"include/ck/utility/span.hpp" did not exist on "7c788e10ce9ddf8e821620fcfda84fbef10d8897"
- 20 Mar, 2025 1 commit
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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
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- 16 Mar, 2025 1 commit
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Lei Wang authored
* [Refactor] Update KernelParam integration across modules - Replaced instances of TensorType with KernelParam in various modules to standardize parameter handling. - Updated JITKernel, BaseKernelAdapter, and CythonKernelAdapter to utilize KernelParam for improved type consistency. - Enhanced Profiler class to include KernelParam in its parameters, ensuring better integration with the new parameter structure. - Adjusted tensor handling in utility functions to accommodate the new KernelParam type, improving overall code clarity and maintainability. - Updated copyright headers to reflect the correct organization. * [Refactor] Clean up whitespace in kernel, profiler, and tensor modules - Added blank lines for improved readability in kernel.py, __init__.py, and tensor.py. - Enhanced code clarity by ensuring consistent formatting across these modules. * [Enhancement] Add detailed docstrings to KernelParam and Profiler classes - Enhanced KernelParam class with comprehensive docstrings for better understanding of its purpose and methods. - Updated Profiler class to include detailed docstrings for its attributes and methods, improving code documentation and usability. - Removed unused do_bench function to streamline the profiler module and improve clarity. * [Refactor] Update type hints in do_bench function and clean up whitespace in profiler module - Changed type hints for grad_to_none and quantiles parameters in do_bench function to use Optional for better clarity. - Added a blank line in __init__.py for improved readability and consistency in the profiler module. * [Refactor] Update type hint in do_bench function for consistency - Changed the return type hint in the do_bench function from a union type to a more explicit List type for better clarity and consistency in type annotations. * [Refactor] Update return type hint in do_bench function for clarity - Changed the return type hint in the do_bench function from a union type to Union[float, List[float]] for improved clarity and consistency in type annotations. * [Enhancement] Add func property to Profiler class for adapter access - Introduced a new property `func` in the Profiler class to provide access to the adapter, ensuring that the adapter is set before retrieval. This enhancement improves the usability of the Profiler class by allowing easier access to the adapter functionality. * [Refactor] Update kernel compilation and profiling in tests - Replaced instances of `TL.lower` and `TL.Profiler` with `tilelang.compile` and the new profiler interface across multiple test files. - Enhanced the kernel compilation process to utilize the updated API, improving consistency and maintainability in the testing framework. - Updated assertions to use the new profiler methods for better clarity and functionality in performance testing. * [Refactor] Simplify kernel invocation and remove unused parameters in tests - Updated the kernel invocation in `test_tilelang_dynamic_symbolic.py` to directly assign the result to `C`, improving clarity. - Removed the `execution_backend` parameter from `tilelang.compile` calls in `test_tilelang_jit_callback.py` and `test_tilelang_jit_gemm.py` for consistency with the updated API. - Commented out the call to `tilelang.testing.main()` in `test_tilelang_jit_callback.py` and replaced it with a direct call to `test_gemm_jit_kernel()` to streamline test execution. - Adjusted the dtype mapping in `TorchDLPackKernelAdapter` to use the parameter's dtype directly, enhancing code simplicity. * [Refactor] Remove unused imports in test files for cleaner code - Eliminated unnecessary imports of `tilelang` as `TL` in various test files to enhance code clarity and maintainability. - Updated multiple test files to streamline the codebase and reduce potential confusion from unused references. * [Refactor] Simplify kernel invocation in tilelang kernel test - Updated the kernel invocation in `test_tilelang_kernel_bf16_gemm_mma.py` to directly assign the result to `C`, enhancing code clarity and consistency with recent changes in the API. * [Refactor] Simplify kernel invocation in tilelang kernel tests - Updated kernel invocations in multiple test files to directly assign the result to `C`, improving code clarity and consistency with the updated API. - Removed unnecessary initialization of `C` as a zero tensor, streamlining the code further. * [Refactor] Update kernel invocation in tilelang transform tests - Replaced the use of `TL.Profiler` with `tilelang.compile` in `test_tilelang_transform_simplify.py`, enhancing code clarity and consistency with the updated API. - Streamlined the kernel invocation process by directly assigning the result to `C`, improving readability and maintainability of the test code.
