clspv
VkFFT
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clspv | VkFFT | |
---|---|---|
8 | 37 | |
575 | 1,443 | |
2.4% | - | |
8.9 | 8.1 | |
4 days ago | about 1 month ago | |
LLVM | C++ | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
clspv
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Vcc – The Vulkan Clang Compiler
See https://github.com/google/clspv for an OpenCL implementation on Vulkan Compute. There are plenty of quirks involved because the two standards use different varieties of SPIR-V ("kernels" vs. "shaders") and provide different guarantees (Vulkan Compute doesn't care much about numerical accuracy). The Mesa folks are also looking into this as part of their RustiCL (a modern OpenCL implementation) and Zink (implementing OpenGL and perhaps OpenCL itself on Vulkan) projects.
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AMD's CDNA 3 Compute Architecture
Vulkan Compute backends for numerical compute (as typified by both OpenCL and SYCL) are challenging, you can look at Google's cspv https://github.com/google/clspv project for the nitty gritty details. The lowest-effort path is actually via some combination of Rocm (for hardware that AMD bothers to support themselves) and the Mesa project's Rusticl backend (for everything else).
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WSL with CUDA Support
D3D12 has more compute features than Vulkan has. It works out for DXVK because games often don’t use those, but it’ll cause much more issues with CLon12.
By the way, if you are ready to have a _limited_ implementation without a full feature set because of Vulkan API limitations, clvk is a thing. The list of limitations of that approach is at https://github.com/google/clspv/blob/master/docs/OpenCLCOnVu...
tldr: Vulkan and OpenCL SPIR-V dialects are different, and the former has significant limitations affecting this use case
- Resources for Vulkan GPGPU searched
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Low overhead C++ interface for Apple's Metal API
For OpenCL on DX12, the test suite doesn't pass yet. Every Khronos OpenCL 1.2 CTS test passes on at least one hardware driver, but there's none that pass them all. That is why CLon12 isn't submitted to Khronos's compliant products list yet.
The pointer semantics that Vulkan has aren't very amenable to implementing a compliant OpenCL implementation on top of. There are also some other limitatons: https://github.com/google/clspv/blob/master/docs/OpenCLCOnVu....
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[Hardware Unboxed] - Apple M1 Pro Review - Is It Really Faster than Intel/AMD?
Vulkan is much more limited, notably because of Vulkan's SPIR-V dialect limitations. That makes a compliant OpenCL 1.2 impl on top of Vulkan impossible. (see: https://github.com/google/clspv/blob/master/docs/OpenCLCOnVulkan.md)
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Cross Platform GPU-Capable Framework?
OpenCL really is your best bet for a cross-platform GPU-capable framework. OpenCL 3.0 cleared out a lot of the cruft from OpenCL 2.x so it's seeing a lot more adoption. The most cross-platform solution is still OpenCL 1.2, largely for MacOS, but OpenCL 3.0 is becoming more and more common for Windows and Linux and multiple devices. Even on platforms without native OpenCL support there are compatibility layers that implement OpenCL on top of DirectX (OpenCLOn12) or Vulkan (clvk and clspv).
VkFFT
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[P] - VkFFT now supports quad precision (double-double) FFT computation on GPU
Hello, I am the creator of the VkFFT - GPU Fast Fourier Transform library for Vulkan/CUDA/HIP/OpenCL/Level Zero and Metal. In the latest update, I have added support for quad-precision double-double emulation for FFT calculation on most modern GPUs. I understand that modern ML is going in the opposite low-precision direction, but I still think that it may be useful to have this functionality at least for some prototyping and development of concepts.
- VkFFT now supports quad precision (double-double) FFT computation on GPU
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VkFFT: Vulkan/CUDA/Hip/OpenCL/Level Zero/Metal Fast Fourier Transform Library
Not quite what I asked for, but close enough for now...
https://github.com/DTolm/VkFFT/discussions/126
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Implementing complex numbers (and FFT) elegantly with just algebraic datatypes (no machine floats)
Source - I have made a somewhat functional programming-like FFT library (https://github.com/DTolm/VkFFT/tree/develop) which also operates on abstract data containers. Maybe it can be interesting to you from the algorithmic point of view.
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how does Vulkan compare to CUDA?
VkFFT is a use-case I've heard of where Vulkan-Compute is faster than its Cuda and OpenCL counter-part: https://github.com/DTolm/VkFFT
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VkFFT now supports Apple Metal API - M1 Pro GPU FFT benchmarking
Hello, I am the creator of the VkFFT - GPU Fast Fourier Transform library for Vulkan/CUDA/HIP/OpenCL and Level Zero. In the latest update, I have added support for Apple Metal API, which will allow VkFFT to run natively on modern Apple SoC. I have tested it on MacBook Pro with an M1 Pro 8c CPU/14c GPU SoC single precision on 1D batched FFT test of all systems from 2 to 4096. Achieved bandwidth is calculated as 2*system size divided by the time taken per FFT - minimum memory that has to be transferred between DRAM and GPU:
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Any good compute shader tutorials?
Another possible project to look at is https://github.com/DTolm/VkFFT
- VkFFT now supports Rader's algorithm - A100 and MI250 benchmarks: Part 2
- VkFFT now supports Rader's algorithm - A100 and MI250 benchmarks
What are some alternatives?
OpenCLOn12 - The OpenCL-on-D3D12 mapping layer
wgpu - Cross-platform, safe, pure-rust graphics api.
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
GLSL - GLSL Shading Language Issue Tracker
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
alpaka - Abstraction Library for Parallel Kernel Acceleration :llama:
cuda-samples - Samples for CUDA Developers which demonstrates features in CUDA Toolkit
MoltenVK - MoltenVK is a Vulkan Portability implementation. It layers a subset of the high-performance, industry-standard Vulkan graphics and compute API over Apple's Metal graphics framework, enabling Vulkan applications to run on macOS, iOS and tvOS.
rocFFT - Next generation FFT implementation for ROCm
SPIRV-VM - Virtual machine for executing SPIR-V
xNVMe - Portable and high-performance libraries and tools for NVMe devices as well as support for traditional/legacy storage devices/interfaces.