* [Refactor] Improve assertion handling in CodeGenCHost and ArgBinder
This commit refines the assertion message generation in CodeGenCHost by optimizing the handling of equality checks and reducing buffer size for error messages. Additionally, it enhances the ArgBinder by introducing a nullable guard mechanism for assertions, allowing for more precise error handling when binding arguments. The changes improve the clarity and efficiency of assertion handling across the codebase.
* [Enhancement] Update matmul kernel and optimize argument binding
This commit enhances the matmul kernel by introducing additional tensor parameters and refining the pipeline stages for improved performance. It also updates the argument binding mechanism to include a flag indicating whether buffers are used, enhancing the efficiency of buffer management. Furthermore, the optimization phase in the engine is improved by adding a simplification step, ensuring better performance and clarity in the generated code.
* lint fix
* [Enhancement] Add tensor checks documentation and improve argument binding assertions
This commit introduces a new documentation page for host-side tensor checks, detailing the automatic validations performed by TileLang on kernel arguments. It enhances the ArgBinder by adding assertions for non-null pointers when arguments are used, improving error handling. Additionally, the optimization phase in the engine is updated to include a simplification step, ensuring better performance and clarity in the generated code.
* [Enhancement] Update .gitignore and refine matmul kernel for improved performance
This commit adds host checks logs to the .gitignore file to prevent unnecessary log files from being tracked. Additionally, it refines the matmul kernel by adjusting pipeline stages, updating tensor parameters, and enhancing argument handling for better performance. The changes also include improved error messages in the argument binding process, ensuring clearer diagnostics for users.
* lint fix
* lint fix
* [Refactor] Simplify tensor_null_test function and remove ptr_null_test
This commit refactors the tensor_null_test function by adding a with_bias parameter and removing the ptr_null_test function, which was previously unused. The run_test function is updated to reflect these changes, streamlining the testing process for tensor operations.
* lint fix
* fix
* Refactor GEMM and Reduce operations by moving NormalizeToBufferRegion and MakeAccessPtrFromRegion to utils.{h,cc} for better code organization and reuse.
* lint fix
* Refactor region handling by removing the RegionOp and updating NormalizeToBufferRegion to only accept BufferLoad and BufferRegion. This change improves code organization and simplifies the handling of memory regions across various operations.
* fix
* Refactor memory region handling by introducing `tl.region` calls across various operations, including GEMM and fill functions. This change enhances the consistency of region management and improves code organization by utilizing utility functions for buffer region conversions.
* fix
* fix
* test fix
* lint fix
* Refactor GEMM operations to improve memory region handling by replacing `mbarPtr_` with `mbarRegion_` and updating related logic in both C++ and Python implementations. This change enhances the clarity and consistency of buffer region management.
* fix
* lint fix
* fix
* fix
* test fix
* lint fix
* lint fix
* minor fix
* fix
---------
Co-authored-by: Zhiwen Mo <zm125@ic.ac.uk>
This commit enhances the LegalizeNegativeIndex transformation pass to handle
both buffer load and store operations with negative indices and adds some
test cases.
* Add test for T.assume
* Add unit test for T.assume
* Add unit test for T.assume
* Add unit tests for T.assume
* Remove debug print for kernel source
Remove print statement for kernel source in tests.
* Update test_tilelang_language_assume.py
---------
Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>
* [BugFix] Use BufferRegion in tl.cumsum to infer buffer shape
* remove debug lines
* remove rubbish
* Fix decorator syntax for atomic_different_memory_orders_program
---------
Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>
* [Feat] add missing support of uint32x2
* [Feat] Add `T.Ref` annotation and tests
* fix lint error
* minor update for error message on twice decl
* Remove unused let_bindings_ in CodeGenC to fix#1300
* [Feature] Add support for A: T.Tensor(n + 1) and A: T.Tensor(2*n)
* issue fix
* fix
* fix
* decreate nproc for debugging
---------
Co-authored-by: Lei Wang <leiwang1999@outlook.com>
* [Refactor] Update FFI type handling and simplify argument management
* Refactored FFI type definitions in runtime and code generation files to use `TVMFFIAny` instead of `TVMValue`, enhancing type clarity.
* Updated function registration in `runtime.cc` to utilize canonical names for better consistency.
* Simplified argument handling in the `simplify` transformation, ensuring unused buffer parameters are removed only when simplification is enabled.
* Adjusted autotuner and profiler parameters to standardize the execution backend to `tvm_ffi`, improving clarity in backend selection.
