GitLab

* [Dependency] Add torch-c-dlpack-ext to project requirements

* Added torch-c-dlpack-ext to both pyproject.toml and requirements.txt to provide prebuilt torch extensions, which may prevent JIT compilation on first import of TVM FFI.

* [Build] Update manylinux images in project configuration

* Changed the manylinux image for x86_64 from "manylinux2014" to "manylinux_2_28" in both pyproject.toml and the Dockerfile to align with updated standards for compatibility and performance.

* [Build] Update CUDA repository configuration in pyproject.toml

* Changed the package manager command from `yum-config-manager` to `dnf config-manager` for adding the CUDA repository, ensuring compatibility with newer systems.

* fix

* [Build] Update CUDA repository to RHEL 8

* Changed the CUDA repository configuration in both pyproject.toml and the manylinux Dockerfile from RHEL 7 to RHEL 8, ensuring compatibility with newer systems.

* test: run out of space

* use cu130 to reduce size

* upd

* upd comment

* upd

---------
Co-authored-by: Your Name <wenji.yyc@alibaba-inc.com>

* [Dependency] Update apache-tvm-ffi version to >=0.1.2 in project files

* [Dependency] Update subproject commit for TVM to latest version afc07935

* [Enhancement] Add support for optional step parameter in loop constructs

- Updated loop creation functions to accept an optional step parameter, enhancing flexibility in loop definitions.
- Modified ForFrame implementations to utilize the new step parameter across various loop types including serial, parallel, and pipelined loops.
- Adjusted related vectorization transformations to accommodate the step parameter, ensuring consistent behavior in loop vectorization processes.

* lint fix

* 3rdparty tvm bump

* bump tvm into v0.22.0

* lint fix

* rebase tvm

* Update submodule tvm to latest commit 3085bc4

* Refactor: Update configuration retrieval in CopyNode and adjust test registration in tilelang

* test fix

* add requirement

* atomic_fix

* atomic_fix

* phaseout py39

* optimize

* optimize

* lint fix

* do not clean cache

* do not clean cache

* [Minor] Minor update for Python versions and dependencies

* [Lint] fix lint for py39

* [Lint] fix lint for ROCm

* [Build][CI] Sync CI changes from upstream/sdist

* [Lint] fix lint for ROCm

* [Build][CI] Update `repair-wheel-command`

* [Minor] update abi3audit result format

* [Lint] fix lint for ROCm

* [BugFix] fix build

* [Lint] fix lint for ROCm

* [BugFix] set rpath for libtvm and libtvm_runtime

* [Deps] pin apache-tvm-ffi version

* [Build] set Python 3.9 Limited API for Cython target

* [Build] set Python 3.9 Limited API for Cython target

* [Deps] Restore Python 3.8 support

* [Build] use `apache-tvm-ffi`'s `libtvm_ffi`

* [BugFix] use `;` as delimiter for RPATH on macOS

* [BugFix] use `--ignore-missing-dependencies` for `delocate-wheel`

* [Build] support `sccache` if available

* [Build] add CIBW import test

* [Build][CI] enable ccache for CIBW on Linux

* [BugFix] set rpath for libtvm and libtvm_runtime

* Revert "[Build][CI] enable ccache for CIBW on Linux"

This reverts commit cd9ab57bb5ddd2572c60bcbbebde81480a658fd3.

* [CI] fix perfbench bot

* [BugFix] use Python 3.9 to build wheel

* [Minor] update perfbench bot envs

* [BugFix] fix CIBW environment on Linux

* [CI] skip import test on CentOS 7

* [CI] use Python urllib to download file instead of Wget

---------
Co-authored-by: Xuehai Pan <XuehaiPan@pku.edu.cn>

* [Refactor][Example] Update linear attention examples and add tests

- Refactored the backward and forward linear attention kernels to use shared memory and atomic additions for improved performance.
- Introduced L2 normalization in the main functions of both examples.
- Added a new test suite for the linear attention examples to ensure correctness and performance.
- Updated argument parsing in the main functions for better usability.

* upd docstring for tma atomic add

* lint

* Add flash-linear-attention dependency to requirements.txt

* Rename main function to chunk_linear_attn_bwd

* Rename main function to chunk_linear_attn_fwd

* chore

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

* refactor: merge test CI workflow files into one

* chore: set `UV_INDEX_STRATEGY=unsafe-best-match`

* feat: add AST test with Python 3.8

* feat: implement manual caching mechanism for self-hosted runners

* refactor: simplify cache logic for self-hosted runners

* chore: clear uv cache on failure

* chore: print format.sh output to logs

* chore: improve uv caching

* chore: disable parallel test

* chore: use `PYTHONDEVMODE=1` in CI

* feat: enable coredump generation

* fix: fix perfbench condition

* Revert "feat: enable coredump generation"

This reverts commit c52da65cb572932e09905d08c43a39ec3cf47c54.

