"docs/source/Tutorial/python_api_start.ipynb" did not exist on "464e33fea186e9b5275c653fe0b80dab13cd3fa0"
- 06 Mar, 2025 2 commits
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xs-keju authored
* Add cpu jit with backend ctypes * Resolve some lint issues * Apply PR feedback on head file and kernel example * Add test cases * Resolve formatting issues * Resolve formatting issues --------- Co-authored-by:xxw <1990389406@qq.con>
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Yu Cheng authored
* [Dev] Adjust computation logic to avoid precision loss when casting acc_s from float to float16 - Remove redundant `acc_s_0` fragment in flash attention kernel - Simplify memory copy and reduction operations - Reorder memory copy and scaling steps for improved performance - Add Hopper-specific synchronization method in CUDA reduce template - Update reduce operation to use architecture-specific synchronization * [Dev] Add DeepSeek MLA Decoding (Paged+Varlen) kernel and Performance Benchmark Script - Implement comprehensive MLA (Multi-Head Latent Attention) decoding benchmark script - Add support for multiple implementations: Torch, TileLang, FlashMLA, FlashInfer, and Triton - Create flexible configuration for benchmarking different batch sizes, sequence lengths, and head configurations - Implement performance comparison and CSV output for detailed performance analysis - Add command-line argument support for targeted benchmarking and comparison * [Dev] Refactor MLA Paged Decoding Kernel with Improved Block Handling and Precision - Replace `d` parameter with `dv` to clarify value dimension in MLA decoding - Enhance block distribution logic for split KV processing - Improve handling of remaining blocks in split KV computation - Add initialization of `lse_max_local` to prevent potential precision issues - Optimize block start and range calculations for more accurate sequence processing * lint
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- 05 Mar, 2025 3 commits
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Chaofan Lin authored
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Lei Wang authored
* Fix debug print buffer template for unsigned char type - Update debug_print_buffer_value template specialization for unsigned char - Modify test_tilelang_debug_print.py to include additional dtype tests - Add test case for uint8 dtype in debug print buffer function * Refactor debug print buffer template formatting for unsigned char - Improve code formatting for debug_print_buffer_value template specialization - Adjust line breaks and indentation for better readability - Maintain consistent code style with other template specializations * Extract map_torch_type utility function to tilelang.utils.tensor - Move map_torch_type function from multiple test files to a centralized location - Import map_torch_type from tilelang.utils.tensor in kernel test files - Improve code reusability by creating a shared utility function for type mapping * Add buffer dtype mapping for Cython kernel adapter - Introduce buffer_dtype_map in CythonKernelAdapter to track buffer variable dtypes - Add _process_buffer_dtype method to extract dtype information from TIR function - Update CythonKernelWrapper to support setting and validating buffer dtypes - Enhance type checking during kernel execution with dtype verification - Improve logging message for Cython JIT adapter compilation * Add static shape mapping for Cython kernel adapter - Introduce static_shape_map in CythonKernelAdapter to track buffer variable static shapes - Add _process_static_shape method to extract static shape information from TIR function - Update CythonKernelWrapper to support setting and validating static shapes - Enhance type checking during kernel execution with static shape verification * Add Multi-Head Attention (MHA) Backward Pass Test for TileLang Kernel - Implement comprehensive test for Multi-Head Attention backward pass - Support both causal and non-causal attention scenarios - Add reference implementation for comparing kernel outputs - Test different batch sizes, head counts, sequence lengths, and head dimensions - Verify forward and backward pass correctness using torch.testing.assert_close * Set random seed for MHA backward pass test - Add random seed initialization for consistent test reproducibility - Use tilelang.testing.set_random_seed(42) to ensure deterministic test results
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Lei Wang authored
* Fix debug print buffer template for unsigned char type - Update debug_print_buffer_value template specialization for unsigned char - Modify test_tilelang_debug_print.py to include additional dtype tests - Add test case for uint8 dtype in debug print buffer function * Refactor debug print buffer template formatting for unsigned char - Improve code formatting for debug_print_buffer_value template specialization - Adjust line breaks and indentation for better readability - Maintain consistent code style with other template specializations