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- 02 Mar, 2025 1 commit
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Lei Wang authored
* Change default log level from WARNING to INFO in TileLang initialization * Refactor Flash Attention Variable-Length MHA Example with Cython Backend Support - Update `example_mha_fwd_varlen.py` to use Cython backend for kernel compilation - Remove unused imports and simplify function signature - Modify `flashattn` function to handle max sequence length as a separate argument - Update kernel call to include max sequence length parameter - Improve code readability and remove commented-out code - Add print statement to confirm successful assertion * Refactor code formatting in TileLang lowering and example files - Improve line breaks and code formatting in `lower.py`, `wrapper.py`, and `tensor.py` - Simplify line breaks and reduce unnecessary whitespace - Enhance code readability by adjusting indentation and line breaks - Update example MHA forward pass script with cleaner tensor initialization
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- 25 Feb, 2025 2 commits
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Lei Wang authored
* Add DeepSeek MLA decode example with Flash Attention implementation * Add GEMM SplitK and StreamK example implementations This commit introduces two new example scripts demonstrating advanced GEMM (matrix multiplication) techniques: - `example_tilelang_gemm_splitk.py`: Implements a Split-K GEMM kernel using TileLang - `example_tilelang_gemm_streamk.py`: Implements a Stream-K GEMM kernel using TileLang Both examples showcase different parallel computation strategies for matrix multiplication, with comprehensive testing using PyTorch reference implementations. * Refactor GEMM SplitK and StreamK example implementations Clean up and improve code formatting for the SplitK and StreamK GEMM example scripts: - Remove unused import (Profiler) in splitk example - Simplify line breaks and improve code readability - Standardize indentation and remove unnecessary whitespace - Optimize atomic add and copy operations for better clarity * Add block sparse attention benchmarks for multiple libraries This commit introduces comprehensive block sparse attention benchmarks for different libraries: - TileLang block sparse FMHA implementation - Triton block sparse FMHA implementation - PyTorch reference block sparse FMHA implementation - FlashAttention dense FMHA reference implementation The benchmarks include: - Configurable benchmark parameters (batch size, heads, sequence length, etc.) - Sparse mask generation using top-k and threshold methods - Performance measurement for different sparse attention configurations - Utility functions for mask generation and benchmarking * Refactor block sparse attention benchmarks with code style improvements - Add Ruff linter ignore comments to benchmark files - Improve code formatting and line breaks - Remove unused imports - Standardize print statement formatting - Enhance code readability across multiple library benchmarks * lint fix * Add CUDA atomic operations for BFLOAT16 and update function naming - Implement AtomicAdd functions for BFLOAT16 and BFLOAT16x2 in CUDA common header - Rename existing atomic add functions to use PascalCase (atomicAdd -> AtomicAdd) - Add a new __pack_nv_bfloat162 function for packing BFLOAT16 values - Update kernel and language customization to use new function names - Add return type annotations in profiler module * lint fix * Add example for Group Query Attention (GQA) forward pass using Flash Attention in TileLang This commit introduces a new example script `example_gqa_fwd_bshd.py` that demonstrates: - Group Query Attention (GQA) implementation - Flash Attention forward pass - Performance benchmarking - Configurable parameters for batch, heads, sequence length, and dimension - Autotuning support - Reference implementation comparison * Refactor IR lowering pipeline into modular phases This commit introduces a new module `phase.py` to modularize the IR lowering process by splitting the complex lowering pipeline into two distinct phases: - `LowerAndLegalize`: Handles initial IR legalization and transformation - `OptimizeForTarget`: Applies target-specific optimizations The changes simplify the lowering logic in multiple files by extracting the transformation steps into reusable functions, improving code readability and maintainability. * lintfix
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Yu Cheng authored
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- 19 Feb, 2025 2 commits
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Lei Wang authored