* chore: move example CI down

* Revert "chore: move example CI down"

This reverts commit 9d8e65055e01d955c5268a9a6705d270c2de0d57.

* chore: skip example `test_example_mha_sink_bwd_bhsd`

* chore: skip example `test_example_gqa_sink_bwd_bhsd`

* fix: fix example argument passing

* fix: loosen test criteria

* chore: rename `CMAKE_CONFIG...

* cleanup

* init

* build first wheel that may not work

* build cython ext

* fix tvm build

* use sabi

* update rpath to support auditwheel

* pass editible build

* update ci

* fix warnings

* do not use ccache in self host runner

* test local uv cache

* test pip index

* update lib search to respect new lib location

* fix

* update ci

* enable cuda by default

* update src map

* fix

* fix

* fix

* Generate version with backend and git information at build time

* copy tvm_cython to wheels

* fix tvm lib search

* fmt

* remove unused

* auto detect ccache

* add back backend-related files

* remove jit cython adaptor to simplify code

* fmt

* fix ci

* ci fix 2

* ci fix 3

* workaround metal

* ci fix 4

* fmt

* fmt

* Revert "ci fix 4"

This reverts commit d1de8291c3e40927955f3ad3cf87a75c78813676.

* tmp

* fix metal

* trivial cleanup

* add detailed build-time version for cuda

* add back mlc

* Restore wheel info and other trivial updates

* update

* fix cuda

* upd

* fix metal ci

* test for ga build

* test for nvidia/cuda

* test ubuntu 20

* fix

* fix

* Do not use `uv build`

* fix

* fix

* log toolchain version

* merge wheel

* update

* debug

* fix

* update

* skip rocm

* update artifacts each

* fix

* fix

* add mac

* fix cache

* fix cache

* fix cache

* reset and add comment

* upd

* fix git version

* update deps

* trivial update

* use in-tree build dir and install to src to speedup editable build

* Revert "use in-tree build dir and install to src to speedup editable build"

This reverts commit 6ab87b05c5eed811210136b8dca4fc3677dd51f2.

* add build-dir

* update docs

* remove old scrips

* [1/n] cleanup scripts

* [Lint]: [pre-commit.ci] auto fixes [...]

* fix and update

* wait for tvm fix

* revert some tmp fix

* fix

* fix

* spell

* doc update

* test cibuildwheel

* fix and test macos on ci

* Update .github/workflows/dist.yml
Co-authored-by: Xuehai Pan <XuehaiPan@outlook.com>

* fix

* test ga event

* cleanup

* bump tvm to support api3

* test final version

* add cron

* Update .github/workflows/dist.yml
Co-authored-by: Xuehai Pan <XuehaiPan@outlook.com>

* fix

* test ccache for metal cibuildwheel

* test newer macos

* finish

---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Xuehai Pan <XuehaiPan@outlook.com>

* Update submodule TVM to commit 872e32c1 and adjust type hints in nvcc.py and utils.py for compatibility with Python typing standards.

* Update requirements.txt to specify ml_dtypes without a version constraint, indicating that versions greater than 0.5.1 are needed for fp4 support.

* bugfix

* [Build] Update build dependencies and Dockerfile configuration

- Updated `pyproject.toml` and `requirements-build.txt` to specify Cython version as `Cython>=3.0.0`.
- Removed unnecessary dependencies from the build system.
- Enhanced `pypi.Dockerfile` to install gcc-9 and g++-9, and added ninja-build for improved build performance.
- Updated conda environment creation to include Python 3.9 to 3.12, while removing the Python 3.8 environment.

* cmake fix

* fix

* fix

* [Bugfix] fix autotune bug

* [Example] add w4a8 gemm kernel

* fix lint: pinned the version of `ml_dtypes`
The version of ml_dtypes should be pinned in the dependency specification. If the version of ml_dtypes is too low, it may result in errors such as fp4 not being defined.

