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[Dev][TL] Implement MMA INT4 Tensor Core and Correctness Test Case.#232
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LeiWang1999 merged 9 commits intomicrosoft:mainfrom Nov 1, 2024
LeiWang1999:tl_extent
Merged
[Dev][TL] Implement MMA INT4 Tensor Core and Correctness Test Case.#232LeiWang1999 merged 9 commits intomicrosoft:mainfrom LeiWang1999:tl_extent
LeiWang1999 merged 9 commits intomicrosoft:mainfrom
LeiWang1999:tl_extent
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- Adjusted the local fragment sizes for tensor core memory allocation in the MatmulFineGrainScheduler class. - Updated the allocation sizes for A_local, B_local, and C_local variables based on the new fragment sizes. - The changes ensure efficient memory utilization and improve performance. Refactor tensor core memory allocation in MatmulDequantizeFineGrainedScheduler - Modified the fragment sizes for tensor core memory allocation in the MatmulDequantizeFineGrainedScheduler class. - Updated the allocation sizes for A_frag, B_frag, and C_frag variables based on the new fragment sizes. - The changes optimize memory usage and enhance the efficiency of the dequantization process. Refactor tensor core memory allocation in MatmulDequantizeWeightPropagationScheduler - Adjusted the fragment sizes for tensor core memory allocation in the MatmulDequantizeWeightPropagationScheduler class. - Updated the allocation sizes for A_frag, B_frag, B_dequantize_frag, and C_frag variables based on the new fragment sizes. - The changes improve memory utilization and optimize the weight propagation process.
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This pull request introduces several enhancements and bug fixes to the
bitblasandtesting/python/tilelangmodules, including the addition of new classes for tensor core intrinsics, improvements to matrix multiplication functions, and updates to memory allocation in test files.Enhancements to tensor core intrinsics:
INT4TensorCoreIntrinEmitterandINT4TensorCoreIntrinEmitterWithLadderTransformclasses inbitblas/tl/macro_generator.pyto support matrix multiplication withint4data type.Improvements to matrix multiplication functions:
tl_matmul_with_ladder_weight_only_transformandtl_matmul_with_ladder_weight_only_transform_block_reduce_int4functions intesting/python/tilelang/test_tilelang_macro_gemm.pyto use separate local sizes for A, B, and C matrices. [1] [2]mainfunction intesting/python/tilelang/test_tilelang_macro_gemm.pyto allocate local memory using the new local size variables. [1] [2]Updates to utility functions:
make_swizzle_layoutfunction inbitblas/tl/utils.pyto include an optionalis_smoothparameter for smoother layout transformations.Subproject updates:
3rdparty/tvm.