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* [experimental] add a draft gemm_sp * [3rdparty] bump cutlass to v3.9.3 * [lint] run format.sh * [chore] rebase * [chore] use abs path * [gemm_sp] add metadata layout * [ci] add more example * [lint] run format.sh * [chore] polish * [chore] move gemm_sp to experimental * [chore] polish * [lint] run format.sh * [Enhancement] Improve bulk copy handling and update GEMM sparse tensor test * Added a warning log for unsupported non-swizzled global layouts in the bulk copy operation, ensuring fallback to normal copy. * Refactored the GEMM sparse tensor test by removing unnecessary imports and simplifying the kernel compilation process. * Updated the test to directly call the `run_gemm_sp` function, enhancing clarity and functionality. * Implement Test * [Enhancement] Update GEMM SP and SM89 templates for improved functionality * Refactored GEMM SP computation to enhance warp partitioning logic, ensuring compatibility with Hopper architecture. * Updated layout inference to support new WGMMA conditions and improved error messaging for unsupported targets. * Modified SM89 templates to utilize new MMA atom structures, enhancing performance and compatibility with fp8 types. * Added conditional inclusion for GEMM SP header based on CUDA architecture version. * lint fix * [gemm_sp] support more layout and data types * Enhancement: sync T.gemm_sp's layout inference with T.gemm * Enhancement: support more block_k in compress util * [Enhancement] enable block_k=64 * [Lint] run format.sh * [Enhancement] compressor support more dtype * Enhancement: enable block_K=32 * [Lint] format.sh * [Fixbug] fix shape * Refactor: sync gemm * [Enhancement] enable transpose * [Enhancement] enable fp8_e4m3 * [Enhancement] enable int8 * [Lint] run format.sh * [Benchmark] add gemm_sp benchmark * [Example] fix 256 threads hang * [CI] fix ci * [Chore] resolve gemini feedback * [Benchmark] increase search space * [Lint] format * [CI] skip sparse tensor core related tests as only sm90 is supported * [CI] pass local run * Update gemm_sm89.h * lint fix * lint fix * [Enhancement] Add support for sparse GEMM and initialize CUDA architecture flags - Introduced a new boolean flag `enable_sparse_gemm_` to control the inclusion of sparse GEMM functionality in CUDA code generation. - Updated the `Finish` method to conditionally include the sparse GEMM header based on the new flag. - Implemented logic in `VisitStmt_` to enable sparse GEMM when the corresponding external call is detected. - Added a function to initialize the `TORCH_CUDA_ARCH_LIST` environment variable based on the target compute version, enhancing compatibility with PyTorch. - Refactored the initialization function into the appropriate module and ensured it is called in the sparse utilities module. * Update test_compress_utils.py --------- Co-authored-by: LeiWang1999 <leiwang1999@outlook.com> Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>