* Renames example for dequantization GEMM

* format

* add w4a8 example to ci

* fix lint

* Phase out attr

* Remove unused dependencies from requirements files

* Update TVM submodule to latest commit 4776d31

* [Feature] Add CTypes JIT kernel support for dynamic shapes and multi-stream execution

- Enhance CtypesKernelAdapter to handle dynamic symbolic shapes
- Add support for multi-stream kernel execution in CTypes backend
- Implement dynamic shape handling in test_tilelang_jit_gemm_ctypes.py
- Add symbolic shape utility function in tilelang.language
- Update profiler to improve flexibility in benchmark selection

* Remove redundant thread binding in GEMM kernel implementations

- Remove unnecessary `thread_binding` line in GEMM kernel functions
- Clean up code in `examples/gemm/README.md` and `testing/python/kernel/test_tilelang_kernel_int4_gemm_mma.py`
- Enhance code readability by removing redundant thread binding annotation

* Fix indentation in int4 GEMM kernel test file

- Correct indentation for function calls in `test_tilelang_kernel_int4_gemm_mma.py`
- Remove extra indentation in `mma_emitter.ldmatrix_a()` and `mma_emitter.ldmatrix_b()` calls
- Improve code formatting for better readability

* [Feature] Add Cython JIT kernel support for dynamic shapes and multi-stream execution

- Implement CythonKernelAdapter to handle dynamic symbolic shapes
- Add support for multi-stream kernel execution in Cython backend
- Create comprehensive test suite for Cython GEMM kernel in test_tilelang_jit_gemm_cython.py
- Update JITKernel to include "cython" as a valid execution backend
- Add Cython-specific wrapper and library generation modules
- Update .gitignore to exclude Cython cache directory
- Modify setup.py to include Cython source files in package data

* lint fix

* [Refactor] Replace JITKernel with compile() function for kernel compilation

- Add new `compile()` function in tilelang/jit/__init__.py as a wrapper for JITKernel
- Update multiple test files and examples to use `tilelang.compile()` instead of `tilelang.JITKernel()`
- Modify kernel adapters to support optional kernel-only source retrieval
- Update `__init__.py` to import the new `compile()` function
- Improve kernel source retrieval for different execution backends

* lint fix

* remove debug print

* Add C/C++ compiler utility module and update Cython JIT kernel support

- Introduce new `tilelang/contrib/cc.py` module with cross-platform C/C++ compiler utilities
- Add functions to detect and retrieve system C/C++ compilers
- Implement cross-compilation and shared library creation support
- Update Cython JIT kernel to validate C++ compiler availability
- Modify Cython adapter to use detected C++ compiler for library generation

* Refactor float8 dtype mapping in tensor utility module

- Move float8_dtype_map inside adapt_torch2tvm function
- Simplify global scope by localizing the dtype mapping
- Maintain existing functionality for converting torch float8 tensors to TVM ndarray

* Refactor float8 dtype mapping in tensor utility module

- Move float8_dtype_map inside adapt_torch2tvm function
- Simplify global scope by localizing the dtype mapping
- Maintain existing functionality for converting torch float8 tensors to TVM ndarray

* revert

* Enhance Cython JIT adapter with Cython compiler detection

- Add `get_cython_compiler()` function to dynamically locate Cython executable
- Update Cython adapter to use detected Cython compiler instead of hardcoded command
- Raise an exception if no Cython compiler is found
- Update requirements.txt to specify minimum PyTorch version (>=2.2.0)

* Fix Cython kernel wrapper stream handling and type annotations

- Update stream parameter type to int64_t for better compatibility
- Directly use torch.cuda.current_stream().cuda_stream instead of casting
- Improve type safety and precision in Cython kernel wrapper

* [Enhancement] Add VectorizeLoop function and update imports for compatibility

* [CI][Test] Improve test cases for vectorization and fix typos in parser comments

* lint fix

* Fix incorrect module reference for VectorizeLoop transformation

* Refactor vectorize_loop transformation by removing unused extent mutation logic

* [Enhancement] Add support for FP8 data types and global barriers in CUDA codegen

* Fix formatting in CUDA FP8 header file for consistency

* Refactor CI workflow to use 'tilelang_ci' virtual environment and update CUDA type printing for better clarity

* Update submodule 'tvm' to latest commit for improved functionality

* Refactor execution backend references from 'dl_pack' to 'dlpack' for consistency and clarity; add apply_simplify function to simplify PrimFunc or IRModule.

* Refactor CUDA code for improved readability; clean up formatting and remove unnecessary whitespace in multiple files.

* Refactor import statement in test_tilelang_kernel_dequantize_gemm.py to use 'tilelang.language' for consistency

* Add CUDA requirements to FP8 test cases and update references for clarity

* Add a blank line for improved readability in test_tilelang_kernel_fp8_gemm_mma.py

* Fix data type in reference result calculation for consistency in test_tilelang_kernel_gemm_mma_intrinsic.py

* Add CUDA requirements and FP8 test cases for matmul and gemv simulations

* Remove debug print statements and use tilelang's testing assertion for result validation in test_tilelang_kernel_gemm_mma_intrinsic.py

* Remove outdated comment regarding FP8 tests in test_tilelang_kernel_gemv_simt.py

* Add BF16 support to matrix multiplication and introduce corresponding test cases

* Add a blank line for improved readability in BF16 GEMM test

* Update acknowledgements in README to include supervision by Zhi Yang at Peking University

