueFlags & vk::QueueFlagBits::eCompute) { + physicalDevice = pd; + computeQueueFamily = i; + break; + } + } + if (computeQueueFamily != ~0u) break; + } + if (computeQueueFamily == ~0u) + throw std::runtime_error("No compute queue family found"); + + // Logical device + float priority = 1.0f; + vk::DeviceQueueCreateInfo qCI{ + .queueFamilyIndex = computeQueueFamily, + .queueCount = 1, + .pQueuePriorities = &priority}; + + // Feature chain: base → 1.1 → 1.2 → 1.3 + // ScalarBlockLayout and BufferDeviceAddress are promoted into Vulkan 1.2; + // they must be set in VkPhysicalDeviceVulkan12Features, not in separate structs. + vk::PhysicalDeviceVulkan13Features v13Features{ + .synchronization2 = true}; + vk::PhysicalDeviceVulkan12Features v12Features{ + .pNext = &v13Features, + .drawIndirectCount = true, + .shaderFloat16 = true, + .shaderInt8 = true, + .scalarBlockLayout = true, + .bufferDeviceAddress = true}; + // variablePointers* are required by clspv-generated SPIR-V (Chapter 05). + // They are harmless for the other headless chapters. + vk::PhysicalDeviceVulkan11Features v11Features{ + .pNext = &v12Features, + .variablePointersStorageBuffer = true, + .variablePointers = true, + .shaderDrawParameters = true}; + vk::PhysicalDeviceFeatures2 features2{ + .pNext = &v11Features, + .features = {.shaderInt64 = true}}; + + std::vector devExtensions; + + vk::DeviceCreateInfo devCI{ + .pNext = &features2, + .queueCreateInfoCount = 1, + .pQueueCreateInfos = &qCI, + .enabledExtensionCount = static_cast(devExtensions.size()), + .ppEnabledExtensionNames = devExtensions.data()}; + device = vk::raii::Device(physicalDevice, devCI); + computeQueue = vk::raii::Queue(device, computeQueueFamily, 0); + + // Command pool + vk::CommandPoolCreateInfo poolCI{ + .flags = vk::CommandPoolCreateFlagBits::eResetCommandBuffer, + .queueFamilyIndex = computeQueueFamily}; + commandPool = vk::raii::CommandPool(device, poolCI); + } + + // ----------------------------------------------------------------------- + // Buffer helpers + // ----------------------------------------------------------------------- + [[nodiscard]] uint32_t findMemoryType(uint32_t typeBits, vk::MemoryPropertyFlags props) const + { + auto memProps = physicalDevice.getMemoryProperties(); + for (uint32_t i = 0; i < memProps.memoryTypeCount; ++i) + if ((typeBits & (1u << i)) && + (memProps.memoryTypes[i].propertyFlags & props) == props) + return i; + throw std::runtime_error("No suitable memory type"); + } + + void createBuffer(vk::DeviceSize size, vk::BufferUsageFlags usage, + vk::MemoryPropertyFlags props, + vk::raii::Buffer& buf, vk::raii::DeviceMemory& mem, + vk::MemoryAllocateFlags allocFlags = {}) const + { + buf = vk::raii::Buffer(device, vk::BufferCreateInfo{ + .size = size, + .usage = usage, + .sharingMode = vk::SharingMode::eExclusive}); + + auto req = buf.getMemoryRequirements(); + + vk::MemoryAllocateFlagsInfo flagsInfo{.flags = allocFlags}; + vk::MemoryAllocateInfo allocInfo{ + .pNext = allocFlags ? &flagsInfo : nullptr, + .allocationSize = req.size, + .memoryTypeIndex = findMemoryType(req.memoryTypeBits, props)}; + mem = vk::raii::DeviceMemory(device, allocInfo); + buf.bindMemory(mem, 0); + } + + // One-shot command buffer + [[nodiscard]] vk::raii::CommandBuffer beginOneShot() const + { + vk::CommandBufferAllocateInfo allocInfo{ + .commandPool = *commandPool, + .level = vk::CommandBufferLevel::ePrimary, + .commandBufferCount = 1}; + auto cb = std::move(vk::raii::CommandBuffers(device, allocInfo).front()); + cb.begin(vk::CommandBufferBeginInfo{ + .flags = vk::CommandBufferUsageFlagBits::eOneTimeSubmit}); + return cb; + } + + void endOneShot(const vk::raii::CommandBuffer& cb) const + { + cb.end(); + vk::SubmitInfo si{.commandBufferCount = 1, .pCommandBuffers = &*cb}; + computeQueue.submit(si); + computeQueue.waitIdle(); + } + + // ----------------------------------------------------------------------- + // SPIR-V loader + // ----------------------------------------------------------------------- + static std::vector readSPV(const std::string& path) + { + std::ifstream f(path, std::ios::ate | std::ios::binary); + if (!f.is_open()) throw std::runtime_error("Cannot open: " + path); + std::vector buf(f.tellg()); + f.seekg(0); f.read(buf.data(), static_cast(buf.size())); + return buf; + } + + [[nodiscard]] vk::raii::ShaderModule loadShader(const std::string& path) const + { + auto code = readSPV(path); + return vk::raii::ShaderModule(device, vk::ShaderModuleCreateInfo{ + .codeSize = code.size(), + .pCode = reinterpret_cast(code.data())}); + } +}; + +// --------------------------------------------------------------------------- +// Simple wall-clock timer +// --------------------------------------------------------------------------- +struct Timer +{ + using Clock = std::chrono::high_resolution_clock; + Clock::time_point t0; + void start() { t0 = Clock::now(); } + double ms() const { + return std::chrono::duration(Clock::now() - t0).count(); + } +}; diff --git a/attachments/compute/install_dependencies_linux.sh b/attachments/compute/install_dependencies_linux.sh new file mode 100755 index 00000000..f328ffc5 --- /dev/null +++ b/attachments/compute/install_dependencies_linux.sh @@ -0,0 +1,169 @@ +#!/bin/bash +# Install dependencies for the Advanced Vulkan Compute tutorial demos. +# The compute demos require: GLFW (windowed demos), GLM, stb. +# They do NOT require tinyobjloader, tinygltf, or KTX. +# slangc must be provided by the Vulkan SDK (1.4.335+). +# +# Chapter 05 (OpenCL on Vulkan) requires the OpenCL ICD loader + headers and the +# clspv compiler + clvk runtime. These are ALWAYS built by this script (there is +# no opt-out): the Chapter 05 sample cannot run without clspv. Building clspv +# pulls in LLVM, so the first run can take 20-40 minutes. +# +# This script takes no options. clspv/clvk are built into ~/opencl-on-vulkan. + +set -e + +TOOLS_DIR="${HOME}/opencl-on-vulkan" + +echo "Installing dependencies for Advanced Vulkan Compute demos..." + +detect_package_manager() { + if command -v apt-get &> /dev/null; then echo "apt" + elif command -v dnf &> /dev/null; then echo "dnf" + elif command -v pacman &> /dev/null; then echo "pacman" + else echo "unknown" + fi +} + +PM=$(detect_package_manager) + +case $PM in + apt) + echo "Detected Ubuntu/Debian" + sudo apt-get update + sudo apt-get install -y \ + build-essential \ + cmake \ + ninja-build \ + clang \ + libglfw3-dev \ + libglm-dev \ + libstb-dev \ + libxxf86vm-dev \ + libxi-dev \ + opencl-headers \ + ocl-icd-opencl-dev \ + clinfo + ;; + dnf) + echo "Detected Fedora/RHEL" + sudo dnf install -y \ + gcc-c++ \ + cmake \ + ninja-build \ + clang \ + glfw-devel \ + glm-devel \ + libXxf86vm-devel \ + libXi-devel \ + opencl-headers \ + ocl-icd-devel \ + clinfo + # stb is header-only; install manually if not available + if ! rpm -q stb-devel &>/dev/null; then + echo "stb not in dnf — installing headers manually..." + sudo mkdir -p /usr/local/include + curl -fsSL https://raw.githubusercontent.com/nothings/stb/master/stb_image.h \ + -o /tmp/stb_image.h + sudo cp /tmp/stb_image.h /usr/local/include/ + fi + ;; + pacman) + echo "Detected Arch Linux" + sudo pacman -S --needed --noconfirm \ + base-devel \ + cmake \ + ninja \ + clang \ + glfw-x11 \ + glm \ + stb \ + opencl-headers \ + ocl-icd \ + clinfo + ;; + *) + echo "Unsupported package manager. Install manually:" + echo " cmake >= 3.29, ninja, clang, libglfw3-dev, libglm-dev, libstb-dev" + exit 1 + ;; +esac + +# --------------------------------------------------------------------------- +# Chapter 05 (REQUIRED): build clspv (OpenCL C -> SPIR-V) and clvk (OpenCL 3.0 +# on Vulkan). The Chapter 05 sample cannot run without these. +# --------------------------------------------------------------------------- +echo "" +echo "=======================================================" +echo " Building clspv + clvk into $TOOLS_DIR (REQUIRED)" +echo " clspv pulls in LLVM/Clang — first build can take 20-40 min" +echo "=======================================================" +mkdir -p "$TOOLS_DIR" +NPROC=$(nproc 2>/dev/null || echo 4) + +# --- clspv ----------------------------------------------------------------- +if [ ! -x "$TOOLS_DIR/clspv/build/bin/clspv" ]; then + if [ ! -d "$TOOLS_DIR/clspv" ]; then + git clone --depth 1 https://github.com/google/clspv.git "$TOOLS_DIR/clspv" + fi + # clspv fetches its own pinned LLVM/Clang/SPIRV deps. + python3 "$TOOLS_DIR/clspv/utils/fetch_sources.py" --shallow || \ + python3 "$TOOLS_DIR/clspv/utils/fetch_sources.py" + cmake -S "$TOOLS_DIR/clspv" -B "$TOOLS_DIR/clspv/build" -G Ninja \ + -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ + ninja -C "$TOOLS_DIR/clspv/build" -j "$NPROC" clspv +fi + +# --- clvk ------------------------------------------------------------------ +if [ ! -f "$TOOLS_DIR/clvk/build/libOpenCL.so" ]; then + if [ ! -d "$TOOLS_DIR/clvk" ]; then + git clone https://github.com/kpet/clvk.git "$TOOLS_DIR/clvk" + fi + git -C "$TOOLS_DIR/clvk" submodule update --init --recursive + "$TOOLS_DIR/clvk/external/clspv/utils/fetch_sources.py" --shallow || \ + "$TOOLS_DIR/clvk/external/clspv/utils/fetch_sources.py" || true + # CMAKE_CXX_EXTENSIONS=OFF avoids a PCH gnu++17-vs-c++17 mismatch in the + # bundled SPIRV-LLVM-Translator (otherwise the build fails to compile). + cmake -S "$TOOLS_DIR/clvk" -B "$TOOLS_DIR/clvk/build" -G Ninja \ + -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \ + -DCMAKE_CXX_EXTENSIONS=OFF + ninja -C "$TOOLS_DIR/clvk/build" -j "$NPROC" +fi + +# --- register clvk as an OpenCL ICD so clGetPlatformIDs finds it ----------- +CLVK_LIB=$(find "$TOOLS_DIR/clvk/build" -name 'libOpenCL.so*' | head -1) +if [ -n "$CLVK_LIB" ]; then + sudo mkdir -p /etc/OpenCL/vendors + echo "$CLVK_LIB" | sudo tee /etc/OpenCL/vendors/clvk.icd > /dev/null + echo "Registered clvk ICD: $CLVK_LIB" +fi + +echo "" +echo "clspv: $TOOLS_DIR/clspv/build/bin/clspv" +echo "clvk : $CLVK_LIB" +echo "" +echo "Add clspv to PATH so CMake finds it (add this to your shell profile):" +echo " export PATH=\"$TOOLS_DIR/clspv/build/bin:\$PATH\"" +echo "Verify the layered OpenCL platform is visible:" +echo " clinfo -l # should list a 'clvk' platform" +echo "" +echo "=======================================================" +echo " Vulkan SDK (with slangc) must be installed separately" +echo "=======================================================" +echo "Download from: https://vulkan.lunarg.com/" +echo "" +echo "Quick install:" +echo " VULKAN_VERSION=\$(curl -s https://vulkan.lunarg.com/sdk/latest/linux.txt)" +echo " curl -O https://sdk.lunarg.com/sdk/download/\$VULKAN_VERSION/linux/vulkansdk-linux-x86_64-\$VULKAN_VERSION.tar.xz" +echo " mkdir -p ~/vulkansdk && tar -xJf vulkansdk-linux-x86_64-\$VULKAN_VERSION.tar.xz -C ~/vulkansdk" +echo " source ~/vulkansdk/\$VULKAN_VERSION/setup-env.sh" +echo "" +echo "Verify slangc is available after SDK install:" +echo " slangc --version" +echo "" +echo "Build the compute demos:" +echo " cd attachments/compute" +echo " cmake -B build -G Ninja -DCMAKE_BUILD_TYPE=Release" +echo " cmake --build build --parallel" +echo "" +echo "Dependencies installed successfully." diff --git a/attachments/compute/install_dependencies_windows.bat b/attachments/compute/install_dependencies_windows.bat new file mode 100644 index 00000000..550b1188 --- /dev/null +++ b/attachments/compute/install_dependencies_windows.bat @@ -0,0 +1,95 @@ +@echo off +REM Install dependencies for the Advanced Vulkan Compute tutorial demos (Windows). +REM Prerequisites: +REM - vcpkg installed and VCPKG_INSTALLATION_ROOT set (https://github.com/microsoft/vcpkg) +REM - Vulkan SDK (with slangc) from https://vulkan.lunarg.com/ +REM +REM The compute demos require: GLFW (windowed demos), GLM, stb. +REM They do NOT require tinyobjloader, tinygltf, or KTX. + +setlocal + +echo Installing dependencies for Advanced Vulkan Compute demos... +echo. + +REM ------------------------------------------------------------------- +REM Check for vcpkg +REM ------------------------------------------------------------------- +if "%VCPKG_INSTALLATION_ROOT%"=="" ( + echo ERROR: VCPKG_INSTALLATION_ROOT is not set. + echo Please install vcpkg from https://github.com/microsoft/vcpkg and set: + echo set VCPKG_INSTALLATION_ROOT=C:\path\to\vcpkg + echo. + exit /b 1 +) + +if not exist "%VCPKG_INSTALLATION_ROOT%\vcpkg.exe" ( + echo ERROR: vcpkg.exe not found at %VCPKG_INSTALLATION_ROOT%\vcpkg.exe + exit /b 1 +) + +echo Using vcpkg at: %VCPKG_INSTALLATION_ROOT% +echo. + +REM ------------------------------------------------------------------- +REM Configure binary caching (speeds up CI and repeat installs) +REM ------------------------------------------------------------------- +if "%VCPKG_BINARY_SOURCES%"=="" ( + set VCPKG_BINARY_SOURCES=clear;files,%TEMP%\vcpkg-cache,readwrite +) + +REM ------------------------------------------------------------------- +REM Install packages +REM ------------------------------------------------------------------- +echo Installing packages via vcpkg (x64-windows)... +REM 'opencl' provides the OpenCL ICD loader + headers used by Chapter 05. +"%VCPKG_INSTALLATION_ROOT%\vcpkg.exe" install ^ + glfw3 ^ + glm ^ + stb ^ + opencl ^ + --triplet=x64-windows + +if %ERRORLEVEL% NEQ 0 ( + echo ERROR: vcpkg install failed. + exit /b %ERRORLEVEL% +) + +echo. +echo ================================================================ +echo Vulkan SDK (with slangc) must be installed separately +echo ================================================================ +echo Download the Vulkan SDK installer from: https://vulkan.lunarg.com/ +echo Install it, then make sure VULKAN_SDK is set in your environment. +echo. +echo Verify slangc is available after SDK install: +echo slangc --version +echo. +echo ================================================================ +echo Chapter 05 (OpenCL on Vulkan): clspv + clvk (REQUIRED) +echo ================================================================ +echo The Chapter 05 sample cannot run without clspv. clspv and clvk are not on +echo vcpkg, so build them from source in a Visual Studio "x64 Native Tools" +echo command prompt (clspv pulls in LLVM; the first build takes a while): +echo. +echo git clone --depth 1 https://github.com/google/clspv.git +echo cd clspv ^&^& python utils\fetch_sources.py --shallow +echo cmake -B build -G Ninja -DCMAKE_BUILD_TYPE=Release ^&^& ninja -C build clspv +echo REM add %CD%\build\bin to PATH so CMake finds clspv.exe +echo. +echo git clone https://github.com/kpet/clvk.git +echo cd clvk ^&^& git submodule update --init --recursive +echo external\clspv\utils\fetch_sources.py --shallow +echo cmake -B build -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_CXX_EXTENSIONS=OFF ^&^& ninja -C build +echo REM register OpenCL.dll from clvk\build as an ICD, or place it next to the exe +echo. +echo Verify the layered platform is visible with: clinfo -l (look for 'clvk') +echo. +echo Build the compute demos: +echo cd attachments\compute +echo cmake -B build -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE="%VCPKG_INSTALLATION_ROOT%\scripts\buildsystems\vcpkg.cmake" +echo cmake --build build --config Release --parallel +echo. +echo Dependencies installed successfully. + +endlocal diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc index 81e70ddb..fc8bd8c9 100644 --- a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc @@ -42,4 +42,4 @@ Throughout this section, we will focus on two key metrics that determine how wel We'll start by diving into the 3D grid system and seeing exactly how it maps to physical hardware. From there, we'll learn how to calculate theoretical occupancy and use engine tools to monitor real-world utilization. Finally, we'll master the scalar block layouts to maximize your data throughput. -xref:../introduction.adoc[Previous: Introduction] | xref:02_workgroups_and_invocations.adoc[Next: Workgroups and Invocations] +xref:Advanced_Vulkan_Compute/introduction.adoc[Previous: Introduction] | xref:Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc[Next: Workgroups and Invocations] diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc index 269db9f5..1e99a213 100644 --- a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc @@ -80,4 +80,4 @@ Note the use of "rounding up" (`(width + 15) / 16`). This ensures that if your i Understanding how workgroups map to hardware is the foundation of GPU compute. But mapping work to hardware is only part of the story; we also need to keep that hardware busy. In the next section, we'll talk about **Occupancy** and how to hide the massive latency of VRAM. -xref:01_introduction.adoc[Previous: Introduction] | xref:03_occupancy_and_latency_hiding.adoc[Next: Occupancy and Latency Hiding] +xref:Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc[Previous: Introduction] | xref:Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc[Next: Occupancy and Latency Hiding] diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc index d3844d8b..e394a1bb 100644 --- a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc @@ -67,4 +67,4 @@ By tracking metrics like **ValuUtilization** (AMD) or **SM Active** (NVIDIA), yo Now that we know how to keep the GPU busy, we need to make sure that when it *is* busy, it's being efficient. In the final section of this chapter, we'll look at **Scalar Layouts**—a Vulkan 1.4 feature that allows us to pack our data tightly and maximize the bandwidth we've worked so hard to hide. -xref:02_workgroups_and_invocations.adoc[Previous: Workgroups and Invocations] | xref:04_vulkan_1_4_scalar_layouts.adoc[Next: Vulkan 1.4 Scalar Layouts] \ No newline at end of file +xref:Advanced_Vulkan_Compute/02_Compute_Architecture/02_workgroups_and_invocations.adoc[Previous: Workgroups and Invocations] | xref:Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc[Next: Vulkan 1.4 Scalar Layouts] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc index d8cc88b2..aad3c8e7 100644 --- a/en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc +++ b/en/Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc @@ -117,4 +117,4 @@ By understanding these low-level architectural details, you've moved beyond "wri In the next chapter, we'll take these concepts even further by looking at the **Vulkan Memory Model** and how to safely synchronize data between thousands of threads. -xref:03_occupancy_and_latency_hiding.adoc[Previous: Occupancy and Latency Hiding] | xref:../03_Memory_Models/01_introduction.adoc[Next: Memory Models and Consistency] \ No newline at end of file +xref:Advanced_Vulkan_Compute/02_Compute_Architecture/03_occupancy_and_latency_hiding.adoc[Previous: Occupancy and Latency Hiding] | xref:Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc[Next: Memory Models and Consistency] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc index dbab97ea..9a92633b 100644 --- a/en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc @@ -31,4 +31,4 @@ Efficient memory synchronization is the difference between a high-performance si We'll start by looking at the theoretical foundation: the **Vulkan Memory Model**. While it might seem abstract at first, it is the key to writing portable, robust compute code that works on every GPU from a smartphone to a high-end workstation. -xref:../02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc[Previous: Scalar Layouts] | xref:02_vulkan_memory_model.adoc[Next: The Vulkan Memory Model] \ No newline at end of file +xref:Advanced_Vulkan_Compute/02_Compute_Architecture/04_vulkan_1_4_scalar_layouts.adoc[Previous: Scalar Layouts] | xref:Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc[Next: The Vulkan Memory Model] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc index c41d85a8..a67a7d58 100644 --- a/en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc @@ -65,4 +65,4 @@ In Vulkan, data races result in **Undefined Behavior**. This doesn't just mean y Next, we'll see how to apply these concepts to **Shared Memory (LDS)**, which is much faster than global VRAM. -xref:01_introduction.adoc[Previous: Introduction] | xref:03_shared_memory_lds.adoc[Next: Shared Memory (LDS)] +xref:Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc[Previous: Introduction] | xref:Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc[Next: Shared Memory (LDS)] diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc index 4c8ad667..75692e6f 100644 --- a/en/Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc @@ -99,4 +99,4 @@ Crucially, **shared memory is not coherent between workgroups**. If you need to In the next section, we'll see how to balance these barriers to keep your pipeline as full as possible. -xref:02_vulkan_memory_model.adoc[Previous: The Vulkan Memory Model] | xref:04_memory_consistency.adoc[Next: Memory Consistency] \ No newline at end of file +xref:Advanced_Vulkan_Compute/03_Memory_Models/02_vulkan_memory_model.adoc[Previous: The Vulkan Memory Model] | xref:Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc[Next: Memory Consistency] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc b/en/Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc index 97054fa1..b6573174 100644 --- a/en/Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc +++ b/en/Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc @@ -63,4 +63,4 @@ We've covered the fundamentals of how GPUs execute code and how they manage memo In the next chapter, we'll dive into **Subgroup Operations**. By learning how to communicate between threads *within* a bundle, we can bypass shared memory altogether and perform high-speed data exchange directly through registers. -xref:03_shared_memory_lds.adoc[Previous: Shared Memory (LDS)] | xref:../04_Subgroup_Operations/01_introduction.adoc[Next: Why Subgroups Matter] \ No newline at end of file +xref:Advanced_Vulkan_Compute/03_Memory_Models/03_shared_memory_lds.adoc[Previous: Shared Memory (LDS)] | xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc[Next: Why Subgroups Matter] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc index 3df76ee6..21b5264f 100644 --- a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc @@ -30,4 +30,4 @@ This leads to: We'll start by looking at the fundamental building blocks of subgroup communication: **Shuffles** and **Broadcasts**. -xref:../03_Memory_Models/04_memory_consistency.adoc[Previous: Memory Consistency] | xref:02_cross_invocation_communication.adoc[Next: Cross-Invocation Communication] \ No newline at end of file +xref:Advanced_Vulkan_Compute/03_Memory_Models/04_memory_consistency.adoc[Previous: Memory Consistency] | xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc[Next: Cross-Invocation Communication] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc index 05afea3c..ea53c8b7 100644 --- a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc @@ -73,4 +73,4 @@ While it's tempting to use subgroup operations everywhere, remember that they on However, a "subgroup-first" approach is often the fastest. Perform as much work as possible within the subgroup, and only use LDS when you absolutely must communicate with another subgroup. -xref:01_introduction.adoc[Previous: Introduction to Subgroups] | xref:03_subgroup_partitioning.adoc[Next: Subgroup Partitioning] \ No newline at end of file +xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc[Previous: Introduction to Subgroups] | xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc[Next: Subgroup Partitioning] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc index 4a978381..052e5b3e 100644 --- a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc @@ -70,4 +70,4 @@ By combining these operations, you can write "wave-aware" code that adapts to ho In the next section, we'll look at how these same subgroup concepts apply to accessing memory and resources through **Non-Uniform Indexing**. -xref:02_cross_invocation_communication.adoc[Previous: Shuffles and Broadcasts] | xref:04_non_uniform_indexing.adoc[Next: Non-Uniform Indexing] \ No newline at end of file +xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/02_cross_invocation_communication.adoc[Previous: Shuffles and Broadcasts] | xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc[Next: Non-Uniform Indexing] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc index cd39de8f..71c27695 100644 --- a/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc +++ b/en/Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc @@ -70,4 +70,4 @@ Subgroup operations represent a paradigm shift in GPU programming. By moving fro In the next chapter, we'll step back and look at how these Vulkan compute concepts interact with the broader ecosystem, starting with **OpenCL on Vulkan**. -xref:03_subgroup_partitioning.adoc[Previous: Subgroup Partitioning] | xref:../05_OpenCL_on_Vulkan/01_introduction.adoc[Next: OpenCL on Vulkan] \ No newline at end of file +xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/03_subgroup_partitioning.adoc[Previous: Subgroup Partitioning] | xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc[Next: OpenCL on Vulkan] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc index 4d3662ad..4d802fe7 100644 --- a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc @@ -28,4 +28,4 @@ What makes this interesting from a Vulkan developer's perspective is the **advan In this chapter, we'll explore the two primary tools: **AOT** (Ahead-of-Time) compilation using `clspv`, and **Runtime Layering** using `clvk`. -xref:../04_Subgroup_Operations/04_non_uniform_indexing.adoc[Previous: Non-Uniform Indexing] | xref:02_setup_and_installation.adoc[Next: Setup and Installation] \ No newline at end of file +xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/04_non_uniform_indexing.adoc[Previous: Non-Uniform Indexing] | xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc[Next: Setup and Installation] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc index 000a9d9e..56a02ba1 100644 --- a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc @@ -9,7 +9,7 @@ To run OpenCL code on Vulkan, you'll need a few extra tools in your development Both `clspv` and `clvk` are open-source projects hosted on GitHub. They are not currently part of the standard Vulkan SDK, so you will need to fetch and build them yourself, although pre-built binaries are occasionally available for certain platforms. - **clspv**: link:https://github.com/google/clspv[github.com/google/clspv] -- **clvk**: link:https://github.com/khrnxs/clvk[github.com/khrnxs/clvk] +- **clvk**: link:https://github.com/kpet/clvk[github.com/kpet/clvk] == Building clspv @@ -39,7 +39,7 @@ Once the build is complete, you'll have a `clspv` executable in your `build` fol [source,bash] ---- -git clone --recursive https://github.com/khrnxs/clvk.git +git clone --recursive https://github.com/kpet/clvk.git cd clvk mkdir build && cd build cmake .. -G Ninja -DCMAKE_BUILD_TYPE=Release @@ -73,4 +73,4 @@ Once you've built the tools, verify your installation: Now that your environment is ready, let's look at how to use `clspv` to compile your first OpenCL kernel for Vulkan. -xref:01_introduction.adoc[Previous: