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I don't see the distinction. Tons of popular PyTorch projects run hand made CUDA kernels, whether through a library or one written themselves. In some cases on

I don't see the distinction. Tons of popular PyTorch projects run hand made CUDA kernels, whether through a library or one written themselves. In some cases one can replace rocm/openvino incompatible libraries with pure PyTorch, but the performance hit is often severe, and not many inference projects are using torch.compile or triton kernels to compensate.

sangnoir 3y ago
> I don't see the distinction Performant Pytorch compatibility can be achieved without CUDA compatibility. > In some cases one can replace rocm/openvino incompatible libraries with pure PyTorch This is the crux of my point: AMD ought to focus on fixing these Pytorch incompatibilities instead of splitting focus with chasing CUDA translations.