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- 04 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 * Update TileLang kernel test with import path changes for MMA layout and macro generator - Modify import statements in test_tilelang_kernel_dequantize_gemm.py - Replace bitblas imports with tilelang.intrinsics imports for MMA-related utilities - Update main function to use tilelang.testing.main() * Add Block Sparse Attention Examples for TileLang and Triton - Implement block sparse attention kernels for both TileLang and Triton - Add utility functions for generating sparse attention masks using top-k and threshold methods - Support causal and variable-length attention scenarios - Include test cases for different sequence length configurations - Demonstrate block-level sparse attention with configurable parameters * Refactor Block Sparse Attention Examples with Code Style Improvements - Improve code formatting in block_sparse_attn_tilelang.py and block_sparse_attn_triton.py - Enhance readability by adjusting line breaks and indentation - Simplify kernel and function calls with better formatting - Add whitespace and line break improvements for better code clarity * Enhance Layout Plotting with Multi-Replication and Dynamic Visualization - Update plot_layout function to support multiple replications in thread and value mapping - Improve thread and value mapping to handle replicated layouts - Dynamically adjust figure size and legend positioning - Add print statements for saved plot file paths - Modify example fragment_mma_load_a.py to uncomment and enable warp and block layout plotting * Refactor AtomicAdd functions in CUDA common header - Implement a generic template for AtomicAdd function - Specialize templates for half_t, bfloat16_t, and pointer types - Reorganize and clean up existing AtomicAdd implementations - Improve type handling and conversion in atomic operations * Remove unused import in MHA backward test file - Remove unnecessary argparse import from test_tilelang_kenrel_mha_bwd.py - Add blank line for improved code formatting - Minor code cleanup in test file
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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 * Update TileLang kernel test with import path changes for MMA layout and macro generator - Modify import statements in test_tilelang_kernel_dequantize_gemm.py - Replace bitblas imports with tilelang.intrinsics imports for MMA-related utilities - Update main function to use tilelang.testing.main() * Add Block Sparse Attention Examples for TileLang and Triton - Implement block sparse attention kernels for both TileLang and Triton - Add utility functions for generating sparse attention masks using top-k and threshold methods - Support causal and variable-length attention scenarios - Include test cases for different sequence length configurations - Demonstrate block-level sparse attention with configurable parameters * Refactor Block Sparse Attention Examples with Code Style Improvements - Improve code formatting in block_sparse_attn_tilelang.py and block_sparse_attn_triton.py - Enhance readability by adjusting line breaks and indentation - Simplify kernel and function calls with better formatting - Add whitespace and line break improvements for better code clarity
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- 28 Feb, 2025 1 commit
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Yu Cheng authored
[Dev][Bugfix] Fix bug in ThreadTagChecker; Add WgmmaSync rewriter and add MHA WGMMA pipelined example (#128) * [Dev] Add RetNet Linear Attention example * [Dev] Add WgmmaSync rewriter for pipelined WGMMA operations and add MHA WGMMA pipelined example (FA3-like scheduling) This commit introduces a new transformation pass `RewriteWgmmaSync` to optimize warp group matrix multiply accumulate (WGMMA) operations in the TileLang compiler: - Implemented `WgmmaSyncRewriter` in `src/transform/wgmma_sync_rewriter.cc` - Added pass registration for `RewriteWgmmaSync` - Updated `tilelang/engine/phase.py` to include the new transformation pass - Updated `tilelang/transform/__init__.py` to expose the new pass The rewriter intelligently manages synchronization and dependencies between WGMMA operations, improving pipeline efficiency for complex matrix multiplication kernels. * [Bugfix] Fix bug in ThreadTagChecker for warp specialization Improve thread tag validation in warp specialized rewriter to prevent unintended transformations: - Add more precise checks for threadIdx.y and threadIdx.z - Validate thread extent to ensure only single-extent thread bindings are allowed - Prevent warp specialization for multi-extent thread bindings in y and z dimensions * lint * [CI] Add TMA descriptor attribute to transformed module in test case
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- 27 Feb, 2025 1 commit
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Lei Wang authored
