GitLab

* [Enhancement] Update KernelParam to use tvm.DataType directly and add torch_dtype conversion method

- Changed dtype in KernelParam from torch.dtype to tvm.DataType to support a wider range of data types and prevent information loss during conversions.
- Added a new method, torch_dtype, to convert tvm.DataType back to torch.dtype for tensor creation.
- Updated various adapters to utilize the new torch_dtype method for parameter type conversion during initialization.

* [Enhancement] Refactor CUDA type handling and add support for FP4 and FP8 types

- Renamed functions for clarity: GetFP8Type, GetFP6Type, and GetFP4Type are now GetTileLangFP8Type, GetTileLangFP6Type, and GetTileLangFP4Type respectively.
- Enhanced FP4 type handling to support additional lane sizes (2, 4, 8, 16, 32, 64).
- Updated CUDA code generation to include new FP8 and FP4 types, ensuring proper type handling in PrintType and related functions.
- Introduced new structures for FP8 types in cuda_fp8.h to facilitate better memory management and type packing.
- Added methods in KernelParam and tensor utilities to recognize and handle float4 types, improving compatibility with PyTorch.
- Enhanced logging for debugging purposes in various CUDA functions to track type handling and memory operations more effectively.

* lint fix

* Remove unnecessary logging statements from CUDA code generation and delete obsolete matrix multiplication test file.

* [Enhancement] Add support for FP4 and FP8 types in CUDA code generation

- Enhanced PrintVecElemLoad and PrintVecElemStore functions to handle new FP4 types.
- Updated arg_binder to allow float4 to match int8 at runtime, improving compatibility with PyTorch.
- Modified loop_vectorize to account for buffer dtype lanes in vectorization calculations.
- Refactored tensor type mapping to support new float4 and float8 types, ensuring correct type handling in tensor operations.
- Added tests for FP4 and FP8 copy operations to validate functionality and integration with existing workflows.

---------
Co-authored-by: Zhiwen Mo <zm125@ic.ac.uk>

* Phase out primitives

* revert changes

* Refactor GemmWarpPolicy method signature for clarity

Updated the `from_warp_partition` method in the `GemmWarpPolicy` class to return the type `GemmWarpPolicy` instead of a string, enhancing type safety and clarity in the codebase. Removed an unnecessary blank line for improved readability.

* fix

* [Enhancement] Add read-only parameter annotation for CUDA codegen

* Introduced the `AnnotateReadOnlyParams` transformation to annotate read-only handle parameters in PrimFuncs, enabling the generation of `const` qualifiers in CUDA codegen.
* Updated `PrintFunctionSignature` and `AddFunction` methods to utilize the new attribute `tl.readonly_param_indices`, enhancing performance by allowing read-only cache loads.
* Modified the optimization pipeline to include the new annotation step, improving the overall efficiency of the code generation process.

* lint fix

* [Dependency] Update apache-tvm-ffi version to >=0.1.3

* Updated the version of apache-tvm-ffi in pyproject.toml, requirements.txt, and requirements-dev.txt to ensure compatibility with the latest features and fixes.
* Made adjustments in CUDA and HIP template files to use `const` qualifiers for global pointer parameters, enhancing code safety and clarity.

* lint fix

* [Enhancement] Refactor ReadWriteMarker for improved parameter handling

* Updated the ReadWriteMarker class to accept a set of parameter or data variables, enhancing its ability to track written variables.
* Introduced a new method, ResolveDataVarFromPtrArg, to resolve underlying buffer data from pointer-like arguments, improving accuracy in identifying written variables.
* Modified the MarkReadOnlyParams function to gather handle parameters and their corresponding buffer data variables, streamlining the process of determining read-only parameters.
* Enhanced the logic for identifying written variables to account for aliased data variables, ensuring comprehensive tracking of modifications.

* lint fix

* Update tma_load function to use const qualifier for global memory pointer

* Changed the parameter type of gmem_ptr in the tma_load function from void* to void const* to enhance type safety and clarity in memory operations.
* This modification ensures that the function correctly handles read-only global memory pointers, aligning with best practices in CUDA programming.

* Remove commented-out code and reorder transformations in OptimizeForTarget function for clarity

* Refactor buffer marking logic in annotate_read_only_params.cc to improve accuracy in identifying written variables. Update OptimizeForTarget function to reorder transformations for better clarity.

* [Enhancement] Update AtomicAdd function signature to accept pointer to destination

* Modified AtomicAdd in CUDA to take a pointer instead of a reference for the destination argument.
* Updated related code in atomicadd_vectorize.cc to ensure compatibility with the new signature.
* Adjusted Python interface in atomic.py to pass the destination by pointer, aligning with device function requirements.

* [Enhancement] Refactor AtomicAddRet function signature to accept pointer

* Updated AtomicAddRet in both CUDA and HIP to take a pointer instead of a reference for the address argument, improving consistency with the AtomicAdd function.
* Adjusted the implementation to ensure proper reinterpretation of the address type for atomic operations.

