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ptillet avatar ptillet commented on August 24, 2024

Sorry for the delayed answer, I've been quite busy and missed this. The documentation is not up to date, so I will fix this, let you know and update it!

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ptillet avatar ptillet commented on August 24, 2024

The correct use of matrix multiplication is indeed @. The other issue is that the kernel is designed for row-major matrices, but the values of lda are assuming column-major ordering.

Changing to:

lda = K
ldb = N
ldc = N

Seems to solve the issue. I would also use torch.allclose() for comparing two FP32 tensors as torch may not do the FMA in the same order as the Triton kernel.

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jack-willturner avatar jack-willturner commented on August 24, 2024

AH thank you I don't know why I didn't consider that the kernel was assuming row-major accesses.

I think I understand everything now, so if you'd like I'd be happy to run through the documentation and make sure the example kernels are compilable/working.

Thanks again!

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ptillet avatar ptillet commented on August 24, 2024

Yes, that would be very cool! Another thing is that triton.empty and triton.shape are no longer necessary. One can simply use torch.empty

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