* [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>