* Removed obsolete `adapt_torch2tvm` function from tensor utilities to streamline the codebase and reduce complexity.
* [Update] Sync TVM submodule and enhance kernel source handling
* Updated the TVM submodule to commit cdc2aced, ensuring compatibility with recent changes.
* Added functionality to print kernel source in `example_blocksparse_gemm.py` for better debugging.
* Commented out the main execution call in test files to prevent unintended execution during testing.
* Introduced `tilelang.disable_cache()` in various test files to streamline testing and avoid cache-related issues.
* Refactored kernel source retrieval methods to improve clarity and consistency across different execution backends.
* [Refactor] Clean up imports and improve code formatting
* Removed unused import of `tilelang.testing` in `test_example_blocksparse_gemm.py` to streamline the code.
* Reformatted several lines in `arg_binder.cc`, `make_packed_api.cc`, `tvm_ffi.py`, and `adapter.py` for improved readability and consistency.
* Updated comments and spacing in `tvm_ffi.py` to enhance clarity without altering functionality.
* Update execution backend options and improve resolution logic
- Changed default execution backend from "cython" to "auto" in multiple locations to allow automatic selection based on the target.
- Expanded the list of supported execution backends to include "torch" and "nvrtc" across various classes and functions.
- Enhanced backend resolution logic in `KernelCache` and `AutoTuner` to ensure appropriate backend selection based on the target.
- Updated documentation to reflect changes in execution backend options and their defaults.
* lint fix
* fix
* Enhance argument handling in CUDA and HIP runtime modules
- Updated `ExtractFuncInfo` in `rt_mod_cuda.cc` and `rt_mod_hip.cc` to map boolean argument types to int32, ensuring compatibility with device runtime.
- Refactored `BindDLTensor` in `arg_binder.cc` to improve null handling and validation checks for DLTensor parameters, utilizing expression-level guards to prevent dereferencing null pointers.
- Enhanced error checking for buffer shape, strides, and data fields, ensuring robust handling of optional inputs and maintaining consistency across various checks.
* lint fix
* lint fix
* lint fix
* lint fix
* minor fix
* fix
* recover check
* Refactor argument binding and validation in `arg_binder.cc`
- Improved null handling and validation checks in `BindDLTensor`, ensuring safe dereferencing of pointers.
- Enhanced consistency checks for buffer shape, strides, and data fields, utilizing expression-level guards.
- Updated `MakePackedAPI` to maintain code clarity and consistency in argument handling.
- Minor adjustments in test files to streamline kernel execution and improve readability.
* lint fix
* stride fix
* minor fix
* fix
* lint fix
* lint fix
* Add CUDA stream access policy window helpers and integrate with L2 persistent cache management
- Introduced functions to set and reset the CUDA stream access policy window, allowing for better control over L2 cache usage.
- Updated runtime files to include new FFI packed functions for managing stream attributes.
- Modified lower_hopper_intrin to incorporate prologue and epilogue statements for L2 cache setup and teardown.
- Enhanced tests to verify the inclusion of new FFI calls in the generated kernel source.
* check with symbolic
* support null ptr
* Update CMakeLists and lower.py for code generation and subproject status
- Added `codegen_c_host.cc` to the list of source files in CMakeLists.txt for improved code generation support.
- Updated the function call in `lower.py` to use `target.build.tilelang_c` for C target host code generation, enhancing compatibility.
- Marked the TVM subproject as dirty to indicate local modifications.
* lint fix
* Update comments for clarity in quickstart.py
* fix nsa bwd and atomic
* [Lint]
* [BugFix]
- New implementation for atomicMax and atomicMin using atomicCAS
- PTX version atomicAdd for single 16-byte data
- Modify the test cases
* [Lint]
---------
Co-authored-by: tzj-fxz <tzjfxz@gmail.com>
* [Refactor] Update buffer handling in copy and atomic operations
* Refactored the `copy` and `atomic_add` functions to use element-wise minimum for defining copy extents, ensuring correct handling of overlapping regions.
* Updated utility functions to create `BufferLoad` instances with explicit extents, improving memory management and clarity.
* Removed unused imports from `atomic.py` and `copy.py` to streamline the codebase.
* Adjusted logging in `copy.cc` to provide clearer warnings for fallback scenarios in bulk copy operations.
* Remove obsolete .git_commit.txt file
* Add unit test for dynamic copy extent handling in TileLang
* Introduced a new test file `test_tilelang_issue_1237.py` to verify that the `T.copy` function correctly manages dynamic extents during primitive function building.