OpenCL on Vulkan] | xref:03_clspv_pipeline.adoc[Next: The clspv Pipeline] \ No newline at end of file +xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc[Previous: OpenCL on Vulkan] | xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc[Next: The clspv Pipeline] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc index 2bb3908b..6fbe0d92 100644 --- a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc @@ -55,4 +55,4 @@ Vulkan 1.4's improved support for **Buffer Device Address** has made this even e In the next section, we'll look at how to handle **Kernel Portability** and ensure your code runs correctly across different vendors. -xref:02_setup_and_installation.adoc[Previous: Setup and Installation] | xref:04_kernel_portability.adoc[Next: Kernel Portability] \ No newline at end of file +xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/02_setup_and_installation.adoc[Previous: Setup and Installation] | xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc[Next: Kernel Portability] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc index b3e63662..3ee09382 100644 --- a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc @@ -43,4 +43,4 @@ The real power of this pipeline is its ability to handle legacy code. Many produ In the next section, we'll explore **clvk**, which takes this a step further by providing a full OpenCL 3.0 API implementation on top of Vulkan. -xref:03_clspv_pipeline.adoc[Previous: The clspv Pipeline] | xref:05_clvk_and_layering.adoc[Next: clvk and Layering] \ No newline at end of file +xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/03_clspv_pipeline.adoc[Previous: The clspv Pipeline] | xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[Next: clvk and Layering] \ No newline at end of file diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc index a76c32e0..3ad22693 100644 --- a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc @@ -37,6 +37,6 @@ Since the actual computation happens in the native Vulkan driver, the primary co `clvk` supports most of the OpenCL 3.0 specification. However, its compatibility depends on the features supported by your Vulkan driver. If your driver supports Vulkan 1.4 with **Descriptor Indexing**, **Variable Pointers**, and **Buffer Device Address**, `clvk` will be able to support almost all OpenCL features. -In the next chapter, we'll move from the OpenCL ecosystem to **Advanced Data Structures on the GPU** — GPU-resident trees, lock-free linked lists, and raw Buffer Device Addresses. +In the next section, we'll put both tools to work in a single, self-contained sample that runs the **same OpenCL kernel two ways onto Vulkan** — once via `clspv` ahead-of-time, once via `clvk` at run time — and proves they produce identical results. -xref:04_kernel_portability.adoc[Previous: Kernel Portability] | xref:../06_Advanced_Data_Structures/01_introduction.adoc[Next: Advanced Data Structures] +xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/04_kernel_portability.adoc[Previous: Kernel Portability] | xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/06_a_practical_sample.adoc[Next: A Practical Sample] diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/06_a_practical_sample.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/06_a_practical_sample.adoc new file mode 100644 index 00000000..ed82e794 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/06_a_practical_sample.adoc @@ -0,0 +1,139 @@ +:pp: {plus}{plus} + += A Practical Sample: Vulkan Rendering Powered by OpenCL + +The previous sections introduced the two tools in the OpenCL-on-Vulkan toolchain: +`clspv` (Ahead-of-Time compilation) and `clvk` (runtime layering). This section +ties them together with a real-time, interactive sample. + +It is important to get the framing right. This is **not** "an OpenCL program that +happens to run on Vulkan". It is the opposite: a normal **Vulkan application** — +window, swapchain, present loop, free-fly camera — that **draws its scene with an +OpenCL kernel**. In the default mode the kernel is compiled by `clspv` and runs as +the Vulkan engine's own compute shader, writing the presented buffer directly with +no copy. That is the real value of the layered ecosystem: a Vulkan engine can tap +into the huge body of existing OpenCL kernels and run them as first-class shaders. + +The complete sources live in `attachments/compute`: + +- `05_opencl_on_vulkan.cl` — the OpenCL C kernel (a raymarched *instanced forest*) +- `05_opencl_on_vulkan.cpp` — the windowed Vulkan host application +- `CMakeLists.txt` — wires up the optional `clspv` and OpenCL detection + +The scene is a small lesson in instancing: a *single* tree distance field is +repeated across an infinite grid (`round(p.xz / cell)`), and a per-cell hash gives +every instance its own height, canopy size, colour, and the occasional clearing. +You fly through it in real time with `WASD`/`EQ` and mouse-drag to look around. + +== The Two Backends + +The application can drive the kernel through either backend, chosen at startup +(override with `--backend=aot` or `--backend=clvk`): + +[cols="1,3"] +|=== +|Backend |How the OpenCL kernel reaches the screen + +|**clspv AOT** (default, zero-copy) +|The OpenCL C kernel is compiled by `clspv` to `forest.spv` at build time and run +as the Vulkan engine's *own* compute shader. It writes straight into the Vulkan +storage buffer that is presented — the OpenCL kernel is literally "just another +shader" in the Vulkan pipeline, with no copies and no second API at run time. + +|**clvk runtime** (`--backend=clvk`) +|The same `.cl` is compiled at run time by `clvk` (OpenCL 3.0 layered on Vulkan). +clvk does not implement `cl_khr_external_memory`, so its result is bridged into the +Vulkan buffer with a per-frame `clEnqueueReadBuffer`. It showcases the runtime +layering tool at the cost of one copy per frame. +|=== + +== The Kernel as a Vulkan Shader (zero-copy) + +The default path is the cleanest demonstration of "Vulkan using OpenCL". Because +`clspv` turns the OpenCL C kernel into ordinary Vulkan SPIR-V, the Vulkan app +loads it like any compute shader and points it at the buffer it is about to +present — the kernel writes the final pixels directly into Vulkan-owned memory: + +[source,cpp] +---- +// forest.spv was produced from 05_opencl_on_vulkan.cl by clspv at build time. +vk::PipelineShaderStageCreateInfo stage{ + .stage = vk::ShaderStageFlagBits::eCompute, + .module = *shaderModule, + .pName = "render"}; // clspv names the entry point after the kernel +// binding 0 = Params, binding 1 = the storage buffer that present() copies to screen +cb.dispatch((W + 15) / 16, (H + 15) / 16, 1); +---- + +There is no interop layer, no FD export, no second device: the OpenCL kernel runs +inside the same Vulkan command buffer flow as the rest of the engine. + +== The clvk Runtime Path + +Why not share the buffer zero-copy with `clvk` too? Because mainline `clvk` does +not expose `cl_khr_external_memory`, so there is no way to import a `VkBuffer` into +its OpenCL context. The runtime path therefore computes into an ordinary OpenCL +buffer and reads it back into the Vulkan-visible memory each frame: + +[source,cpp] +---- +clEnqueueNDRangeKernel(queue, kernel, 2, nullptr, global, local, 0, nullptr, nullptr); +clEnqueueReadBuffer(queue, outMem, CL_TRUE, 0, bytes, hostMappedVkBuffer, 0, nullptr, nullptr); +// ... vkCmdCopyBufferToImage(vkBuffer -> intermediate) ; blit -> swapchain ; present +---- + +This is the state of the tooling today: `clspv` gives you true zero-copy +integration, while `clvk` gives you runtime compilation of unmodified OpenCL host +code at the cost of a bridge copy. + +== The Portable Kernel + +The kernel still follows the portability rules from the previous sections so its +descriptor mapping is deterministic and it runs unchanged on both backends: + +[source,c] +---- +typedef struct { + int width, height; + float camX, camY, camZ; // free-fly camera position + float camYaw, camPitch, fog; +} Params; + +#define MAX_STEPS 128 // compile-time constant — see the note below + +__attribute__((reqd_work_group_size(16, 16, 1))) +__kernel void render(__global const Params* P, __global uint* outRGBA) { + const int x = get_global_id(0), y = get_global_id(1); + if (x >= P->width || y >= P->height) return; // guard the rounded-up global size + for (int i = 0; i < MAX_STEPS; ++i) { /* raymarch the instanced-forest SDF */ } + // ... shade, then: + outRGBA[y * P->width + x] = r | (g << 8) | (b << 16) | (0xFFu << 24); +} +---- + +[NOTE] +==== +The raymarch step count is a **compile-time constant**, not a kernel parameter. +`clspv` miscompiles a raymarch loop whose bound is loaded from a storage buffer — +its structured-control-flow pass cannot prove the loop terminates, and the +resulting shader hangs the GPU. A native OpenCL driver compiles the same dynamic +bound fine, so this is a portability gotcha worth knowing: keep loop bounds +constant in kernels you intend to run through `clspv`/`clvk`. +==== + +* **Only