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[Kernel] Add CUTLASS sparse support with argument sweep, heuristics, and torch operators #10335

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Add Cutlass 2:4 Sparsity Support for Faster LLM Inference

Implements NVIDIA Cutlass 2:4 structured sparsity support in VLLM for accelerated LLM inference. This sparsification pattern, where only 2 out of every 4 weights are non-zero, can provide up to 1.5x speedup while maintaining model quality.


Changes

  • Added Cutlass sparse GEMM kernels
  • Implemented weight matrix conversion to 2:4 sparse format
  • Modified model loading pipeline to handle sparse weights
  • Added sparsity configuration options

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👋 Hi! Thank you for contributing to the vLLM project.
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@mergify mergify bot added the ci/build label Nov 14, 2024
@Faraz9877 Faraz9877 closed this Nov 14, 2024

FetchContent_Declare(
cutlass
GIT_REPOSITORY https://github.com/nvidia/cutlass.git
GIT_TAG v3.5.1
GIT_TAG be692b48b01620eedabeef8325df5d4eeed6c2ae
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Can you keep a git tag? If you switch to commit, then we can't use GIT_SHALLOW TRUE

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I don't think so since cutlass tag 3.6.0 is not still out and I need its features for sparse

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