* The test reproduces a specific issue related to dynamic slice lengths and static buffer sizes, ensuring robustness in the handling of such scenarios.
* The test does not require execution of the kernel, as building the primitive function is sufficient to validate the fix.
* lint fix
* fix
* Revert "fix"
This reverts commit 828b4c1e4d.
* Update TVM submodule and refactor atomic and copy functions
* Updated the TVM submodule to a dirty state.
* Refactored `atomic_add` and `copy` functions to pass extents explicitly to the `_to_region` helper, improving clarity and correctness in handling buffer regions.
* Commented out the main execution call in the test example for `cast` and added a new function call to better demonstrate the example usage.
* Enhance extent handling in atomic and copy functions
* Introduced `legalize_pairwise_extents` utility to align and broadcast extent lists for `atomic_add` and `copy` functions, ensuring compatibility and correctness in buffer operations.
* Updated both functions to utilize the new utility, improving clarity and robustness in handling dynamic and static extents.
* Added comments to clarify the extent handling logic.
* Enhance `legalize_pairwise_extents` function with early-exit rule
* Added an early-exit condition to the `legalize_pairwise_extents` function to return original extents if the number of non-1 dimensions in both source and destination extents is equal, improving performance by avoiding unnecessary adjustments.
* Updated the function's documentation to clarify the new behavior and maintain clarity in the extent handling logic.
* lint fix
* Update layout handling and introduce reshape functionality
- Updated the `LayoutNode` class to include a new `Reshape` method, allowing for dynamic reshaping of layouts based on input shapes.
- Enhanced the `OutputShape` method to provide better handling of cases where the analyzer cannot form an `IntervalSet`, implementing fallback mechanisms to ensure safe extents.
- Refactored the `ReduceOpNode` to utilize `BufferRegion` for improved memory handling during reduction operations.
- Added tests for reshaping functionality and layout transformations to ensure correctness and performance in various scenarios.
* lint fix
* Revert tvm submodule pointer to 1815c3e0b6ec4ead36370bbd1562025d8529017c; keep src unchanged
* Update tvm submodule to commit f0bbd3bf741413c35c389ba5dedd5be206000ad1
* Update tvm submodule to commit f0bbd3bf741413c35c389ba5dedd5be206000ad1
* remove useless prove
* remove comment
---------
Co-authored-by: tilelang-bot <bot@tilelang>
* Add kernel selection option for GEMM v1 in environment settings
- Introduced `TILELANG_USE_GEMM_V1` environment variable to control the selection of GEMM version.
- Added `use_gemm_v1` method in the `Environment` class to determine if GEMM v1 should be used based on the environment variable.
- Updated GEMM function assignment to default to v2, allowing for v1 to be forced via the new environment variable.
* bug fix
* Add kernel selection option for GEMM in environment settings
- Introduced `TILELANG_USE_GEMM_V1` environment variable to allow users to select between GEMM v1 and v2 implementations.
- Updated `gemm` function to default to v2 but switch to v1 if the environment variable is set to a truthy value.
- Added a method `use_gemm_v1` in the `Environment` class to facilitate this selection based on the environment variable.
* Refactor GEMM macro generator to use BufferRegion instead of Buffer
- Updated `wgmma` and `wgmma_rs` methods in `TensorCoreIntrinEmitter` to accept `BufferRegion` parameters instead of `Buffer`.
- Adjusted related calls in `GemmWGMMA` to ensure compatibility with the new parameter types.
- Simplified buffer access logic for better clarity and maintainability.
* Refactor GEMM functions to utilize BufferRegion for improved memory handling
- Updated `run_gemm`, `run_gemm_rs`, `run_gemm_sr`, and `run_gemm_rr` functions to set `num_stages` based on block dimensions, enhancing performance for larger matrices.
- Simplified calls to GEMM functions by removing redundant parameters and ensuring compatibility with BufferRegion.
- Introduced utility functions for converting between Buffer, BufferLoad, and BufferRegion, improving code clarity and maintainability.
- Enhanced error handling for full region checks in GEMM operations to ensure correctness in memory access.
* Refactor GEMM code for improved readability and consistency
- Cleaned up formatting and spacing in GEMM-related files for better readability.
- Standardized comments and code structure across various GEMM functions and macros.
- Enhanced error messages for clarity in buffer region checks.
- Removed redundant lines and improved overall code maintainability.
* Update GEMM correctness evaluation and macro generator for improved functionality
- Modified `N_VALUES` in `correctness_evaluation_sm70.py` to include only relevant sizes for tests.