* bump version into v0.1.0 * [Enhancement] Add custom develop command for editable installs and update .gitignore * [Documentation] Update README to include system dependencies installation instructions * [Build] Update setup.py to support library file copying for both release and develop modes * [Build] Refactor library file copying logic in setup.py * [Documentation] Remove unnecessary install section header in Installation.md * [Build] Add tox configuration and local distribution script for multi-Python version support * [Build] Improve git submodule update function with better error handling * [Build] Update LLVM configuration path in ROCm installation script * [Build] Add .tox/ to .gitignore for tox testing environment * [Build] Add support for TVM prebuild path configuration in CMakeLists.txt * [Cleanup] Remove unused TVM runtime error codes header * [Cleanup] Fix TVM grid constant type reference in CUDA module * [Cleanup] Remove unused customized_code function from IR module * [Feature] Add TileLang thread synchronization and storage access analysis passes * [Build] Reorder DLL search path directories for more flexible library loading * [Refactor] Improve thread synchronization and library path handling - Rename ThreadSync and TileLangThreadSync functions in C++ code - Update Python docstring for ThreadSync with more detailed description - Reorder library path detection in tilelang environment setup - Minor comment and code cleanup in CUDA and warp specialization modules * [Refactor] Improve thread synchronization code style and formatting - Standardize pointer type spacing in storage_access.h and storage_access.cc - Update whitespace and indentation in thread_storage_sync.cc - Reorder include statements in thread_partial_sync.cc - Minor code formatting improvements across thread synchronization files * [Refactor] Fix global function registration for ThreadSync - Correct global function registration to use ThreadSync instead of TileLangThreadSync - Update TVM global registration to match recent refactoring efforts * [Refactor] Simplify ThreadSync global function registration - Remove unnecessary whitespace in global function registration - Compact the TVM global registration line for ThreadSync * [Feature] Add WebGPU code generation support in TileLang - Implement WebGPU code generator (codegen_webgpu.cc and codegen_webgpu.h) - Add WebGPU target support in lower.py and target.py - Update CMakeLists.txt to include WebGPU codegen source files - Introduce WebGPU-specific code generation for WGSL shader language * [Refactor] Improve WebGPU code generation formatting and readability - Enhance code formatting in codegen_webgpu.cc and codegen_webgpu.h - Standardize pointer type spacing and indentation - Improve line breaks and reduce line length for better readability - Minor code style improvements in WebGPU code generation * [Test] Add WebGPU matrix multiplication code generation test - Implement test_webgpu_codegen.py for WebGPU matrix multiplication - Add assert_gemm_codegen function to validate WebGPU code generation - Include basic matrix multiplication kernel test case * Update README with WebGPU codegen support announcement * Support multi version pypi package build via tox * Add support for CPU device backend with C code generation - Introduce `is_cpu_device_backend` function to detect CPU backend with C code generation - Modify `lower` function to handle special case of CPU device backend - Update host and device call filtering for CPU backend - Add conditional source code generation for C host target - Extend JITKernel to support optional target_host parameter * lint fix * Enhance JIT kernel adapters with CTypes and Torch C++ backends - Add CtypesKernelAdapter with dynamic library generation and kernel wrapping - Implement TorchCPPKernelAdapter for CUDA kernel compilation - Refactor BaseKernelAdapter to support more flexible initialization - Improve error handling and argument processing in kernel adapters - Update adapter initialization to support various execution backends * Refactor and clean up code style in JIT CTypes adapter modules - Apply consistent code formatting and whitespace in CTypes adapter files - Remove unused imports and improve import organization - Enhance readability of code in adapter, libgen, and wrapper modules - Add missing whitespace and improve line breaks - Minor linting and code style improvements across CTypes adapter files * Add test for TileLang JIT GEMM with CTypes backend - Implement comprehensive test for matrix multiplication using CTypes execution backend - Create test functions for GEMM with float16 data type - Add kernel source verification with custom callback - Implement reference implementation using PyTorch for result validation - Support various matrix multiplication configurations (transposition, block sizes) * test fix * Update TileLang JIT callback registration with override parameter - Modify tilelang_callback_cuda_postproc to use @tvm.register_func(override=True) - Ensure proper function registration with ability to replace existing implementations * Reorder TileLang lowering passes for Hopper intrinsics and PTX async copy - Adjust the order of LowerHopperIntrin and InjectPTXAsyncCopy passes - Move these passes to ensure correct synchronization and device preparation * Rebase main * shared.dyn * lint fix * test fix * Add environment variable handling for TileLang template and CUTLASS paths - Introduce fallback logic for TL_TEMPLATE_PATH environment variable - Add support for optional TL_CUTLASS_PATH configuration - Include TODO comment for future environment variable renaming