* refactor code * enhance tutorial * Enhance error handling and code generation in CUDA and TileLang components This commit introduces several improvements across multiple files: - Added more informative error messages in GEMM layout checks - Updated CUDA codegen to support more flexible function signature generation - Improved TMA descriptor initialization and kernel dispatch logic - Refined library generation and source code parsing utilities - Enhanced error handling in various adapter and wrapper classes * Add thread tag validation for warp specialization Introduce a ThreadTagChecker to validate that a PrimFunc only uses threadIdx.x before applying warp specialization. This prevents unintended transformations on kernels with complex thread binding and provides a clear warning to users about potential issues with warp specialization. * Update TileLang Profiling and Compilation in Flash Decoding Examples Refactor the profiling and compilation workflow in two flash decoding example scripts: - Replace `tilelang.lower()` and `tilelang.Profiler()` with `tilelang.compile()` - Simplify profiler initialization using `get_profiler()` - Update method calls to use the new profiler and compiled kernel objects - Maintain existing performance benchmarking and validation logic * Refactor and clean up code formatting in TileLang testing and adapter modules This commit includes several code style and formatting improvements: - Adjust whitespace and line breaks in test files - Improve code formatting in CUDA source wrapper and adapter utilities - Enhance readability of function calls and argument handling - Remove unnecessary whitespace and standardize indentation - Simplify function signatures and argument parsing * Refactor CUDA codegen and improve code formatting This commit includes several improvements to CUDA code generation and formatting: - Enhance function signature generation in CodeGenTileLangCUDA - Improve code formatting and readability in CUDA-related files - Simplify parameter handling and type annotations - Clean up whitespace and line breaks in codegen and layout files --------- Co-authored-by:Ubuntu <dlisuser@h100testl730RPS.xu5snccwrbtejcqqalluoku5hb.xx.internal.cloudapp.net>
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- 21 Feb, 2025 1 commit
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Lei Wang authored
* [Feature] Add CTypes JIT kernel support for dynamic shapes and multi-stream execution - Enhance CtypesKernelAdapter to handle dynamic symbolic shapes - Add support for multi-stream kernel execution in CTypes backend - Implement dynamic shape handling in test_tilelang_jit_gemm_ctypes.py - Add symbolic shape utility function in tilelang.language - Update profiler to improve flexibility in benchmark selection * Remove redundant thread binding in GEMM kernel implementations - Remove unnecessary `thread_binding` line in GEMM kernel functions - Clean up code in `examples/gemm/README.md` and `testing/python/kernel/test_tilelang_kernel_int4_gemm_mma.py` - Enhance code readability by removing redundant thread binding annotation * Fix indentation in int4 GEMM kernel test file - Correct indentation for function calls in `test_tilelang_kernel_int4_gemm_mma.py` - Remove extra indentation in `mma_emitter.ldmatrix_a()` and `mma_emitter.ldmatrix_b()` calls - Improve code formatting for better readability * [Feature] Add Cython JIT kernel support for dynamic shapes and multi-stream execution - Implement CythonKernelAdapter to handle dynamic symbolic shapes - Add support for multi-stream kernel execution in Cython backend - Create comprehensive test suite for Cython GEMM kernel in test_tilelang_jit_gemm_cython.py - Update JITKernel to include "cython" as a valid execution backend - Add Cython-specific wrapper and library generation modules - Update .gitignore to exclude Cython cache directory - Modify setup.py to include Cython source files in package data * lint fix * [Refactor] Replace JITKernel with compile() function for kernel compilation - Add new `compile()` function in tilelang/jit/__init__.py as a wrapper for JITKernel - Update multiple test files and examples to use `tilelang.compile()` instead of `tilelang.JITKernel()` - Modify kernel adapters to support optional kernel-only source retrieval - Update `__init__.py` to import the new `compile()` function - Improve kernel source retrieval for different execution backends * lint fix * remove debug print * Add C/C++ compiler utility module and update Cython JIT kernel support - Introduce new `tilelang/contrib/cc.py` module with cross-platform C/C++ compiler utilities - Add functions to detect and retrieve system C/C++ compilers - Implement cross-compilation and shared library creation support - Update Cython JIT kernel to validate C++ compiler availability - Modify Cython adapter to use detected C++ compiler for library generation * Refactor float8 dtype mapping in tensor utility module - Move float8_dtype_map inside adapt_torch2tvm function - Simplify global scope by localizing the dtype mapping - Maintain existing functionality for converting torch float8 tensors to TVM ndarray * Refactor float8 dtype mapping in tensor utility module - Move float8_dtype_map inside adapt_torch2tvm function - Simplify global scope by localizing the dtype mapping - Maintain existing functionality for converting torch float8 tensors to TVM ndarray * revert * Enhance Cython JIT adapter with Cython compiler detection - Add `get_cython_compiler()` function to dynamically locate Cython executable - Update Cython adapter to use detected Cython compiler instead of hardcoded command - Raise an exception if no Cython compiler is found - Update requirements.txt to specify minimum PyTorch version (>=2.2.0) * Fix Cython kernel wrapper stream handling and type annotations - Update stream parameter type to int64_t for better compatibility - Directly use torch.cuda.current_stream().cuda_stream instead of casting - Improve type safety and precision in Cython kernel wrapper
