1. 20 Mar, 2025 1 commit
    • Lei Wang's avatar
      [Refactor] Phaseout LLVM Dependency by Making it Optional (#247) · f2e99180
      Lei Wang authored
      * remove llvm build
      
      * [Refactor] Update kernel compilation and profiling in examples
      
      - Replaced `tilelang.lower` with `tilelang.compile` in multiple example scripts to streamline kernel compilation.
      - Updated profiling calls to utilize the new `get_profiler` method, enhancing performance measurement consistency.
      - Adjusted assertions and benchmarking methods to align with the new profiling structure across various examples, ensuring correctness and clarity in performance evaluations.
      
      * lint fix
      
      * License Update
      
      * [Refactor] Improve code formatting and documentation in CUDA header and HIP runtime files
      
      - Adjusted formatting in `cuda.h` for better readability, including alignment of comments and struct fields.
      - Cleaned up whitespace and improved comment clarity in `rt_mod_hip.cc` to enhance code maintainability.
      
      * [Refactor] Enhance formatting and clarity in CUDA header and HIP runtime files
      
      - Improved comment alignment and readability in `cuda.h`.
      - Cleaned up whitespace and formatting in `rt_mod_hip.cc` to enhance maintainability.
      
      * lint fix
      
      * lint fix
      
      * lint fix
      
      * lint fix
      
      * fix
      
      * License update
      
      * [Enhancement] Update JITKernel to use artifact for kernel source
      
      - Assigned the generated artifact to `self.artifact` for better management.
      - Updated kernel source references to use `artifact.kernel_source` for consistency in execution backend handling.
      
      * lint fix
      
      * Add @tilelang.testing.requires_llvm decorator to vectorization tests
      
      * Enhance setup.py and env.py for library management
      
      - Added functionality to remove original files after copying in CMakeBuild.
      - Updated TVM_LIBRARY_PATH in env.py to include the PyPI build library path for better integration.
      
      * Refactor TVM_LIBRARY_PATH assignment for improved readability in env.py
      
      * Refactor CMakeBuild file handling in setup.py
      
      - Added a check to ensure the target library directory exists before copying .so files.
      - Improved the logic for creating the target directory and copying files to enhance robustness.
      
      * bugfix
      
      * Rename BuildTLDebug to BuildTileLangCUDAWithoutCompile and update registration. Add @tilelang.testing.requires_llvm decorator to multiple tests for LLVM requirement.
      
      * lint fix
      
      * Enhance TileLang code generation by adding support for device code generation without compilation. Updated `host_codegen` and `device_codegen` functions to include new transformations and registration for `tilelang_hip_without_compile`. Refactored JIT kernel adapters to accommodate host and device modules, improving overall integration and flexibility.
      
      * lint fix
      
      * Add support for C target in device code generation
      
      - Updated `device_codegen_without_compile` to include handling for the C target by registering the `tilelang_cpp` function.
      
      * [Enhancement] Implement auto-clear cache feature based on environment variable
      
      * Added TILELANG_CLEAR_CACHE environment variable to control cache clearing.
      * Updated CI workflow to set TILELANG_CLEAR_CACHE during testing.
      * Modified cache initialization to clear cache if TILELANG_CLEAR_CACHE is set to true.
      
      * [Refactor] Update kernel invocation and import paths in tests and cache
      
      * Changed kernel invocation in `test_tilelang_kernel_dequantize_gemm.py` to return the result.
      * Updated import statements in `test_tilelang_kernel_int4_gemm_mma.py` to use `bitblas` instead of `tilelang`.
      * Refactored paths for artifact and parameters in `kernel_cache.py` for better maintainability.
      
      * [Refactor] Clean up whitespace and improve code formatting in kernel_cache.py
      
      * Removed unnecessary blank lines and adjusted spacing for better readability in the KernelCache class.
      * Enhanced overall code formatting to align with project standards.
      
      * [Enhancement] Add bfloat16 test case and improve kernel caching logic
      
      * Introduced a new test case for bfloat16 matrix multiplication in `test_tilelang_kernel_gemm_mma_intrinsic.py`.
      * Updated `KernelCache` to handle multiple kernel source files and improve error handling during saving and loading.
      * Refactored `JITKernel` to support instantiation from a database, enhancing flexibility in kernel management.
      * Adjusted `CtypesKernelAdapter` and `CythonKernelAdapter` to utilize the new kernel loading mechanism from the database.
      * Improved code formatting and readability across several files.
      
      * lint fix
      
      * Update bfloat16 matrix multiplication test case to use larger dimensions for improved coverage
      f2e99180
  2. 07 Mar, 2025 1 commit
    • Lei Wang's avatar
      [Example] Implement NSA Decode tilelang exampls (#168) · 69f35439
      Lei Wang authored
      * [Refactor] Update BitBLAS Benchmark with TileLang Carver Imports and Roller Hints Generation
      
      - Replace BitBLAS imports with TileLang Carver imports in benchmark_matmul.py
      - Modify roller hints generation using new TileLang Carver template and utility functions
      - Update get_roller_hints_from_func to handle None cases and improve return logic
      - Adjust DefaultPolicy to handle different codegen dictionary formats
      
      * [Refactor] Update Thread Binding and Import Statements in TileLang Kernels
      
      - Replace T.thread_binding() with T.get_thread_binding() across multiple kernel test files
      - Update import statements for MMA layout and macro generator in dequantize GEMM and FP8 examples
      - Move map_torch_type utility function to tilelang.utils.tensor
      - Remove unnecessary imports and improve code organization
      
      * Refactor Native Sparse Attention Example with Enhanced Triton Kernel
      
      - Update parallel_nsa_fwd_kernel to support more flexible sparse attention computation
      - Add support for block counts and offsets in the Triton kernel
      - Modify kernel grid and computation logic for improved performance
      - Update example script to use naive_nsa_simple reference implementation
      - Improve type hints and kernel configuration
      
      * Add Native Sparse Attention Examples with Tilelang and Triton Implementations
      
      - Introduce new example scripts for native sparse attention:
        * example_tilelang_nsa_fwd.py: Forward pass implementation using TileLang
        * example_tilelang_nsa_decode.py: Decoding-specific sparse attention implementation
        * example_triton_nsa_fwd.py: Triton-based sparse attention forward pass
      - Update reference.py with naive implementations for sparse attention
      - Support different sparse attention scenarios including forward pass and inference
      - Add comprehensive testing and validation against reference implementations
      
      * lint fix
      69f35439