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Lei Wang authored
* bump version into v0.1.0 * [Enhancement] Add custom develop command for editable installs and update .gitignore * [Documentation] Update README to include system dependencies installation instructions * [Build] Update setup.py to support library file copying for both release and develop modes * [Build] Refactor library file copying logic in setup.py * [Documentation] Remove unnecessary install section header in Installation.md * [Build] Add tox configuration and local distribution script for multi-Python version support * [Build] Improve git submodule update function with better error handling * [Build] Update LLVM configuration path in ROCm installation script * [Build] Add .tox/ to .gitignore for tox testing environment * [Build] Add support for TVM prebuild path configuration in CMakeLists.txt * [Cleanup] Remove unused TVM runtime error codes header * [Cleanup] Fix TVM grid constant type reference in CUDA module * [Cleanup] Remove unused customized_code function from IR module * [Feature] Add TileLang thread synchronization and storage access analysis passes * [Build] Reorder DLL search path directories for more flexible library loading * [Refactor] Improve thread synchronization and library path handling - Rename ThreadSync and TileLangThreadSync functions in C++ code - Update Python docstring for ThreadSync with more detailed description - Reorder library path detection in tilelang environment setup - Minor comment and code cleanup in CUDA and warp specialization modules * [Refactor] Improve thread synchronization code style and formatting - Standardize pointer type spacing in storage_access.h and storage_access.cc - Update whitespace and indentation in thread_storage_sync.cc - Reorder include statements in thread_partial_sync.cc - Minor code formatting improvements across thread synchronization files * [Refactor] Fix global function registration for ThreadSync - Correct global function registration to use ThreadSync instead of TileLangThreadSync - Update TVM global registration to match recent refactoring efforts * [Refactor] Simplify ThreadSync global function registration - Remove unnecessary whitespace in global function registration - Compact the TVM global registration line for ThreadSync * [Feature] Add WebGPU code generation support in TileLang - Implement WebGPU code generator (codegen_webgpu.cc and codegen_webgpu.h) - Add WebGPU target support in lower.py and target.py - Update CMakeLists.txt to include WebGPU codegen source files - Introduce WebGPU-specific code generation for WGSL shader language * [Refactor] Improve WebGPU code generation formatting and readability - Enhance code formatting in codegen_webgpu.cc and codegen_webgpu.h - Standardize pointer type spacing and indentation - Improve line breaks and reduce line length for better readability - Minor code style improvements in WebGPU code generation * [Test] Add WebGPU matrix multiplication code generation test - Implement test_webgpu_codegen.py for WebGPU matrix multiplication - Add assert_gemm_codegen function to validate WebGPU code generation - Include basic matrix multiplication kernel test case * Update README with WebGPU codegen support announcement * Support multi version pypi package build via tox * Add support for CPU device backend with C code generation - Introduce `is_cpu_device_backend` function to detect CPU backend with C code generation - Modify `lower` function to handle special case of CPU device backend - Update host and device call filtering for CPU backend - Add conditional source code generation for C host target - Extend JITKernel to support optional target_host parameter * lint fix * Enhance JIT kernel adapters with CTypes and Torch C++ backends - Add CtypesKernelAdapter with dynamic library generation and kernel wrapping - Implement TorchCPPKernelAdapter for CUDA kernel compilation - Refactor BaseKernelAdapter to support more flexible initialization - Improve error handling and argument processing in kernel adapters - Update adapter initialization to support various execution backends * Refactor and clean