- Updated test function call in `correctness_evaluation.py` to use `test_gemm_false_true` for better accuracy in testing.
- Refactored buffer handling in `mma_sm70_macro_generator.py` to improve clarity and consistency in shared buffer access.
- Enhanced `gemm_mma_sm70.py` to ensure full region checks for input and output buffers, improving correctness in GEMM operations.
* Refactor GEMM and intrinsic files for improved clarity and functionality
- Removed unused variable `A_stride_last` in `mma_sm70_macro_generator.py` to streamline code.
- Adjusted function signature formatting in `swizzle.py` for better readability.
- Restored the return of `GemmWGMMA` in `__init__.py` for correct GEMM instantiation.
- Removed unused variable `B_buf` in `gemm_mma_sm70.py` to enhance code cleanliness.
- Improved function signature formatting in `language.py` for consistency.
* Enhance GEMM and MMA functionality for FP64 support
- Refactored `GemmNode` to streamline the decision-making process for GEMM instruction selection.
- Added support for FP64 inputs in the MMA dispatcher, enabling new tensor operations.
- Introduced a new layout function for FP64 in `mma_layout.py` to facilitate shared memory storage.
- Updated `TensorCoreIntrinEmitter` to handle FP64 data types, including adjustments for micro tile dimensions and loading mechanisms.
- Enhanced utility functions to accommodate FP64 index mapping for shared memory operations.
* lint fix
* Refactor GEMM correctness evaluation and shared memory alignment handling
- Reverted the GEMM function call in `correctness_evaluation.py` to the original implementation for consistency.
- Added a helper function in `merge_shared_memory_allocations.cc` to streamline the marking of shared variables under alignment scope.
- Enhanced the `VisitExpr_` methods to ensure proper handling of shared memory alignment for `BufferLoadNode` and `VarNode` types.
- Cleaned up commented-out test code in `correctness_evaluation.py` for better readability.
* Enhance GEMM and MMA implementations with region-based memory handling
- Updated GEMM and MMA classes to utilize BufferRegion for input and output buffers, improving memory management and supporting strided GEMM operations.
- Added checks to ensure full region compliance for input buffers, enhancing correctness in matrix multiplication.
- Implemented clear accumulation functionality to reset output buffers before accumulation, ensuring accurate results in GEMM operations.
* Refactor test_tilelang_example_deepseek_v32.py to improve import structure and function calls
- Updated import statements to directly reference modules instead of individual test functions, enhancing clarity.
- Modified function calls to use the new module structure for better organization and maintainability in testing examples.
* Enhance OnArrayDeclaration method to handle repeated buffer declarations
- Updated the OnArrayDeclaration method to merge metadata for buffers that may appear in multiple Allocate statements, improving robustness against upstream transformations.
- Added logic to prefer concrete element data types and record extents when previously unknown, enhancing the handling of buffer declarations.
* Add abbreviation for bfloat16 data type in mfma_macro_generator.py
- Introduced a new abbreviation "bf16" for the bfloat16 data type in the mfma_macro_generator.py file, enhancing clarity and consistency in data type representation.
* Refactor CodeGenTileLangHIP to enhance dtype handling and mfma call generation
- Introduced a mapping function to normalize input data types to their corresponding scalar types, improving compatibility with MfmaTraits.
- Updated the mfma call generation to utilize the new mapping, streamlining the code and enhancing clarity.
- Removed outdated dtype mapping and replaced it with a more flexible approach to support additional data types like FP8.
* lint fix
* Enhance backend configuration in CMakeLists.txt and improve dtype handling in CodeGenTileLangHIP
- Introduced a macro to define backend options for CUDA, ROCM, and Metal, allowing user overrides and caching of settings.
- Updated logic to track user-selected backends and conditionally enable defaults based on environment variables.
- Refactored dtype handling in CodeGenTileLangHIP to streamline mfma call generation and improve clarity.
- Added support for bfloat16 in the mfma_macro_generator.py, enhancing data type representation consistency.
* Update bfloat16 handling in CodeGenTileLangHIP and mfma_macro_generator.py
- Changed the representation of bfloat16 in CodeGenTileLangHIP from "bfloat16x4" to "bfloat16x4_vec" for improved clarity.
- Adjusted the mfma_suffix generation in mfma_macro_generator.py to remove the underscore before "bf16", aligning with HIP intrinsic requirements.
