kompute
clspv
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kompute | clspv | |
---|---|---|
37 | 8 | |
1,480 | 574 | |
6.5% | 2.3% | |
8.3 | 9.0 | |
7 days ago | 4 days ago | |
C++ | LLVM | |
Apache License 2.0 | Apache License 2.0 |
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.
kompute
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Intel CEO: 'The entire industry is motivated to eliminate the CUDA market'
The two I know of are IREE and Kompute[1]. I'm not sure how much momentum the latter has, I don't see it referenced much. There's also a growing body of work that uses Vulkan indirectly through WebGPU. This is currently lagging in performance due to lack of subgroups and cooperative matrix mult, but I see that gap closing. There I think wonnx[2] has the most momentum, but I am aware of other efforts.
[1]: https://kompute.cc/
[2]: https://github.com/webonnx/wonnx
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[P] - VkFFT version 1.3 released - major design and functionality improvements
Great to see the positive momentum of this framework! Best wishes and upvotes from the Vulkan Kompute team :)
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VkFFT: Vulkan/CUDA/Hip/OpenCL/Level Zero/Metal Fast Fourier Transform Library
To a first approximation, Kompute[1] is that. It doesn't seem to be catching on, I'm seeing more buzz around WebGPU solutions, including wonnx[2] and more hand-rolled approaches, and IREE[3], the latter of which has a Vulkan back-end.
[1]: https://kompute.cc/
[2]: https://github.com/webonnx/wonnx
[3]: https://github.com/openxla/iree
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I'm Having Trouble Building this Library...
I look in an example and see similar instructions, stating that the build should be quite simple. But again, it doesn't work. It generates a bunch of folders with Visual Studio stuff, but no executables, no libraries, or anything like that.
I can't figure out how, and there are no tutorials. According to https://kompute.cc/overview/build-system.html I should simply run "cmake -Bbuild". But this doesn't output what I need, and when I look in the Makefile I get the sense that this is more an example Makefile... but then that contradicts the above tutorial.
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How to properly construct an abstraction layer with Vulkan
Kompute is in my opinion good example to take inspiration for abstractions.
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Vulkan for Image Processing? Good choice?
Currently, there's a few Vulkan compute frameworks floating around (like Kompute). I would work with those. Kompute simplifies a lot of the biolerplate and seems like you could benefit from using it.
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Paralell computing project
Try Kompute, a project from the Linux foundation. It is quite simple to use, and does not require deep knowledge of graphics API. It’s a bit painful to setup, but it kinda works well (and I have a project going on on it)
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Bootstrapping Vulkan for Scientific Compute Applications?
This so much.
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[D] PyTorch is moving to the Linux Foundation
This makes alot of sense considering the Linux Foundation is also in charge of Kompute which is likely to be the basis of vendor agnostic GPGPU, and thus the basis of vendor agnostic GPU-based machine learning.
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).
What are some alternatives?
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
OpenCLOn12 - The OpenCL-on-D3D12 mapping layer
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
GLSL - GLSL Shading Language Issue Tracker
VkFFT - Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal Fast Fourier Transform library
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.
alpaka - Abstraction Library for Parallel Kernel Acceleration :llama:
godot-proposals - Godot Improvement Proposals (GIPs)
SPIRV-VM - Virtual machine for executing SPIR-V
VulkanExamples - Examples and demos for the Vulkan C++ API
clvk - Implementation of OpenCL 3.0 on Vulkan