up code style in JIT CTypes adapter modules - Apply consistent code formatting and whitespace in CTypes adapter files - Remove unused imports and improve import organization - Enhance readability of code in adapter, libgen, and wrapper modules - Add missing whitespace and improve line breaks - Minor linting and code style improvements across CTypes adapter files * Add test for TileLang JIT GEMM with CTypes backend - Implement comprehensive test for matrix multiplication using CTypes execution backend - Create test functions for GEMM with float16 data type - Add kernel source verification with custom callback - Implement reference implementation using PyTorch for result validation - Support various matrix multiplication configurations (transposition, block sizes) * test fix * Update TileLang JIT callback registration with override parameter - Modify tilelang_callback_cuda_postproc to use @tvm.register_func(override=True) - Ensure proper function registration with ability to replace existing implementations
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- 15 Feb, 2025 1 commit
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Lei Wang authored
* bump version into v0.1.0 * [Enhancement] Add custom develop command for editable installs and update .gitignore * [Documentation] Update README to include system dependencies installation instructions * [Build] Update setup.py to support library file copying for both release and develop modes * [Build] Refactor library file copying logic in setup.py * [Documentation] Remove unnecessary install section header in Installation.md * [Build] Add tox configuration and local distribution script for multi-Python version support * [Build] Improve git submodule update function with better error handling * [Build] Update LLVM configuration path in ROCm installation script * [Build] Add .tox/ to .gitignore for tox testing environment * [Build] Add support for TVM prebuild path configuration in CMakeLists.txt * [Cleanup] Remove unused TVM runtime error codes header * [Cleanup] Fix TVM grid constant type reference in CUDA module * [Cleanup] Remove unused customized_code function from IR module * [Feature] Add TileLang thread synchronization and storage access analysis passes * [Build] Reorder DLL search path directories for more flexible library loading * [Refactor] Improve thread synchronization and library path handling - Rename ThreadSync and TileLangThreadSync functions in C++ code - Update Python docstring for ThreadSync with more detailed description - Reorder library path detection in tilelang environment setup - Minor comment and code cleanup in CUDA and warp specialization modules * [Refactor] Improve thread synchronization code style and formatting - Standardize pointer type spacing in storage_access.h and storage_access.cc - Update whitespace and indentation in thread_storage_sync.cc - Reorder include statements in thread_partial_sync.cc - Minor code formatting improvements across thread synchronization files * [Refactor] Fix global function registration for ThreadSync - Correct global function registration to use ThreadSync instead of TileLangThreadSync - Update TVM global registration to match recent refactoring efforts * [Refactor] Simplify ThreadSync global function registration - Remove unnecessary whitespace in global function registration - Compact the TVM global registration line for ThreadSync * [Feature] Add WebGPU code generation support in TileLang - Implement WebGPU code generator (codegen_webgpu.cc and codegen_webgpu.h) - Add WebGPU target support in lower.py and target.py - Update CMakeLists.txt to include WebGPU codegen source files - Introduce WebGPU-specific code generation for WGSL shader language * [Refactor] Improve WebGPU code generation formatting and readability - Enhance code formatting in codegen_webgpu.cc and codegen_webgpu.h - Standardize pointer type spacing and indentation - Improve line breaks and reduce line length for better readability - Minor code style improvements in WebGPU code generation * [Test] Add WebGPU matrix multiplication code generation test - Implement test_webgpu_codegen.py for WebGPU matrix multiplication - Add assert_gemm_codegen function to validate WebGPU code generation - Include basic matrix multiplication kernel test case * Update README with WebGPU codegen support announcement
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- 14 Feb, 2025 1 commit
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Lei Wang authored