buffer arguments** → `clspv` maps the two `__global` pointers to a + predictable layout (`set=0,binding=0` = Params, `set=0,binding=1` = output), + which the AOT path's hand-built `VkDescriptorSetLayout` matches exactly. +* **A `uint` output** (packed RGBA8) keeps everything to 32-bit storage access, + so no special 8-bit-storage Vulkan feature is needed. +* **A pinned work-group size** plus host round-up keeps the NDRange uniform. +* **No cross-invocation state** — each invocation raymarches one pixel — so the + same kernel runs unchanged on both backends (any difference between them is + just float rounding between two different GPUs). + +Fly through the forest with `WASD` (move), `E`/`Q` (up/down), mouse-drag (look), +`Shift` (boost), `R` (reset), `ESC` (quit). With the default backend every pixel +you see was produced by an OpenCL kernel running as the Vulkan engine's own +compute shader — no copies, no second API. + +xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[Previous: clvk and Layering] | xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/07_clspv_for_production.adoc[Next: Developing with clspv] diff --git a/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/07_clspv_for_production.adoc b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/07_clspv_for_production.adoc new file mode 100644 index 00000000..4a7b60f9 --- /dev/null +++ b/en/Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/07_clspv_for_production.adoc @@ -0,0 +1,199 @@ += clspv for Production: OpenCL C as Vulkan SPIR-V + +When you compile an OpenCL kernel with `clspv` for a Vulkan engine, you are not +wrapping OpenCL inside Vulkan or running a compatibility layer at runtime. You are +using SPIR-V as a *shared intermediate language* — the same binary format Vulkan +consumes for every shader — and `clspv` is the translator from OpenCL C into that +format. + +This distinction matters because SPIR-V has two different dialects. The OpenCL +ecosystem defines its own set of SPIR-V capabilities (execution models, storage +classes, built-in variables, extended instructions) and so does Vulkan. They +overlap in the middle, but neither side is a strict subset of the other. + +== Two Dialects of the Same Format + +image::images/spirv_dialects_venn.svg[SPIR-V Dialects Venn Diagram — OpenCL and Vulkan overlap in a shared common region,780] + +`clspv` targets the *Vulkan dialect* — it emits the `GLCompute` execution model +with `StorageBuffer` and `Workgroup` storage classes, not the OpenCL `Kernel` +execution model. The generated SPIR-V is valid Vulkan shader code, loadable by +`vkCreateShaderModule` like any compute shader you would write in GLSL or HLSL. + +This is why the AOT path works at all: there is no special treatment at the Vulkan +driver level. The driver sees an ordinary compute shader and has no idea it came +from OpenCL C. + +== What Compiles Cleanly + +The core of OpenCL C maps directly to Vulkan compute shaders: + +* **Buffer arguments** (`__global` pointers) → `StorageBuffer` descriptors. + Argument *n* → `set=0, binding=n`. Predictable, deterministic, inspectable with + `--descriptormap`. +* **Shared memory** (fixed-size `__local`) → `Workgroup` storage class arrays — + the same memory your GLSL `shared` variables live in. +* **NDRange built-ins** (`get_global_id`, `get_local_id`, `get_group_id`, + `get_global_size`) → `gl_GlobalInvocationID`, `gl_LocalInvocationID`, + `gl_WorkGroupID`, etc. +* **Math built-ins** (`sin`, `cos`, `sqrt`, `fma`, `clamp`, `mix`, `dot`, `cross`, + `native_sqrt`, …) → `GLSL.std.450` extended instructions. The mapping is + nearly 1-to-1. +* **Integer atomics** on global buffers (`atomic_add`, `atomic_cmpxchg`, etc.) → + `OpAtomicIAdd`, `OpAtomicCompareExchange`. +* **Barriers** (`barrier(CLK_LOCAL_MEM_FENCE | CLK_GLOBAL_MEM_FENCE)`) → + `OpControlBarrier` with the appropriate scopes. +* **Subgroup operations** (via `cl_khr_sub_groups`) → the same `OpGroupNon- + Uniform*` instructions GLSL subgroup extensions emit. + +== What Does Not Survive the Translation + +Some OpenCL C features are absent from the Vulkan SPIR-V dialect, or require +Vulkan hardware features that are not universally available. + +=== No printf + +`printf` in a Vulkan compute shader has no standardized mechanism. `clspv` does +not support it. The idiomatic replacement is a debug-output storage buffer: write +diagnostic values into a `__global uint*` (or structured buffer) and read them back +on the host after the kernel finishes. + +=== Limited double / float64 + +`double` and `double`-typed built-ins require the `shaderFloat64` Vulkan device +feature, which is absent on many mobile and integrated GPUs. `clspv` disables +double support by default. Kernels that use `double` must: + +. Pass `-DCMAKE_DOUBLE_SUPPORT=ON` (or equivalent) to `clspv`, and +. Verify `VkPhysicalDeviceFeatures::shaderFloat64 == VK_TRUE` at device selection. + +For portability, write kernels in `float` and reserve `double` for desktop-only +deployments where you have verified the device feature. + +=== Pipes and Device-side Enqueue + +`read_pipe`, `write_pipe`, and `enqueue_kernel` are OpenCL 2.0 features with no +Vulkan equivalent. `clspv` targets OpenCL 1.2 semantics (`-cl-std=CL1.2`) and +does not compile these constructs. + +=== Dynamic Loop Bounds from Buffers + +This is one of the most important production gotchas. `clspv`'s structured- +control-flow pass must be able to prove that every loop terminates so it can +produce valid structured SPIR-V. When a loop bound is loaded from a storage +buffer at runtime, the pass cannot make that proof, and the resulting shader +typically hangs the GPU. + +A native OpenCL driver (NVIDIA CUDA, AMD ROCm) compiles dynamic bounds without +complaint because it does not require structured control flow. The kernel will +work on those platforms and silently produce a GPU hang via `clspv`. + +The rule: **loop bounds must be compile-time constants in kernels destined for +`clspv`.** Use `#define`, `constexpr`, or SPIR-V specialisation constants — +never a value read from a descriptor. + +[WARNING] +==== +This failure mode produces a **silent GPU hang**, not a compilation error or a +validation layer message. If a kernel that worked under a native OpenCL driver +hangs under the `clspv` AOT path, a dynamic loop bound is the first thing to check. +==== + +=== No Variable-Length Arrays + +OpenCL C allows `__local float tmp[n]` where `n` is a kernel argument. `clspv` +requires `__local` array sizes to be fixed at compile time (they map to statically- +sized `Workgroup` arrays in SPIR-V). Factor dynamic sizing into a `#define` or +specialisation constant instead. + +=== Vulkan-Only Capabilities You Cannot Reach from OpenCL C + +The right side of the Venn diagram — ray tracing, mesh shaders, variable-rate +shading, cooperative matrices, fragment operations — is not accessible from OpenCL +C at all. Kernels that need those capabilities must be written in GLSL/HLSL/SLANG +and compiled with a Vulkan-aware compiler. The clspv AOT path is the right choice +for compute-only workloads; it is not a path to the full Vulkan shader ecosystem. + +== Argument Mapping in Production + +The deterministic descriptor layout is `clspv`'s most useful production property: +every `__global` buffer argument *n* maps to a storage buffer at `set=0, binding=n`, +and scalar (POD) arguments are grouped into a uniform buffer at a predictable +binding. Never rely on this from memory — always generate and commit the map: + +[source,bash] +---- +clspv -cl-std=CL1.2 --inline-entry-points \ + --descriptormap=forest.map \ + forest.cl -o forest.spv +---- + +The `.map` file is the authoritative specification of your kernel's interface. +Check it into version control alongside the `.cl` source and treat divergence +between the map and your `VkDescriptorSetLayout` as a build error. + +=== POD Arguments and Push Constants + +By default `clspv` puts scalar arguments (e.g. `float scale, int steps`) into a +uniform buffer. If you prefer push constants — lower latency, no descriptor +update — pass `--pod-pushconstant`: + +[source,bash] +---- +clspv --pod-pushconstant -cl-std=CL1.2 --descriptormap=kernel.map kernel.cl -o kernel.spv +---- + +The `.map` file will show `pushconstant` offsets instead of bindings, and your +`VkPipelineLayout` must declare a matching `VkPushConstantRange`. Either approach +is correct; pick one and commit the map so the host code can follow it. + +== Specialization Constants + +When you need a value that is fixed per-dispatch but should remain changeable +without recompilation (work-group tile size, algorithm variant, feature toggle), +`clspv` supports SPIR-V specialization constants via a `clspv_builtin` attribute. +This is preferable to `#define` for values the engine varies at runtime, and +avoids the dynamic-bound problem because the value is still a compile-time +constant from the shader's perspective: + +[source,c] +---- +int __attribute__((annotate("clspv,spec_constant,0,0"))) kMaxSteps; +---- + +The