* Change logging level from WARNING to DLOG in LegalizeNegativeIndex for non-negative index checks to reduce log verbosity.
* Refactor attention sink examples to simplify index calculations
- Updated index handling in `example_gqa_sink_bwd_bhsd.py` and `example_mha_sink_bwd_bhsd.py` to eliminate unnecessary local allocations and streamline logic for determining start and end indices.
- Improved readability by using direct calculations instead of local variables for index bounds in pipelined loops.
* Refactor attention sink examples to streamline index calculations
- Simplified index handling in `example_gqa_sink_bwd_bhsd.py`, `example_gqa_sink_fwd_bhsd_wgmma_pipelined.py`, `example_mha_sink_bwd_bhsd.py`, `example_mha_sink_fwd_bhsd_wgmma_pipelined.py`, and `example_mha_sink_fwd_bhsd.py` by removing unnecessary local allocations for start and end indices.
- Enhanced readability by directly calculating index bounds for pipelined loops, improving overall code clarity.
* lint fix
* bugfix
* Refactor reduce operation handling in CUDA and Python
- Removed outdated shared memory reduction logic from `reduce.cc`.
- Introduced fragment allocation and improved buffer handling in `reduce.py` to support shared and fragment scopes.
- Updated CUDA header to define a wider accumulator type for better numerical accuracy.
- Enhanced error handling for buffer scope validation in the reduction process.
* Fix ReduceOpNode to correctly compute AbsMax by using absolute values of inputs
* Enhance unit loop handling by refining annotation checks
- Updated the condition for identifying effectively empty annotations in unit loops to include cases where only the `pragma_unroll_explicit` hint is present.
- Introduced a new method, `IsEffectivelyEmptyAnnotation`, to encapsulate this logic, improving code clarity and maintainability.
* clean clode
* [Enhancement] Add thread count validation for ReduceOp fragment layout inference
* Introduced a check to ensure that the thread count is divisible by the replicate extent during layout inference in ReduceOpNode. This validation prevents layout inference failures and provides detailed error messages to guide users in resolving issues related to thread block sizes and fragment layouts.
* Updated tests to remove unsupported configurations that could lead to layout inference errors, ensuring more robust testing scenarios.
* lint fix
* [Enhancement] Improve iterator handling in layout utilities and parallel operations
* Added a new function, DivideUnusedIterators, to detect per-iterator gaps in fused index expressions, enhancing the accuracy of unused iterator detection.
* Updated CompleteBufferFragment to prefer direct inversion for bijective index mappings and introduced a fallback mechanism for non-bijective cases, improving layout inversion robustness.
* Added a new test for layout inference in fused kernels to ensure correct compilation and execution without layout inversion failures.
* lint fix
* [Enhancement] Introduce LetWrapper for handling loop variable substitutions in pipeline rewriting
* Added LetWrapper struct to encapsulate variable and value pairs for loop variable substitutions.
* Updated PipelineRewriter to accept a vector of LetWrapper instances, allowing for proper handling of Let statements that depend on the pipeline loop variable.
* Enhanced the BuildPipeline method to incorporate LetWrapper instances into rewritten blocks, ensuring correct substitutions during pipeline execution.
* Refactored logic for processing Let statements to differentiate between those that use the loop variable and those that do not, improving the flexibility of the pipeline transformation.
* Refactor lambda expression for clarity in loop variable usage check in inject_pipeline.cc
* [Test] Add regression test for loop variable handling in kernel compilation
* Introduced a new test case to verify correct handling of loop variables in the kernel compilation process, addressing a regression issue with InjectSoftwarePipeline.
* The test ensures that the loop variable is not left as a free variable, which previously caused failures in MakePackedAPI.
* Configurations are set to disable warp specialization and TMA lowering to align with the original issue reproduction.
* Remove unused import in regression test for loop variable handling in kernel compilation
* [Feature] Support serial for with step
* add more tests
* fix
* Enhance trip count validation in SerialForWithStep to ensure non-zero step values and prevent undefined behavior. Added error handling for zero step values and improved logging for non-constant steps.
* Update builder.py
* fix lint error
---------
Co-authored-by: Zhiwen Mo <zm125@ic.ac.uk>
Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>
* Update dependency version for apache-tvm-ffi in pyproject.toml to fix CI
* [Math] Add `tl.infinity` operation and update Python interface for infinity handling
- Implemented `infinity_op` in C++ to return infinity values for supported data types.
- Registered new operation `tl.infinity` with appropriate attributes.
- Updated Python interface to call the new `tl.infinity` operation instead of the previous method.