* bump version into v0.1.0 * [Enhancement] Add custom develop command for editable installs and update .gitignore * [Documentation] Update README to include system dependencies installation instructions * [Build] Update setup.py to support library file copying for both release and develop modes * [Build] Refactor library file copying logic in setup.py * [Documentation] Remove unnecessary install section header in Installation.md * [Build] Add tox configuration and local distribution script for multi-Python version support * [Build] Improve git submodule update function with better error handling * [Build] Update LLVM configuration path in ROCm installation script * [Build] Add .tox/ to .gitignore for tox testing environment * [Build] Add support for TVM prebuild path configuration in CMakeLists.txt * [Cleanup] Remove unused TVM runtime error codes header * [Cleanup] Fix TVM grid constant type reference in CUDA module * [Cleanup] Remove unused customized_code function from IR module * [Feature] Add TileLang thread synchronization and storage access analysis passes * [Build] Reorder DLL search path directories for more flexible library loading * [Refactor] Improve thread synchronization and library path handling - Rename ThreadSync and TileLangThreadSync functions in C++ code - Update Python docstring for ThreadSync with more detailed description - Reorder library path detection in tilelang environment setup - Minor comment and code cleanup in CUDA and warp specialization modules * [Refactor] Improve thread synchronization code style and formatting - Standardize pointer type spacing in storage_access.h and storage_access.cc - Update whitespace and indentation in thread_storage_sync.cc - Reorder include statements in thread_partial_sync.cc - Minor code formatting improvements across thread synchronization files * [Refactor] Fix global function registration for ThreadSync - Correct global function registration to use ThreadSync instead of TileLangThreadSync - Update TVM global registration to match recent refactoring efforts * [Refactor] Simplify ThreadSync global function registration - Remove unnecessary whitespace in global function registration - Compact the TVM global registration line for ThreadSync
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- 03 Feb, 2025 1 commit
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Lei Wang authored
* [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
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- 26 Jan, 2025 1 commit
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Lei Wang authored
* implement jit test case * [Dev] implement auto tune test case for matrix multiplication * Implement test for legalize memory access and vectorized loop * lint fix * introduce run_once * Refactor callback function names for consistency and improve code readability * enhance documentations * lint fix * lint fix * lint fix * lint fix * fix formatting issues in rt_mod_hip.cc * add random seed initialization for deterministic testing
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- 23 Jan, 2025 1 commit
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Lei Wang authored
[Bugfix] Reorder Passes: Place Vectorize Loop Before StorageFlatten and FlattenBuffer to Prevent Redundant Allocations (#37) * installation script fix * readme typo fix * doc fix for dequantize gemm * [Doc] remove CODE_OF_CONDUCT.md and SECURITY.md; update references in CONTRIBUTING.md * [Doc] add unit tests for AnnotateDeviceRegions transform; remove SUPPORT.md * update license * [Enhancement] add tensor supply handling for unsigned integers; improve error message for execution backend assertion * [Refactor] improve code readability by reformatting function signatures and assertions * [Refactor] replace torch.manual_seed with tilelang.testing.set_random_seed for consistency in random seed handling * [Refactor] unify thread binding variable naming across kernel and example files * [Refactor] remove unused thread binding parameter from matrix multiplication functions * [Refactor] remove unused thread binding parameter from matrix multiplication functions * [Refactor] enable main testing function in tilelang kernel gemm test * bug fix * lint fix * [Refactor] reorder vectorize loop
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- 20 Jan, 2025 1 commit
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Lei Wang authored
* instruction update * replace link with TileLang/tile-lang * [Dev][Adapter] Implement Torch DLPack Kernel Adapter and related utilities * lint fix * Implement JIT Compiler Components * Documents update * lint fix * update logo * install script fix
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- 17 Jan, 2025 1 commit
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Lei Wang authored
* README.md fixed * test fix * cpu backend update * cpu test case
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- 11 Jan, 2025 1 commit
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Lei Wang authored
* 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>
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