1. 12 Nov, 2025 1 commit
    • Lei Wang's avatar
      [Refactor] Add kernel selection option for GEMM v1 in environment settings (#1200) · 8fbe1b3a
      Lei Wang authored
      * 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
      8fbe1b3a
  2. 02 Nov, 2025 1 commit
  3. 18 Oct, 2025 1 commit
  4. 11 Oct, 2025 1 commit
    • Lei Wang's avatar
      [Refactor] Refactor Pass `InjectFenceProxy` and expose some warp group... · ddfaac36
      Lei Wang authored
      [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
      ddfaac36
  5. 09 Oct, 2025 1 commit
    • Lei Wang's avatar
      [TileOp] Implement WGMMA for T.gemm_v2 (#813) · a13cde28
      Lei Wang authored
      * [Feature] Introduce WGMMA support and enhance GEMM layout handling
      
      - Added support for the WGMMA intrinsic in the TileLang framework, enabling efficient matrix multiplication on newer architectures.
      - Refactored GEMM layout functions to accept a boolean parameter for K dimension handling, improving flexibility in layout generation.
      - Updated layout inference logic to accommodate new WGMMA configurations and ensure compatibility with existing GEMM operations.
      - Enhanced Python bindings for layout functions, allowing for better integration and usability in user-defined operations.
      - Improved documentation for layout functions and GEMM operations to clarify usage and parameters.
      
      These changes enhance the performance and usability of GEMM operations, particularly for advanced architectures, while maintaining backward compatibility with existing implementations.
      
      * [Refactor] Clean up code formatting and enhance layout function readability
      
      - Improved code formatting across multiple files for better readability, including consistent indentation and line breaks.
      - Updated layout function signatures to enhance clarity, particularly in `gemm_layouts.cc`, `layout.cc`, and `layout.h`.
      - Refactored lambda functions in `builtin.cc` and `gemm_py.cc` for improved structure and maintainability.
      - Enhanced comments and documentation in layout-related files to clarify usage and parameters.
      
      These changes contribute to a cleaner codebase and improved maintainability of layout functions in the TileLang framework.
      
      * [Feature] Add descriptor initialization and offset manipulation for WGMMA
      
      - Introduced new TileLang builtins `initialize_descriptor` and `increase_descriptor_offset` to facilitate descriptor management for WGMMA operations.
      - Updated `builtin.cc` and `builtin.h` to define and document the new builtins, enhancing the framework's capabilities for descriptor handling.
      - Modified `codegen_cuda.cc` and `ptx.cc` to integrate the new builtins into the code generation process, ensuring proper assembly generation for WGMMA operations.
      - Enhanced the `GemmWGMMA` class to utilize the new descriptor functionalities, improving the efficiency of matrix multiplication operations.
      - Updated related tests and documentation to reflect the new features and ensure comprehensive coverage.
      
      These changes enhance the TileLang framework's support for advanced matrix operations on newer architectures, improving performance and usability.
      
      * [Refactor] Improve code formatting and readability in various files
      
      - Enhanced code formatting across multiple files for better readability, including consistent indentation and line breaks.
      - Updated function signatures and comments in `builtin.h`, `codegen_cuda.cc`, and `ptx.cc` to improve clarity.
      - Refactored descriptor initialization and offset manipulation functions in `builtin.py` and `wgmma_macro_generator.py` for improved structure.
      - Cleaned up unnecessary whitespace and improved alignment in `common.h` and `allocate.py`.
      
      These changes contribute to a cleaner and more maintainable codebase in the TileLang framework.
      
      * [Update] Update subproject commit and refactor layout function call
      
      - Updated the subproject commit for `cutlass` to indicate a dirty state.
      - Refactored the `UpdateAnalyzer` function in `layout.cc` to call `LayoutNode::getVarMap()` instead of `getVarMap()`, improving clarity and ensuring proper context for variable mapping.
      
      These changes enhance the maintainability and clarity of the layout handling in the TileLang framework.
      
      * support more data types
      
      * gemm_rs support
      
      * lint fix
      
      * wgmma wrapper
      
      * Remove debug logging for wgmma assembly code and refactor swizzle byte size calculations in wgmma macro generator. Enhanced handling of leading and stride byte offsets based on swizzle mode, improving clarity and performance in tensor core intrinsic emissions.
      
      * Refactor GEMM layout functions to replace 'kfactor' with 'k_inner' for improved clarity and consistency. Update includes necessary changes in error messages for Hopper and Sm100 layouts. Additionally, include a new header for CUTE utilities in common.h.
      
      * Comprehensively support WGMMA GEMM SS
      
      * remove debug print
      
      * lint fix
      
      * remove debug print
      
      * reduce bwd test shape
      
      * lint fix
      
      * clear cache for pytest
      
      * lint fix
      
      * Update sparse MLA examples to support SKV adjustment and correctness checks
      
      - Changed SKV parameter from 32768 to 8192 in sparse MLA backward and forward tests.
      - Added check_correctness parameter to test functions for validation of outputs.
      - Updated test cases to reflect new SKV values and correctness checks.
      
      * test fix
      
      * adjust test case
      
      * test fix
      
      * skip some test currently
      a13cde28
  6. 06 Oct, 2025 1 commit
  7. 29 Sep, 2025 1 commit
    • Lei Wang's avatar
      [Example] Add topk into sparse mla example and append some docs (#901) · 6021ef32
      Lei Wang authored
      * Remove unused `fp8_mqa_logits.py` file and update README.md to reflect new directory structure and file descriptions for deepseek_v32 example. Added sections for architecture overview, Lightning Indexer, Top-k Selector, and Sparse MLA Forward implementations.
      
      * Update linting configurations and improve code formatting in deepseek_v32 example scripts
      
      - Added per-file ignores for the inference directory in `pyproject.toml`.
      - Refactored code in `topk_selector.py`, `convert.py`, `generate.py`, `kernel.py`, and `model.py` to enhance readability by adjusting spacing and line breaks.
      - Ensured consistent formatting across function definitions and assertions for better clarity.
      
      * Refactor test functions in deepseek_v32 example scripts for improved clarity and consistency
      
      - Updated `fp8_lighting_indexer.py` to define a dedicated test function for the lighting indexer.
      - Refactored `sparse_mla_fwd_pipelined.py` and `sparse_mla_fwd.py` to standardize test function parameters and improve readability.
      - Enhanced `topk_selector.py` by introducing a test function with parameters for batch size and sequence length.
      - Ensured all test functions are invoked correctly in the main execution block.
      
      * Enhance test functions in deepseek_v32 example scripts with CUDA requirements and parameterization
      
      - Added CUDA requirements decorators to `test_example_sparse_mla_fwd` and `test_example_sparse_mla_fwd_pipelined`.
      - Parameterized test functions to use specific small shapes for testing, improving test coverage and clarity.
      
      * lint fix
      
      * Update README.md to correct image path for DeepSeek V3.2 architecture diagram
      6021ef32