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kadeng avatar kadeng commented on June 8, 2024

Thanks for reporting this. I brought this to the attention of the core development team, and will come back to you. We're striving for numerical equivalence, so we might consider this to be a bug.

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kadeng avatar kadeng commented on June 8, 2024

As a quick update: The cutlass library underlying AITemplate's GEMM Kernels is using tf32 with some accuracy-enhancing trick by default on A100 / SM80+ GPUs, it seems. See https://github.com/NVIDIA/cutlass/blob/main/examples/27_ampere_3xtf32_fast_accurate_tensorop_gemm/27_ampere_3xtf32_fast_accurate_tensorop_gemm.cu - the numerical differences you are seeing are likey a result of this.

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kadeng avatar kadeng commented on June 8, 2024

@zhekunz2 the PR above should address this issue.

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zhekunz2 avatar zhekunz2 commented on June 8, 2024

@kadeng Thanks for the quick reply and fix! This fix works for me. Much appreciated! 🙏

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