two integers after `spec_constant` are the descriptor set and binding of the +spec constant in the generated SPIR-V. Set the value via +`VkSpecializationInfo` at pipeline creation time, with no shader recompilation. + +== Required Vulkan Device Features + +`clspv`-generated SPIR-V uses pointer arithmetic internally, which requires two +Vulkan 1.1 features that are not enabled by default: + +[source,cpp] +---- +vk::PhysicalDeviceVulkan11Features vk11{ + .variablePointersStorageBuffer = true, + .variablePointers = true}; +---- + +Add this to your device-feature chain. Validation will catch a missing feature +immediately; the chapter's `compute_common.h` enables both for all samples. + +== A Production Checklist + +Before shipping a kernel through the `clspv` AOT path: + +[%checklist] +- [ ] All loop bounds are compile-time constants (`#define`, specialisation const). +- [ ] No `printf` — replaced with a debug output buffer. +- [ ] `double` usage audited; `shaderFloat64` verified if present. +- [ ] `--descriptormap` generated and committed; host layout matches exactly. +- [ ] `variablePointers` + `variablePointersStorageBuffer` in device feature chain. +- [ ] Entry point name in `VkPipelineShaderStageCreateInfo::pName` matches the + OpenCL kernel name, **not** `"main"`. +- [ ] Work-group size fixed via `reqd_work_group_size` and matched in the dispatch + round-up on the host. +- [ ] SPIR-V validated with `spirv-val forest.spv` in CI. + +xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/06_a_practical_sample.adoc[Previous: A Practical Sample] | xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc[Next: Advanced Data Structures] diff --git a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc index 37d0387a..2f5dc100 100644 --- a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc @@ -29,4 +29,4 @@ GPU-resident data structures are the foundation of modern high-performance rende By the end of this chapter, you'll understand how to stop treating the GPU as a "dumb array processor" and start treating it as a platform for autonomous, complex data management. -xref:../05_OpenCL_on_Vulkan/05_clvk_and_layering.adoc[Previous: clvk and Layering] | xref:02_gpu_resident_trees.adoc[Next: GPU-Resident Trees] +xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/07_clspv_for_production.adoc[Previous: clspv for Production] | xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc[Next: GPU-Resident Trees] diff --git a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc index 8ef13156..05d75859 100644 --- a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc +++ b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc @@ -101,4 +101,4 @@ uint allocateNode() { While this works, it can be slow if thousands of threads are all hitting the same counter. In the next section, we'll look at how **64-bit Atomics** and **Global Atomic Management** can optimize this process for massive scale. -xref:01_introduction.adoc[Previous: Introduction to Advanced Data Structures] | xref:03_global_atomic_management.adoc[Next: Global Atomic Management] +xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc[Previous: Introduction to Advanced Data Structures] | xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc[Next: Global Atomic Management] diff --git a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc index 73b54eda..6680265f 100644 --- a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc +++ b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc @@ -125,4 +125,4 @@ As we discussed in Chapter 4, you can use **Subgroup Operations** to **coalesce* This simple optimization can improve the throughput of global atomics by 32x or 64x, making complex data structures viable for even the most demanding real-time applications. -xref:02_gpu_resident_trees.adoc[Previous: GPU-Resident Trees] | xref:04_device_addressable_buffers.adoc[Next: Device-Addressable Buffers] +xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/02_gpu_resident_trees.adoc[Previous: GPU-Resident Trees] | xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Next: Device-Addressable Buffers] diff --git a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc index 572ae3dd..a52dfa3f 100644 --- a/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc +++ b/en/Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc @@ -98,4 +98,4 @@ By combining 64-bit atomics, subgroup operations, and raw buffer device addresse In the next chapter, we'll see how to take this a step further and use these structures to drive the entire rendering pipeline directly from the GPU: **Indirect Dispatch and GPU-Driven Pipelines**. -xref:03_global_atomic_management.adoc[Previous: Global Atomic Management] | xref:../07_GPU_Driven_Pipelines/01_introduction.adoc[Next: Indirect Dispatch] +xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/03_global_atomic_management.adoc[Previous: Global Atomic Management] | xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc[Next: Indirect Dispatch] diff --git a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc index bf879170..9025074a 100644 --- a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc @@ -34,4 +34,4 @@ By moving the "decision-making" to the GPU, we can: In this chapter, we'll learn how to build these autonomous pipelines, starting with the fundamental building block: **Indirect Dispatch**. -xref:../06_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Previous: Device-Addressable Buffers] | xref:02_indirect_dispatch.adoc[Next: Indirect Dispatch] +xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/04_device_addressable_buffers.adoc[Previous: Device-Addressable Buffers] | xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc[Next: Indirect Dispatch] diff --git a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc index 8cb65324..dfaa7b21 100644 --- a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc +++ b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc @@ -94,4 +94,4 @@ This approach is much more efficient than always dispatching for the "maximum" n In the next section, we'll look at how the GPU can go beyond just changing its dispatch size and start generating its own **Command Chains**. -xref:01_introduction.adoc[Previous: Introduction to GPU-Driven Pipelines] | xref:03_gpu_side_command_generation.adoc[Next: GPU-Side Command Generation] +xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc[Previous: Introduction to GPU-Driven Pipelines] | xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc[Next: GPU-Side Command Generation] diff --git a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc index a982eba8..2cd76f4c 100644 --- a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc +++ b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc @@ -38,4 +38,4 @@ This is the standard architecture for many modern, high-end rendering engines. I In the next section, we'll look at the final piece of the puzzle: **Multi-Draw Indirect (MDI)**, which bridges our compute analysis to the graphics pipeline. -xref:02_indirect_dispatch.adoc[Previous: Indirect Dispatch] | xref:04_multi_draw_indirect_mdi.adoc[Next: Multi-Draw Indirect (MDI)] +xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/02_indirect_dispatch.adoc[Previous: Indirect Dispatch] | xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Next: Multi-Draw Indirect (MDI)] diff --git a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc index 1775ca08..1bc1d7e5 100644 --- a/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc +++ b/en/Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc @@ -44,4 +44,4 @@ By mastering **Indirect Dispatch**, **GPU-Side Command Generation**, and **Multi In the next chapter, we'll look at how to coordinate these heavy compute workloads with your graphics rendering using **Asynchronous Compute Orchestration**. -xref:03_gpu_side_command_generation.adoc[Previous: GPU-Side Command Generation] | xref:../08_Asynchronous_Compute/01_introduction.adoc[Next: Asynchronous Compute Orchestration] +xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/03_gpu_side_command_generation.adoc[Previous: GPU-Side Command Generation] | xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc[Next: Asynchronous Compute Orchestration] diff --git a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc index 69fe20f4..a7909ea4 100644 --- a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc @@ -17,4 +17,4 @@ In this chapter, we're going to move beyond the simple "one queue for all" model Orchestrating these workloads requires a shift in how we think about the GPU's timeline. It's no longer just a linear sequence of commands, but a multi-lane highway where different types of traffic can move at different speeds, occasionally merging or yielding to ensure the overall throughput is maximized. -xref:../07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Previous: Multi-Draw Indirect (MDI)] | xref:02_concurrent_execution.adoc[Next: Concurrent Execution] +xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/04_multi_draw_indirect_mdi.adoc[Previous: Multi-Draw Indirect (MDI)] | xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc[Next: Concurrent Execution] diff --git a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc index b72ed05b..92532568 100644 --- a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc +++ b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc @@ -61,4 +61,4 @@ The real "magic" happens when we use **Semaphore-based synchronization** (using Remember, though, that not all hardware is created equal. Some mobile GPUs have unified hardware for compute and graphics, where "concurrency" might just mean the scheduler interleaved the tasks. High-end desktop GPUs, on the other hand, often have dedicated compute pipes that can run entirely in parallel with the graphics engines. Profiling is your only way to know if your orchestration is truly delivering the performance gains you expect. -xref:01_introduction.adoc[Previous: Introduction] | xref:03_timeline_semaphores.adoc[Next: Timeline Semaphores] +xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc[Previous: Introduction] | xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc[Next: Timeline Semaphores] diff --git a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc index 5571693c..3cc102b0 100644 --- a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc +++ b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc @@ -47,4 +47,4 @@ In an asynchronous compute setup, you often have multiple streams of work with c Using binary semaphores for this would require a complex web of "Signal A -> Wait A -> Signal B -> Wait B". With timeline semaphores, you simply have a single "Engine Timeline". Every task signals its completion by incrementing the counter, and every dependent task waits for its specific prerequisite value. This drastically simplifies the orchestration logic and reduces the overhead of semaphore management. -xref:02_concurrent_execution.adoc[Previous: Concurrent Execution] | xref:04_queue_priority.adoc[Next: Queue Priority] +xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/02_concurrent_execution.adoc[Previous: Concurrent Execution] | xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc[Next: Queue Priority] diff --git a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc index 7c22474d..177e1214 100644 --- a/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc +++ b/en/Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc @@ -36,4 +36,4 @@ Another critical consideration is **Queue Family** (a group of queues with simil In practice, managing queue priorities is a balancing act. Used correctly, it's a powerful tool for ensuring that your engine remains responsive and that the most critical tasks are always handled with the urgency they require. This orchestration is the hallmark of a truly advanced Vulkan engine—moving beyond just "doing the work" to "doing the work in the right order at the right time." -xref:03_timeline_semaphores.adoc[Previous: Timeline Semaphores] | xref:../09_Specialized_Math/01_introduction.adoc[Next: Specialized Math] +xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/03_timeline_semaphores.adoc[Previous: Timeline Semaphores] | xref:Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc[Next: Specialized Math] diff --git a/en/Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc b/en/Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc index 37524f59..bc354cb6 100644 --- a/en/Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc @@ -9,4 +9,4 @@ Whether you're building a fluid simulation that requires solving large systems o In this chapter, we're going to dive into how these specialized math units work. We'll explore how to use the `cooperative_matrix` types in Slang and GLSL, and we'll see how to leverage **Mixed Precision**—using FP16 or Int8 for calculations while maintaining accuracy where it counts. This is about more than just speed; it's about utilizing the full potential of modern GPU silicon for high-performance computing tasks. -xref:../08_Asynchronous_Compute/04_queue_priority.adoc[Previous: Queue Priority] | xref:02_cooperative_matrices.adoc[Next: Cooperative Matrices] +xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/04_queue_priority.adoc[Previous: Queue Priority] | xref:Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc[Next: Cooperative Matrices] diff --git a/en/Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc b/en/Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc index 3e841ef4..9ee9b87f 100644 --- a/en/Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc +++ b/en/Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc @@ -119,4 +119,4 @@ The physical dimensions (latexmath:[M, N, K]) are not arbitrary. You must query By leveraging these specialized units, you can achieve throughput that is often an order of magnitude higher than what's possible with standard floating-point units. This makes cooperative matrices essential for any performance-critical linear algebra on the GPU. -xref:01_introduction.adoc[Previous: Introduction] | xref:03_mixed_precision.adoc[Next: Mastering Mixed Precision] +xref:Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc[Previous: Introduction] | xref:Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc[Next: Mastering Mixed Precision] diff --git a/en/Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc b/en/Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc index 8e318da7..426e5a9c 100644 --- a/en/Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc +++ b/en/Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc @@ -100,4 +100,4 @@ Managing this requires a technique known as **Loss Scaling**. You multiply your By mastering mixed precision, you're not just "squeezing out more performance"; you're being smarter about how you use the hardware's resources. Whether you're optimizing a fluid simulation or a real-time signal processing engine, these techniques are essential for pushing the boundaries of what's possible on modern GPUs. -xref:02_cooperative_matrices.adoc[Previous: Cooperative Matrices] | xref:../10_Performance_Optimization/01_introduction.adoc[Next: Performance Optimization] +xref:Advanced_Vulkan_Compute/09_Specialized_Math/02_cooperative_matrices.adoc[Previous: Cooperative Matrices] | xref:Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc[Next: Performance Optimization] diff --git a/en/Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc index 3403a6f3..36272280 100644 --- a/en/Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc @@ -25,4 +25,4 @@ By the end of this chapter, you'll be equipped with the methodology to move from 2. **The Divergence Audit**: Techniques for visualizing and refactoring divergent branching logic. [horizontal] -*Previous:* xref:../09_Specialized_Math/03_mixed_precision.adoc[Mastering Mixed Precision] | *Next:* xref:02_instruction_throughput.adoc[Instruction Throughput Analysis] +*Previous:* xref:Advanced_Vulkan_Compute/09_Specialized_Math/03_mixed_precision.adoc[Mastering Mixed Precision] | *Next:* xref:Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc[Instruction Throughput Analysis] diff --git a/en/Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc index fbd953e7..8ee29f89 100644 --- a/en/Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc +++ b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc @@ -46,4 +46,4 @@ However, be careful! Higher occupancy isn't always better. If your occupancy is Optimization is an iterative process. You profile, identify the bottleneck, apply a targeted fix, and then profile again. This is how you eventually arrive at a truly optimized solution that makes the most of the GPU's massive parallel potential. -xref:01_introduction.adoc[Previous: Introduction] | xref:03_divergence_audit.adoc[Next: Divergence Audit] +xref:Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc[Previous: Introduction] | xref:Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc[Next: Divergence Audit] diff --git a/en/Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc index d2df99f1..86547ed5 100644 --- a/en/Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc +++ b/en/Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc @@ -61,4 +61,4 @@ If your divergence is caused by processing different types of data (e.g., in a r By conducting regular divergence audits, you can identify the "hidden" costs in your compute kernels and refactor them into more efficient, SIMD-friendly patterns. This is the difference between code that "just runs" and code that truly masters the GPU's architecture. -xref:02_instruction_throughput.adoc[Previous: Instruction Throughput Analysis] | xref:../11_Diagnostics_and_Refinement/01_introduction.adoc[Next: Diagnostics and Refinement] +xref:Advanced_Vulkan_Compute/10_Performance_Optimization/02_instruction_throughput.adoc[Previous: Instruction Throughput Analysis] | xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc[Next: Diagnostics and Refinement] diff --git a/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc index 0c9dc4d5..ee563e1c 100644 --- a/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc +++ b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc @@ -25,4 +25,4 @@ Whether you're struggling to vectorize a naive loop or looking for a more effici 1. **Compute Validation**: Setting up and using GPU-Assisted Validation to catch memory errors and using `printf` for shader debugging. 