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[None][feat] add MXFP8 weight format + CUTLASS W8A8 Linear and MoE#14962

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[None][feat] add MXFP8 weight format + CUTLASS W8A8 Linear and MoE#14962
WeiHaocheng wants to merge 1 commit into
NVIDIA:mainfrom
WeiHaocheng:feat/main_mxfp8_sm100

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Add first-class MXFP8 (OCP microscaling: e4m3 elements + per-32-element
UE8M0 block scales) weight quantization to the PyTorch backend and
execute MXFP8xMXFP8 W8A8 GEMMs through CUTLASS on Blackwell sm_100/103
for both dense Linear layers and fused MoE.

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    Add first-class MXFP8 (OCP microscaling: e4m3 elements + per-32-element
    UE8M0 block scales) weight quantization to the PyTorch backend and
    execute MXFP8xMXFP8 W8A8 GEMMs through CUTLASS on Blackwell sm_100/103
    for both dense Linear layers and fused MoE.

Signed-off-by: Fred Wei <20514172+WeiHaocheng@users.noreply.github.com>
@WeiHaocheng WeiHaocheng self-assigned this Jun 4, 2026
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