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- 20 Feb, 2025 1 commit
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Lei Wang authored
* [Feature] Add CTypes JIT kernel support for dynamic shapes and multi-stream execution - Enhance CtypesKernelAdapter to handle dynamic symbolic shapes - Add support for multi-stream kernel execution in CTypes backend - Implement dynamic shape handling in test_tilelang_jit_gemm_ctypes.py - Add symbolic shape utility function in tilelang.language - Update profiler to improve flexibility in benchmark selection * Remove redundant thread binding in GEMM kernel implementations - Remove unnecessary `thread_binding` line in GEMM kernel functions - Clean up code in `examples/gemm/README.md` and `testing/python/kernel/test_tilelang_kernel_int4_gemm_mma.py` - Enhance code readability by removing redundant thread binding annotation * Fix indentation in int4 GEMM kernel test file - Correct indentation for function calls in `test_tilelang_kernel_int4_gemm_mma.py` - Remove extra indentation in `mma_emitter.ldmatrix_a()` and `mma_emitter.ldmatrix_b()` calls - Improve code formatting for better readability
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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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- 11 Feb, 2025 2 commits
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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 * [Enhancement] Add support for FP8 data types and global barriers in CUDA codegen * Fix formatting in CUDA FP8 header file for consistency * Refactor CI workflow to use 'tilelang_ci' virtual environment and update CUDA type printing for better clarity * Update submodule 'tvm' to latest commit for improved functionality * Refactor execution backend references from 'dl_pack' to 'dlpack' for consistency and clarity; add apply_simplify function to simplify PrimFunc or IRModule. * Refactor CUDA code for improved readability; clean up formatting and remove unnecessary whitespace in multiple files. * Refactor import statement in test_tilelang_kernel_dequantize_gemm.py to use 'tilelang.language' for consistency * Add CUDA requirements to FP8 test cases and update references for clarity * Add a blank line for improved readability in test_tilelang_kernel_fp8_gemm_mma.py * Fix data type in reference result calculation for consistency in test_tilelang_kernel_gemm_mma_intrinsic.py * Add CUDA requirements and FP8 test cases for matmul and gemv simulations * Remove debug print statements and use tilelang's testing assertion for result validation in test_tilelang_kernel_gemm_mma_intrinsic.py * Remove outdated comment regarding FP8 tests in test_tilelang_kernel_gemv_simt.py * Add BF16 support to matrix multiplication and introduce corresponding test cases * Add a blank line for improved readability in BF16 GEMM test * Update acknowledgements in README to include supervision by Zhi Yang at Peking University * enhance acknowledgement * Replace tutorial on memory layout optimization with new tutorial on writing high-performance kernels with thread primitives * Update subproject commit for TVM dependency * Update subproject commit for TVM dependency * Add int4_t type and functions for packing char values in CUDA common header * Add plot_layout example and implement GetForwardVars method in layout classes * Refactor code for improved readability by adjusting line breaks and formatting in layout and test files * Fix formatting by removing unnecessary line break in layout.h * Refactor make_int4 function for improved readability by adjusting parameter formatting * Add legend to plot_layout for improved clarity of thread and local IDs * Remove unnecessary dependencies from requirements files for cleaner setup * Remove flash_mha.py and add .gitkeep to deepseek_mla directory * Add build requirements and update installation scripts for improved setup * Introduce carver * Refactor imports and improve code formatting for consistency * Add unit tests for carver recommendation hints * lint fix * Enhance ElementwiseTemplate and BaseTemplate with detailed docstrings for improved code documentation and clarity * Refactor import statements and clean up whitespace in template files for improved readability * Add README.md for Carver framework with usage examples and architecture support * Refactor import statement in matmul_analysis.py for consistency * Refactor TileDict and TensorCorePolicy methods for improved clarity and functionality * Add tests for general matrix multiplication emit configurations * Refactor formatting in test_tilelang_carver_generate_hints.py for improved readability * Add FlashAttentionTemplate and related functionality for hint recommendations * Refactor whitespace in FlashAttentionTemplate and test_tilelang_carver_recommend_hints for improved readability