2. **Assistant-Led Optimization**: Leveraging AI to refactor naive compute kernels into wave-aware, high-performance patterns. -xref:../10_Performance_Optimization/03_divergence_audit.adoc[Previous: Divergence Audit] | xref:02_compute_validation.adoc[Next: Compute Validation] +xref:Advanced_Vulkan_Compute/10_Performance_Optimization/03_divergence_audit.adoc[Previous: Divergence Audit] | xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc[Next: Compute Validation] diff --git a/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc index 35c8be38..ac78fdb3 100644 --- a/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc +++ b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc @@ -70,4 +70,4 @@ When a validation error or a `printf` occurs, the output can be verbose. Look fo While GAV and `printf` have a significant performance cost, they are indispensable for development. They turn the "black box" of the GPU into a transparent environment where you can build complex, reliable compute pipelines with confidence. -xref:01_introduction.adoc[Previous: Introduction] | xref:03_assistant_led_optimization.adoc[Next: AI-Assisted Optimization] +xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc[Previous: Introduction] | xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Next: AI-Assisted Optimization] diff --git a/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc index a9974b00..1d1c957f 100644 --- a/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc +++ b/en/Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc @@ -64,4 +64,4 @@ It's crucial to remember that an AI assistant is just that—an **assistant**. W As we move toward the final conclusion of this series, we've seen how modern tools like GPU-Assisted Validation and AI-led refactoring can transform the compute development workflow. In the next section, we'll summarize everything we've learned and look ahead to the future of high-performance Vulkan compute. -xref:02_compute_validation.adoc[Previous: Compute Validation] | xref:../conclusion.adoc[Next: Series Conclusion] +xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/02_compute_validation.adoc[Previous: Compute Validation] | xref:Advanced_Vulkan_Compute/conclusion.adoc[Next: Series Conclusion] diff --git a/en/Advanced_Vulkan_Compute/conclusion.adoc b/en/Advanced_Vulkan_Compute/conclusion.adoc index aa718f15..0b51198b 100644 --- a/en/Advanced_Vulkan_Compute/conclusion.adoc +++ b/en/Advanced_Vulkan_Compute/conclusion.adoc @@ -49,4 +49,4 @@ Thank you for following along with this series. We've moved from "making pixels Happy Hacking! -xref:11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Previous: Assistant-Led Optimization] | xref:../00_Introduction.adoc[Back to Home] +xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/03_assistant_led_optimization.adoc[Previous: Assistant-Led Optimization] | xref:00_Introduction.adoc[Back to Home] diff --git a/en/Advanced_Vulkan_Compute/introduction.adoc b/en/Advanced_Vulkan_Compute/introduction.adoc index 95466b34..fda2e60e 100644 --- a/en/Advanced_Vulkan_Compute/introduction.adoc +++ b/en/Advanced_Vulkan_Compute/introduction.adoc @@ -49,15 +49,15 @@ Let's dive into the world of high-performance GPU computing! == Chapters -* xref:02_Compute_Architecture/01_introduction.adoc[The Compute Architecture and Execution Model] -* xref:03_Memory_Models/01_introduction.adoc[Memory Models and Consistency] -* xref:04_Subgroup_Operations/01_introduction.adoc[Subgroup Operations: The Hidden Power] -* xref:05_OpenCL_on_Vulkan/01_introduction.adoc[Heterogeneous Ecosystem: OpenCL on Vulkan] -* xref:06_Advanced_Data_Structures/01_introduction.adoc[Advanced Data Structures on the GPU] -* xref:07_GPU_Driven_Pipelines/01_introduction.adoc[Indirect Dispatch and GPU-Driven Pipelines] -* xref:08_Asynchronous_Compute/01_introduction.adoc[Asynchronous Compute Orchestration] -* xref:09_Specialized_Math/01_introduction.adoc[Cooperative Matrices and Specialized Math] -* xref:10_Performance_Optimization/01_introduction.adoc[Performance Auditing and Optimization] -* xref:11_Diagnostics_and_Refinement/01_introduction.adoc[Diagnostics and AI-Assisted Compute Refinement] - -xref:11_Compute_Shader.adoc[Previous: Basic Compute Shaders] | xref:02_Compute_Architecture/01_introduction.adoc[Next: Compute Architecture] \ No newline at end of file +* xref:Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc[The Compute Architecture and Execution Model] +* xref:Advanced_Vulkan_Compute/03_Memory_Models/01_introduction.adoc[Memory Models and Consistency] +* xref:Advanced_Vulkan_Compute/04_Subgroup_Operations/01_introduction.adoc[Subgroup Operations: The Hidden Power] +* xref:Advanced_Vulkan_Compute/05_OpenCL_on_Vulkan/01_introduction.adoc[Heterogeneous Ecosystem: OpenCL on Vulkan] +* xref:Advanced_Vulkan_Compute/06_Advanced_Data_Structures/01_introduction.adoc[Advanced Data Structures on the GPU] +* xref:Advanced_Vulkan_Compute/07_GPU_Driven_Pipelines/01_introduction.adoc[Indirect Dispatch and GPU-Driven Pipelines] +* xref:Advanced_Vulkan_Compute/08_Asynchronous_Compute/01_introduction.adoc[Asynchronous Compute Orchestration] +* xref:Advanced_Vulkan_Compute/09_Specialized_Math/01_introduction.adoc[Cooperative Matrices and Specialized Math] +* xref:Advanced_Vulkan_Compute/10_Performance_Optimization/01_introduction.adoc[Performance Auditing and Optimization] +* xref:Advanced_Vulkan_Compute/11_Diagnostics_and_Refinement/01_introduction.adoc[Diagnostics and AI-Assisted Compute Refinement] + +xref:11_Compute_Shader.adoc[Previous: Basic Compute Shaders] | xref:Advanced_Vulkan_Compute/02_Compute_Architecture/01_introduction.adoc[Next: Compute Architecture] \ No newline at end of file diff --git a/images/spirv_dialects_venn.svg b/images/spirv_dialects_venn.svg new file mode 100644 index 00000000..36e7c350 --- /dev/null +++ b/images/spirv_dialects_venn.svg @@ -0,0 +1,90 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + SPIR-V + + + + + + + + + + + + + + + OpenCL + dialect + + + pipes + device-side enqueue + printf + Kernel exec model + CrossWorkGroup + + + common + GLCompute + StorageBuffer + math built-ins + atomics + barriers + subgroups + + + Vulkan + dialect + + + ray tracing + mesh shaders + push constants + variable-rate shading + fragment ops + + + clspv targets this region + + From eca4ae0bd435e552f13ec3843d9e7ad1435ed1b2 Mon Sep 17 00:00:00 2001 From: swinston Date: Fri, 12 Jun 2026 01:51:03 -0700 Subject: [PATCH 5/5] Fix for the BVH cornell box missing geometry and update the performance optimization to output ASCII instead of UTF-8 char. --- attachments/compute/06_advanced_data_structures.cpp | 8 ++++---- attachments/compute/10_performance_optimization.cpp | 4 ++-- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/attachments/compute/06_advanced_data_structures.cpp b/attachments/compute/06_advanced_data_structures.cpp index 1a40f971..977eebee 100644 --- a/attachments/compute/06_advanced_data_structures.cpp +++ b/attachments/compute/06_advanced_data_structures.cpp @@ -209,10 +209,10 @@ static int buildBVH(std::vector& nodes, return nodeIdx; } - // Reserve this node's slot, recurse for children - // Children must be created after this node, so indices are nodeIdx+1... etc. - node.leftChild = buildBVH(nodes, tris, offset, leftCount, depth + 1); - // Re-fetch reference since nodes may have been reallocated: + // Use nodes[nodeIdx] (stable index) for both children — the 'node' reference + // becomes dangling after push_back reallocates the vector during the left + // child's recursive call. + nodes[nodeIdx].leftChild = buildBVH(nodes, tris, offset, leftCount, depth + 1); nodes[nodeIdx].rightChild = buildBVH(nodes, tris, offset + leftCount, rightCount, depth + 1); nodes[nodeIdx].triOffset = -1; nodes[nodeIdx].triCount = 0; diff --git a/attachments/compute/10_performance_optimization.cpp b/attachments/compute/10_performance_optimization.cpp index 602c0e86..0b03db0e 100644 --- a/attachments/compute/10_performance_optimization.cpp +++ b/attachments/compute/10_performance_optimization.cpp @@ -958,11 +958,11 @@ class HeatmapApp } const char *names[4] = {"Divergent", "Non-divergent", "LDS-reduce", "Wave-reduce"}; - std::cout << "[frame " << m_frameCount << "] avg tile GPU time (µs):\n"; + std::cout << "[frame " << m_frameCount << "] avg tile GPU time (us):\n"; for (int q = 0; q < 4; ++q) { double avgUs = (cnt[q] > 0) ? sumTime[q] / cnt[q] / 1000.0 : 0.0; - std::cout << " Q" << q << " " << names[q] << ": " << avgUs << " µs\n"; + std::cout << " Q" << q << " " << names[q] << ": " << avgUs << " us\n"; } }