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ROCm mx-fp8 Gemm #2066
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ROCm mx-fp8 Gemm #2066
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…dation logic. Added MXFP8_HIPBLASLT recipe and adjusted mx_mm function to accommodate new kernel options.
…ASLT kernel choice for mxfp8 gemm. Enhance documentation on end-to-end performance optimization efforts for AMD GPUs.
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2066
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 129a6d6 with merge base 801af03 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
…py to include HIPBLASLT as a valid kernel choice for MX FP8 operations.
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module: rocm
mx
topic: new feature
Use this tag if this PR adds a new feature
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TLDR: This pull request introduces support for AMD MI355x GPUs with HIPBLASLT kernels in the MX formats prototype. Note that this feature requires ROCm 6.5+ and gfx950
alongside several updates to improve compatibility and functionality for these GPUs. Key changes include updates to configuration options, validation logic, and GEMM kernel handling to integrate HIPBLASLT support.
AMD MI355x GPU Support:
torchao/prototype/mx_formats/config.py
:HIPBLASLT
as a newMXGemmKernelChoice
and included it in theMXLinearRecipeName
for configuration presets. [1] [2]_validate_gemm_kernel_choice
to include validation logic forHIPBLASLT
, ensuring proper block size, data type, and ROCm availability.torchao/prototype/mx_formats/mx_ops.py
:mx_mm
to supportHIPBLASLT
for scaled matrix multiplication and real GEMM operations. [1] [2]Documentation Updates:
torchao/prototype/mx_formats/README.md
:Minor Code Refinements:
torchao/prototype/mx_formats/mx_ops.py
:mx_view_op
by reformatting conditions for FP6 element packing.