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Yu Cheng authored
* [CI][Test] Add test cases for tilelang transform MultiVersionBuffer and WarpSpecialized * Relax the mismatch ratio restrictions in the flash_linear_attention and mha tests
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- 10 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 * [Enhancement] Add support for FP8 data types and global barriers in CUDA codegen * Fix formatting in CUDA FP8 header file for consistency * Refactor CI workflow to use 'tilelang_ci' virtual environment and update CUDA type printing for better clarity * Update submodule 'tvm' to latest commit for improved functionality * Refactor execution backend references from 'dl_pack' to 'dlpack' for consistency and clarity; add apply_simplify function to simplify PrimFunc or IRModule. * Refactor CUDA code for improved readability; clean up formatting and remove unnecessary whitespace in multiple files. * Refactor import statement in test_tilelang_kernel_dequantize_gemm.py to use 'tilelang.language' for consistency * Add CUDA requirements to FP8 test cases and update references for clarity * Add a blank line for improved readability in test_tilelang_kernel_fp8_gemm_mma.py * Fix data type in reference result calculation for consistency in test_tilelang_kernel_gemm_mma_intrinsic.py * Add CUDA requirements and FP8 test cases for matmul and gemv simulations * Remove debug print statements and use tilelang's testing assertion for result validation in test_tilelang_kernel_gemm_mma_intrinsic.py * Remove outdated comment regarding FP8 tests in test_tilelang_kernel_gemv_simt.py * Add BF16 support to matrix multiplication and introduce corresponding test cases * Add a blank line for improved readability in BF16 GEMM test * Update acknowledgements in README to include supervision by Zhi Yang at Peking University * enhance acknowledgement * Replace tutorial on memory layout optimization with new tutorial on writing high-performance kernels with thread primitives * Update subproject commit for TVM dependency * Update subproject commit for TVM dependency * Add int4_t type and functions for packing char values in CUDA common header * Add plot_layout example and implement GetForwardVars method in layout classes * Refactor code for improved readability by adjusting line breaks and formatting in layout and test files * Fix formatting by removing unnecessary line break in layout.h * Refactor make_int4 function for improved readability by adjusting parameter formatting * Add legend to plot_layout for improved clarity of thread and local IDs * Remove unnecessary dependencies from requirements files for cleaner setup * Remove flash_mha.py and add .gitkeep to deepseek_mla directory * Add build requirements and update installation scripts for improved setup * Introduce carver * Refactor imports and improve code formatting for consistency * Add unit tests for carver recommendation hints * lint fix * Enhance ElementwiseTemplate and BaseTemplate with detailed docstrings for improved code documentation and clarity * Refactor import statements and clean up whitespace in template files for improved readability * Add README.md for Carver framework with usage examples and architecture support
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- 09 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 * [Enhancement] Add support for FP8 data types and global barriers in CUDA codegen * Fix formatting in CUDA FP8 header file for consistency * Refactor CI workflow to use 'tilelang_ci' virtual environment and update CUDA type printing for better clarity * Update submodule 'tvm' to latest commit for improved functionality * Refactor execution backend references from 'dl_pack' to 'dlpack' for consistency and clarity; add apply_simplify function to simplify PrimFunc or IRModule. * Refactor CUDA code for improved readability; clean up formatting and remove unnecessary whitespace in multiple files. * Refactor import statement in test_tilelang_kernel_dequantize_gemm.py to use 'tilelang.language' for consistency * Add CUDA requirements to FP8 test cases and update references for clarity * Add a blank line for improved readability in test_tilelang_kernel_fp8_gemm_mma.py * Fix data type in reference result calculation for consistency in test_tilelang_kernel_gemm_mma_intrinsic.py * Add CUDA requirements and FP8 test cases for matmul and gemv simulations * Remove debug print statements and use tilelang's testing assertion for result validation in test_tilelang_kernel_gemm_mma_intrinsic.py * Remove outdated comment regarding FP8 tests in test_tilelang_kernel_gemv_simt.py * Add BF16 support to matrix multiplication and