* Add unit tests for `tl.infinity` operation in TileLang
- Introduced a new test file `test_tilelang_language_infinity.py` to validate the behavior of the `tl.infinity` operation across multiple data types (float16, bfloat16, float32, float64).
- Implemented a kernel to fill a tensor with infinity values and asserted the correctness of the output against PyTorch's `torch.inf`.
* lint
---------
Co-authored-by: Zhiwen Mo <zm125@ic.ac.uk>
* [Feature] Enhance fill operation to support various buffer types
- Added support for `BufferLoad` in the `fill` function to handle different buffer types.
- Updated `Fill` class to process region descriptors and buffer regions, improving flexibility in buffer handling.
- Introduced checks for static bounds in region definitions to ensure safety during operations.
- Refactored loop induction variable handling in `FillNode` to accommodate sliced regions.
* lint fix
* [Refactor] Improve Python compatibility for ParamSpec and Self
- Added compatibility handling for ParamSpec and Self to support Python versions below 3.10 and 3.11 respectively.
- Updated type annotations across multiple files to ensure consistent usage of typing features.
* [Update] Require Python 3.9 and enhance type annotations
- Updated the minimum required Python version from 3.8 to 3.9 in `pyproject.toml`.
- Removed references to Python 3.8 in classifiers.
- Changed type annotations from `int | None` to `Optional[int]` in multiple example files for better clarity and compatibility.
- Improved import statements to use `collections.abc` for `Iterable` and `contextlib` for `AbstractContextManager` in relevant files.
* [Refactor] Update import statements to enhance type annotations
- Replaced imports from `typing` with `collections.abc` for `Iterable` and `Mapping` in relevant files to improve compatibility and clarity.
- Updated the caching decorator from `functools.lru_cache` to `functools.cache` for better performance in the C++ compiler retrieval function.
- Adjusted import statements in the language proxy file to maintain consistency in type annotations.
* disable rocm rs nt test.
* lint fix
* [Feature] Enhance fill operation to support various buffer types
- Added support for `BufferLoad` in the `fill` function to handle different buffer types.
- Updated `Fill` class to process region descriptors and buffer regions, improving flexibility in buffer handling.
- Introduced checks for static bounds in region definitions to ensure safety during operations.
- Refactored loop induction variable handling in `FillNode` to accommodate sliced regions.
* lint fix
* tilelang frontend v2
* syntax sugar: defining a local var by annotation
* [Refactor] fix type linting warning like `T.float32`
* Add tl.local_var_init for new tl.float32
* allow passing default argument as function annotation
* allow default arguments as annotation
* fix lint error
* minor fix
* [Refactor] refactor tilelang.jit and tilelang.autotune
* minor fix
* minor fix
* minor fix
* fix metal get function name
* add par_compile impl and tests
* Type consistency on tvm datatype
1. isinstance(tl.float32, tvm.DataType) == True
2. Allow `tl.float32` as function annotations
3. Allow `tl.float32` as argument to be passed to `tl.alloc` or other functions
* fix lint error
* add more warning in frontend
* update tvm version
* Minor fix on tvm_ffi annotations
* add document and examples
* fix lint error
* Simplify index calculations in example_chunk_o_bwd.py
Refactor index calculations for dg_last_fragment assignment.
* minor fix
* lint fix
---------
Co-authored-by: Lei Wang <leiwang1999@outlook.com>
Co-authored-by: Lei Wang <34334180+LeiWang1999@users.noreply.github.com>
* remove debug print
* pipeline fix
* use the correct buffer access scope
* rs support
* warp warpgroup_fence_operand
* fix
* fp8 dtype ptx enhance
* mma fix
* TCGEN05 Interface
* tcgen05 support
* rebase
* update
* Enhance TCGEN05 support by adding new intrinsic operations and descriptors. Introduced `ptx_tcgen05_mma_ts` for tensor-memory to shared-memory instructions and `tcgen05_mma_arrive` for signaling barrier completion. Updated existing descriptors and code generation logic to accommodate these changes, ensuring compatibility with new instruction sets. Refactored related allocation functions and improved handling of shared memory descriptors.
* lint fix
* Refactor buffer reference handling in CUDA code generation and update test execution in tilelang. Ensure default annotations for unrolling are set correctly in TIR IR module.
* wgmma fix
---------
Co-authored-by: Zhiwen Mo <zm125@ic.ac.uk>
* 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 cd9ab57bb5.
* [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>
Chaofan Lin