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by Lichtso
2039 days ago
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So far there have been two ways to to heavy compute tasks on GPUs: CUDA (Nvidia only) and OpenCL (all vendors). Nvidia invested a lot in software and toolchains to make CUDA the go to option for many projects (especially in the machine learning community). Meanwhile OpenCL is falling apart and sees less and less support and updates. However, the Vulkan API which is also supported by most vendors (except Apple where you have to use a compatibility layer called MoltenVK) is gaining traction in the compute sector. If you trust the benchmarks, then this library here is showing that you can get a similar performance out of Vulkan compute than what you would expect from CUDA. It is just that this library only provides a very small fraction of the features of what the CUDA ecosystem does, so the Vulkan compute ecosystem still has a lot catching up to do. Edit: In case it is not obvious from the title, the library is used to calculate the https://en.wikipedia.org/wiki/Fast_Fourier_transform |
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I think this view is too pessimistic. In fact, support either gets better (Intel oneAPI, Microsoft CLonD3D12, AMD ROCm, Mesa NIR-clover, …) or is unchanged but still maintained (NVIDIA). Moreover, Khronos noticed that OpenCL 2.x was a dead end and was to start over from a point that all vendors could agree on.