introduce corresponding test cases * Add a blank line for improved readability in BF16 GEMM test * Update acknowledgements in README to include supervision by Zhi Yang at Peking University * enhance acknowledgement * Replace tutorial on memory layout optimization with new tutorial on writing high-performance kernels with thread primitives * Update subproject commit for TVM dependency * Update subproject commit for TVM dependency * Add int4_t type and functions for packing char values in CUDA common header * Add plot_layout example and implement GetForwardVars method in layout classes * Refactor code for improved readability by adjusting line breaks and formatting in layout and test files * Fix formatting by removing unnecessary line break in layout.h * Refactor make_int4 function for improved readability by adjusting parameter formatting
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- 08 Feb, 2025 1 commit
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Yu Cheng authored
* [Dev] Add FlashDecoding example * [CI][Test] Add test cases for tilelang kernel convolution * [CI][Test] Add test cases for tilelang kernel FlashAttention * Reduce the number of stages to ensure the shared memory allocation is valid * Temporarily remove the dim128 case * lint * update einops in requirements-dev.txt * update einops in requirements-test.txt * remove einops in requirements-dev.txt * [CI][Test] Add test cases for tilelang transform ClusterPlanning * [CI][Test] Add test cases for tilelang transform LowerHopperIntrin * [CI][Test] Add test cases for tilelang transform InjectFenceProxy
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- 06 Feb, 2025 2 commits
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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 * [Enhancement] Add support for FP8 data types and global barriers in CUDA codegen * Fix formatting in CUDA FP8 header file for consistency * Refactor CI workflow to use 'tilelang_ci' virtual environment and update CUDA type printing for better clarity * Update submodule 'tvm' to latest commit for improved functionality * Refactor execution backend references from 'dl_pack' to 'dlpack' for consistency and clarity; add apply_simplify function to simplify PrimFunc or IRModule. * Refactor CUDA code for improved readability; clean up formatting and remove unnecessary whitespace in multiple files. * Refactor import statement in test_tilelang_kernel_dequantize_gemm.py to use 'tilelang.language' for consistency * Add CUDA requirements to FP8 test cases and update references for clarity * Add a blank line for improved readability in test_tilelang_kernel_fp8_gemm_mma.py * Fix data type in reference result calculation for consistency in test_tilelang_kernel_gemm_mma_intrinsic.py * Add CUDA requirements and FP8 test cases for matmul and gemv simulations * Remove debug print statements and use tilelang's testing assertion for result validation in test_tilelang_kernel_gemm_mma_intrinsic.py * Remove outdated comment regarding FP8 tests in test_tilelang_kernel_gemv_simt.py * Add BF16 support to matrix multiplication and introduce corresponding test cases * Add a blank line for improved readability in BF16 GEMM test * Update acknowledgements in README to include supervision by Zhi Yang at Peking University
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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 * [Enhancement] Add support for FP8 data types and global barriers in CUDA codegen * Fix formatting in CUDA FP8 header file for consistency * Refactor CI workflow to use 'tilelang_ci' virtual environment and update CUDA type printing for better clarity * Update submodule 'tvm' to latest commit for improved functionality * Refactor execution backend references from 'dl_pack' to 'dlpack' for consistency and clarity; add apply_simplify function to simplify PrimFunc or IRModule. * Refactor CUDA code for improved readability; clean up formatting and remove unnecessary whitespace in multiple files. * Refactor import statement in test_tilelang_kernel_dequantize_gemm.py to use 'tilelang.language' for consistency * Add CUDA requirements to FP8 test cases and update references for clarity * Add a blank line for improved readability in test_tilelang_kernel_fp8_gemm_mma.py * Fix data type in reference result calculation for consistency in test_tilelang_kernel_gemm_mma_intrinsic.py * Add CUDA requirements and FP8 test cases for matmul and gemv simulations * Remove debug print statements and use tilelang's testing assertion for result validation in test_tilelang_kernel_gemm_mma_intrinsic.py * Remove outdated comment regarding FP8 tests in test_tilelang_kernel_gemv_simt.py
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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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- 27 Jan, 2025 1 commit
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Yu Cheng authored
