[Dev][TL] Implement MMA INT4 Tensor Core and Correctness Test Case. #232
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
- 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.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
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.