GitLab

* [feat] add an example mma atom

* [fix] fix typo naming

* [feat] add a template to enable compilation

* [feat] add print util

* [WIP] pass on single block tile

* [feat] add sm80 metadata layout

* [chore] clean codebase

* [CI] format.sh

* [feat] add sm80 compress utils

* [bugfix] fix C fragment layout

* [refactor] use nvcc version instead of str

* [test] add test cases

* [chore] add a param check

* [chore] format a bit

* [chore] rename func to satisfy PEP 8 and appease gemini

* [chore] add check

* [feat] support sm75 layout && add assertion && chore

* [bug] fix illegal memory access when using two warps over N=32

This could be a missing check related to cutlass 2.x implementation.
Using the cutlass example can't trigger this cause it's bypassed by
padding the input.

For now I think it might be safe to increase the atom size and inve-
sgate in the future.

* [chore] add example

* [chore] format

* [example] update benchmark

* [bugfix] fix namespace and format

* [bugfix] fix incorrect param passing

* [refactor] update variable declaration for clarity in gemm_layouts and gemm_sp

* [Cleanup] Remove unnecessary blank lines in metadata layout functions in gemm_sp.py

* [CI] fix arch

* [example] add torch sparse benchmark

* [misc] polish && add reference && apply review suggestionsi && format

* [CI] format with clang-tidy

* [Cleanup] Format and align template struct definitions in half.hpp, common.h, and gemm_sp_sm80.h

* [Update] Modify CUDA version requirements in test_gemm_sp_sm80 and mark cutlass subproject as dirty

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Co-authored-by: LeiWang1999 <leiwang1999@outlook.com>

* [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

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Co-authored-by: LeiWang1999 <leiwang1999@outlook.com>
Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>