* lint fix

* [Enhancement] Refactor AtomicAddNode::MakeSIMTLoop to use destination pointer

* Updated the MakeSIMTLoop function to build a pointer to the destination element using tvm_access_ptr instead of loading the destination value directly.
* Simplified the handling of source and destination predicates, improving clarity and maintainability of the code.
* Ensured compatibility with the new pointer-based approach for atomic operations.

* lint fix

* test fix

* lint fix

* [misc] add a cpp side wrapper for gemm_sp_py

* [misc] typing

* [IR] bind GemmSPWarpPolicy

* [chore] add wrapper code

* [IR] fix GemmSPWarpPolicy

* [codegen] apply ptxas instructions

* [intrinsic] add typical (unused) mma layout

* [template] add uint16 debug func

* [intrinsic] add b matrix layout

* [gemm_sp] enable fp16/bf16 on sm8x

* [layout] refactor fp16/bf16 layout

* [gemm_sp] enable int8

* [chore] update test case dtype

* [gemm_sp] enable fp32

* [layout] refactor layouts

* [intrinsic] enable ldmatrix for mat A

* [layout] enable ldsm for matrix b

* [layout] add ldmatrix for fp32 and fp8

* [chore] refine

* [chore] refactor

* [chore] add fp8 efactor

* [chore] refactor

* [chore] add remove negative zero util

* [example] add a custom compress kernel

* [chore] minor update

* [test] refactor gemm_sp test

* [refactor] make metadata layout func

* [example] add option for using cutlass layout

* [doc] add a gemm_sp doc

* [doc] minor polish

* [chore] remove unused

* [bugfix] fix non replicate b case

* [test] refactor

* [chore] add a check

* [bugfix] fix util bug

* [wip] init a new test case for v2

* [chore] minor refactor

* [chore] minor update

* [bugfix] enable 16bit rs

* [language] enable rs

* [language] enable gemm_sp_sr

* [language] enable gemm_sp_rr

* [test] enable more tests

* [tvm] update ffi binding

* [chore] remove print

* [chore] fix benchmark script

* [lint] precommit lint

* [chore] apply feedback

* [test] use arch 8.0

* [chore] rollback ::ordered_metadata for backward compatibility

* [bugfix] fix captialized

* [example] keep gemm_sp on hopper

* [test] fix no fp8 normal kernel

* [test] reduce matmul size to satisfy accum error

* [test] use cal_diff for assertion

* [bugfix] expand float8 type

* [lib] add make_int4 for short type

* [language] add transpose E

* [bugfix] fix wrong var

* [format] format

* [chore] refactor binding

* [chore] fix wrong passing var

* feat: add fp8 variants; add placeholder for fp6/fp4 in meta

support ld with pack for fp32 dtype

add dump

add tempalte expand

remove unused dtype and change to rebased apis

* fix: when atom-m!=128, enable_ws

* fix: typo in tcgen05 meta; dispatch in gemm sm100

* [Enhancement] Support more dtype in `T.print`

* upd

* upd

* [Feat] Support warp reduce

* lint

* add test

* lint

This reverts commit 0d101c11

.
Co-authored-by: Zhiwen Mo <zm125@ic.ac.uk>

support ld with pack for fp32 dtype

add dump

add tempalte expand

remove unused dtype and change to rebased apis

* bugfix

* lint fix

* test

* lint fix

* increate procs

* recover

* fix for bool dtype

* lint fix

* fix

* ci fix

* 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>

* [fix] NVRTC execution backend

* [fmt] run pre-commit

* [fix] coderabbit reviews

* [test] add cuda-python to test dep

* [fix] coderabbit reviews

* [fix] CUDA 13 compatibility

* [fix] sm90

* [fix] CUDA 13 compatibility

* [fix] pre-commit

* [fix] always use cuda::std::__atomic_ref_impl

* [fix] restore to external API

* Revert "[fix] restore to external API"

This reverts commit 49bd875638fb631d270015f408991d38fd1e9a5d.

* [fmt] use space instead tabs for py codegen

* [fix] im2col API

* [fix] revert atomic.h

* [fix] dynamic shape

* [refactor] extract common utils

* [feat] support L2 persistent map

* [fix] l2 persistent map

* [fix] pre-commit

* [fix] restore _TYPE_MAP

* [fix] pre-commit

* [fix] avoid duplicate TMA descs

* [docs] add docstring

* [fix] coderabbit

* [fix] coderabbit

* [fix] coderabbit

* [fix] coderabbit

* [Enhancement] Add FP8 support and reproducibility in lighting indexer

* Introduced a manual seed in `test_fp8_lighting_indexer` to ensure reproducible performance.
* Added specializations for `cute::float_e4m3_t` and `cute::float_e5m2_t` in `gemm_mma.h` for enhanced FP8 support across multiple CUDA architectures, ensuring compatibility and improved functionality.ix

* Fix typos in `fp8_lighting_indexer.py` and improve formatting in `gemm_mma.h`

* Corrected a typo in the comment for `test_fp8_lighting_indexer` to enhance clarity.
* Reformatted lines in `gemm_mma.h` for better readability by aligning template specializations across multiple CUDA architectures.