* enhance acknowledgement

* Replace tutorial on memory layout optimization with new tutorial on writing high-performance kernels with thread primitives

* Update subproject commit for TVM dependency

* Update subproject commit for TVM dependency

* Add int4_t type and functions for packing char values in CUDA common header

* Add plot_layout example and implement GetForwardVars method in layout classes

* Refactor code for improved readability by adjusting line breaks and formatting in layout and test files

* Fix formatting by removing unnecessary line break in layout.h

* Refactor make_int4 function for improved readability by adjusting parameter formatting

* Add legend to plot_layout for improved clarity of thread and local IDs

* Remove unnecessary dependencies from requirements files for cleaner setup

* Remove flash_mha.py and add .gitkeep to deepseek_mla directory

* Add build requirements and update installation scripts for improved setup

* Add format.sh script for code formatting and linting

* docs update

* center align the title

* lint fix

* add ignore

* Add .gitignore for 3rdparty directory

* Add requirements-dev.txt, requirements-test.txt, and requirements.txt

* 3rdparty

* Add gemm.h, CMakeLists.txt, _ffi_api.py, __init__.py, runtime.h, reduce.h, loop_partition.h, utils.h, and loop_vectorize.h

* Refactor CMakeLists.txt and include statements

- Update CMakeLists.txt to use a newer version of CMake and add project name
- Remove unnecessary include directories

Fix include paths in layout.cc, codegen.cc, codegen.h, rt_mod.cc, frontend_legalize.cc, inject_pipeline.cc, layout_inference.cc, loop_vectorize.cc, and lower_tile_op.cc

- Update include paths to use relative paths instead of absolute paths

* Update submodule for 3rdparty/tvm

* update

* load dll first

* Refactor CMakeLists.txt and include statements

* Refactor CMakeLists.txt and include statements

* git keep update

* Refactor CMakeLists.txt and include statements

* Refactor CMakeLists.txt and include statements

* refactor code structure

* Update Readme

* CMakeLists Customized

* update readme

* update README

* update readme

* update usage

* with TVM_IMPORT_PYTHON_PATH to handle own tvm build python import

* annotate lower transform global func with `transform` prefix

* Migrate Simplify Pass from tilelang tvm branch

* enhance system environment handling with __init__ and CMake

* Initial commit

* CODE_OF_CONDUCT.md committed

* LICENSE committed

* README.md committed

* SECURITY.md committed

* SUPPORT.md committed

* CODE_OF_CONDUCT Commit

* LICENSE Commit

* SECURITY Commit

* SUPPORT Commit

* Modify Support

* Update README.md

* security ci update

* remove examples

* Update and implement clang-format

* add composable kernel components

* Migrate from latest update

* submodule update

* Test update

* Update License

* Spell check

* lint fix

* add clang-tidy to apply static analysis for c source

* update tilelang examples

* Update Install Docs

* Refactor filetree

* Enhance Install

* conflict resloved

* annotate_version

* Initial Update

* test fix

* install

* Implement setup.py

* lint fix

* Separate Init

* Separate test

* docker file commit

* add logo

* Update Readme and Examples

* update readme

* update logo

* Implement AMD Installation

* Add License

* Update AMD MI300x Benchmark

* update README

* update mi300 benchmark scripts

* update ignore

* enhance build scirpt

* update image

* enhance setup.py to remove duplicated libraries

* remove debug files

* update readme

* update image

* update gemm examples

* update flashattention README

* readme update

* add cmake into requirements

* libinfo fix

* auto update submodule

* lint fix

* Fix AMD Build and Test

* Update check for transpose attribute for CDNA Arch

* typo fix for amd

* Implement Matmul Benchmark

* Refactor Code

* [TypoFix] Fix GEMM Example

* [Docs] Init Linear Attention README

* [TYPO] Typo fix

* [Lint] Lint Fix

* enhance example with intrinsics

* [Enhancement] Improve Buffer Collection during IR Parser

* [Dev] Introduce Current classmethod to get current frame

* submodule update

* fake test pass update

* support thread_extent_api

* code optimize

* Add GEMM function implementation for matrix multiplication

* Update logging format to reflect TileLang in logger messages

* Refactor CMakeLists.txt for improved readability and set default build type to Release

* Support Gemm SS Primitives Implementation

* [README] Upload Tile Language Logo (#5)

* update logo

* Update README.md to enhance formatting and center the title

---------
Co-authored-by: microsoft-github-operations[bot] <55726097+microsoft-github-operations[bot]@users.noreply.github.com>
Co-authored-by: Microsoft Open Source <microsoftopensource@users.noreply.github.com>
Co-authored-by: Yu Cheng <yu.cheng@pku.edu.cn>