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Comment on Intel Gaudi2 chips outperform Nvidia H100 on diffusion transformersparent

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Pytorch relies heavily on the extensive libraries of high-performance kernels provided by NVidia, such as cuDNN.

In other words, it goes something like this:

    Application
    Pytorch (and similar)
    cuDNN (and similar)
    CUDA (and similar)
    NVidia GPU
My opinion, based on what I saw those wizards do, is that reproducing the feature set and efficiency of cuDNN/cuBLAS is deeply nontrivial.
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