* test fix

* bug fix

* 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

* [Feature] Add support for SM70 tensor core MMA instructions

- Introduced new intrinsic `ptx_mma_sm70` for Volta GPUs, enabling m16n16k4 shape with FP16 inputs and FP16/FP32 accumulation.
- Added `GemmMMASm70` class for handling GEMM operations specific to SM70 architecture.
- Implemented layout functions for Volta swizzled layouts and updated existing GEMM layout inference logic.
- Updated `requirements-dev.txt` to include `apache-tvm-ffi` dependency.
- Added correctness evaluation script for testing GEMM operations on SM70.

* [Refactor] Update formatting and installation commands in scripts

- Modified `format.sh` to install `pre-commit` and `clang-tidy` with the `--user` flag for user-specific installations.
- Improved readability in `correctness_evaluation_sm70.py` by adjusting the formatting of pytest parameters.
- Cleaned up spacing and formatting in various C++ source files for better consistency and readability.
- Removed unnecessary comments and improved layout function definitions in `mma_sm70_layout.py` and `mma_sm70_macro_generator.py` for clarity.
- Ensured consistent formatting in layout initialization and swizzle functions.

* typo fix

* fix

* lint fix

* fix

* lint fix

* fix

* upd

* 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>

* Add type-safe warp shuffle helpers for 16-bit float types in common.h

- Introduced generic passthrough functions for warp shuffle operations: `shfl_xor_sync`, `shfl_down_sync`, `shfl_up_sync`, and `shfl_sync`.
- Added specializations for `cutlass::half_t` and `cutlass::bfloat16_t` to ensure type safety during shuffle operations.
- Updated `reduce.h` to utilize the new shuffle functions, enhancing code clarity and maintainability.

* lint fix

* [BugFix] Correct direct copy from bf16 to fp8

* fix lint

* implement overloaded cast codegen for type conversion

* fix lint

* remove test

* fix lint

* trigger CI

* Overload fp8 for implicit conversion

* format

* new format

* fix: Reinterpret types to cute types in GEMM

* new format

* fix lint

* new format

* fix lint

* format

* trigger ci

---------
Co-authored-by: nicunxiao <nicunxiao@bytedance.com>

* Remove an incorrect check

* add fp8 pack function

* code lint

* minor fix

* minor fix

* minor fix

* Minor fix

* Minor fix

* add pack function

* code lint

* code lint

* update

* update

* [Enhancement] Add missing  primitive after mbarrier init

* lint

* [Feature] Add memory_order PTX for vectorized (2x) atomic add

* [Feature] Add memory_order PTX for all vectorized atomic add

* [Lint]

* test

* [BugFix] FIx init optional argument in alloc_var

* bug fix

* bug fix

* lint fix

* lint fix

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

* [Lint] Retire `format.sh` and add `clang-tidy` to GHA workflow

* chore: update clang-tidy settings

* chore: upgrade clang-format and clang-tidy version

* lint: resolve clang-tidy errors

* [Maint] restore format.sh

* [CI] pre-commit autoupdate

* [Minor] fix `command -v` usage

* [BugFix] Add memory order argument for non-vectorized atomic add

* [Lint]

* [BugFix] Memory order

* [Lint]

* [BugFix] Argument in cuda template

* [Lint]

* Support reduce ss

* lint fix

* test fix

* lint fix

* [Feature] Support Reduce operators for bitwise and/or/xor

* [Lint]

* Expose CUDA warp/lane intrinsics in TileLang frontend

* generalize warp indexing intrinsics and add coverage

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

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

* Remove an incorrect check

* add fp8 pack function

* code lint

* minor fix

* minor fix

* minor fix

* Minor fix

* Minor fix

* [Enhancement] Update abs function for half_t and bfloat_t to use cutlass implementation

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

* optimize amd ci

---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: LeiWang1999 <leiwang1999@outlook.com>

* [Feature][Example] Support TMA reduce operation and update GQA bwd example

* move GQA bwd with TMA reduce to new example

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

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

[Refactor] Refactor Pass `InjectFenceProxy` and expose some warp group primitives in frontend (#977)

* • InjectFenceProxy docs and tests

  - annotate proxy fence injector with context comments for async/generic detection
  - add compiler internals doc covering the pass mechanics and link it in docs index
  - repair fence proxy test by fixing descriptor init usage and fence counter logic

* do not consider call_extern as async.

* doc update.

* reduce test size for sparse mla

* support cumsum-1d

* cumsum 1d support