* [Dev] Add FlashDecoding example * [CI][Test] Add test cases for tilelang kernel convolution * [CI][Test] Add test cases for tilelang kernel FlashAttention * Reduce the number of stages to ensure the shared memory allocation is valid * Temporarily remove the dim128 case * lint * update einops in requirements-dev.txt * update einops in requirements-test.txt * remove einops in requirements-dev.txt * [CI][Test] Add test cases for tilelang transform ClusterPlanning * [CI][Test] Add test cases for tilelang transform LowerHopperIntrin
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- 26 Jan, 2025 2 commits
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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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Yu Cheng authored
* [Dev] Add FlashDecoding example * [CI][Test] Add test cases for tilelang kernel convolution * [CI][Test] Add test cases for tilelang kernel FlashAttention * Reduce the number of stages to ensure the shared memory allocation is valid * Temporarily remove the dim128 case * lint * update einops in requirements-dev.txt * update einops in requirements-test.txt * remove einops in requirements-dev.txt * [CI][Test] Add test cases for tilelang transform ClusterPlanning
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- 25 Jan, 2025 5 commits
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Cunxiao Ni authored
* [CI][Test] Add test cases for element_add * [Doc] fix typo * Parallelization * format * remove useless condition * format
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Yu Cheng authored
* [Dev] Add FlashDecoding example * [CI][Test] Add test cases for tilelang kernel convolution * [CI][Test] Add test cases for tilelang kernel FlashAttention * Reduce the number of stages to ensure the shared memory allocation is valid * Temporarily remove the dim128 case * lint * update einops in requirements-dev.txt * update einops in requirements-test.txt * remove einops in requirements-dev.txt
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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
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Yu Cheng authored
* [CI][Test] Add test cases for tilelang kernel convolution
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Lei Wang authored
* [Doc] Update documentation structure and content: add overview section, revise project name, and change theme to Furo * [Feature] Add device-side debug printing functions and integrate into kernel interface * lint fix * remove debug print * implement test for debug * lint fix * add some comments * Enhance fragment design and assert fragment print * enhance debug print * add test for msg * lint fix * format * add flash decoding exmaples * remove comment * test simplified
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- 24 Jan, 2025 3 commits
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Lei Wang authored
* [Doc] Update documentation structure and content: add overview section, revise project name, and change theme to Furo * [Feature] Add device-side debug printing functions and integrate into kernel interface * lint fix * remove debug print * implement test for debug * lint fix * add some comments * Enhance fragment design and assert fragment print * enhance debug print * add test for msg * lint fix
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Zhengju Tang authored
[CI][Test] Add test cases for tilelang transform `LayoutInference` and `LowerTileOp` on loop tail split functionality (#29) * [CI][Test] Add test cases for tilelang transform `LayoutInference` and `LowerTileOp` on loop tail split functionality * format * rename test script
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Cunxiao Ni authored
* [Doc] update installation.md and readme * solve conflicts * change readme * fix installation.rst * fix readme * fix installation * [fix] fix installation.rst * [Doc] fix installation.rst * [Doc] fix installation * [CI][Test] Add test cases for tilelang transform PipelinePlanning
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- 23 Jan, 2025 3 commits
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Lei Wang authored
[Refactor] Simplify interface via replacing argument thread binding of intrinsics with `KernelFrame.Current` (#34) * 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
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Lei Wang authored
* 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
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Cunxiao Ni authored
* [Doc] update installation.md and readme * solve conflicts * change readme * fix installation.rst * fix readme * fix installation * [fix] fix installation.rst * [Doc] fix installation.rst * [Doc] fix installation * [CI][Test] Add test cases for tilelang transform `InjectSoftwarePipeline` and `FrontendLegalize` * format * change license
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- 22 Jan, 2025 1 commit
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Lei Wang authored
* 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
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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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