this post was submitted on 08 Apr 2024
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Unfortunately, those of us doing scientific compute don't have a real alternative.
ROCm just isn't as widely supported as CUDA, and neither is Vulkan for GPGPU use cases.
AMD dropped the ball on GPGPU, and Nvidia is eating their lunch. Linux desktop users be damned.
yep yep and yep.
and they've been eating their lunch so long at this point I've given up on that changing.
The new world stands in cuda and that's just the way it is. I don't really want an nVidia, radeon seems far better for price to performance . Except I can justify an nVidia for work.
I can't justify a radeon for work.
Long term, I expect Vulkan to be the replacement to CUDA. ROCm isn't going anywhere...
We just need fundamental Vulkan libraries to be developed that can replace the CUDA equivalents.
cuFFT->vkFFT(this definitely exists)cuBLAS->vkBLAS(is anyone working on this?)cuDNN->vkDNN(this definitely doesn't exist)At that point, adding Vulkan support to XLA (Jax and TensorFlow) or ATen (PyTorch) wouldn't be that difficult.
The amount of times I said that only to be quickly proven wrong by the fundamental forces of existence is the reason that's going to be written on my tombstone.