tile-ai/tilelang
Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels
Python★ 8,159+163 that day#6 on trendingD 43.8 health15% duplicated
D43.8/100
Duplication29
15.2% in python, cpp, c-header, cpp-header, bash, cmake, perlDead code95
0.5%Complexity43
61.1%Most complex files
- 3rdparty/hip-headers/include/hip/amd_detail/hip_prof_str.h3032 cx
- src/ascend/codegen/codegen_pto.cc1728 cx
- src/cuda/codegen/codegen_cuda.cc1438 cx
- src/tl_templates/cpp/half.hpp1061 cx
- src/ascend/codegen/codegen_ascend.cc962 cx
- src/cuda/codegen/codegen_cutedsl.cc776 cx
- src/transform/inject_pipeline.cc684 cx
- src/rocm/codegen/codegen_hip.cc612 cx
- src/cuda/transform/materialize_ws_schedule.cc530 cx
- src/ascend/transform/insert_sync.cc494 cx
Dead code 0.52% unused · 104 findings
- maint/scripts/pytest_cuda_scheduler.pyunused-file
- tilelang/language/tir/ir.pyiunused-file
- docs/conf.pyunused-file
- maint/layout_inference/cases/broadcast_read.pyunused-file
- maint/layout_inference/cases/reducer_scalar_candidates.pyunused-file
- maint/layout_inference/cases/offset_region_copy.pyunused-file
- maint/layout_inference/cases/reduce_broadcast.pyunused-file
- maint/layout_inference/cases/mixed_dtype_chain.pyunused-file
- maint/layout_inference/cases/elementwise_copy.pyunused-file
- maint/layout_inference/cases/transposed_store.pyunused-file
1,897files
531,916lines
4,503,869tokens
5,837clones
79,786duplicated lines (15%)
794,040duplicated tokens (17.63%)
By format
| Format | Files | Lines | Clones | Duplicated lines | Duplication |
|---|---|---|---|---|---|
| python | 1,254 | 283,243 | 3,716 | 50,071 | 17.68% |
| c-header | 207 | 80,969 | 1,052 | 11,205 | 13.84% |
| cpp | 224 | 133,195 | 923 | 15,923 | 11.95% |
| cpp-header | 4 | 8,138 | 78 | 706 | 8.68% |
| json | 11 | 1,966 | 20 | 775 | 39.42% |
| yaml | 19 | 2,043 | 19 | 330 | 16.15% |
| markdown | 91 | 15,981 | 13 | 265 | 1.66% |
| bash | 42 | 2,320 | 5 | 46 | 1.98% |
| txt | 12 | 1,942 | 5 | 415 | 21.37% |
| markup | 4 | 501 | 4 | 35 | 6.99% |
Largest clones
- 1010 lines · 8,914 tokens cppsrc/ascend/transform/thread_storage_sync.cc:582–1591⇆src/transform/thread_storage_sync.cc:583–1592
- 670 lines · 6,121 tokens cppsrc/ascend/transform/layout_inference.cc:51–720⇆src/transform/layout_inference/layout_inference.cc:46–715
- 640 lines · 6,084 tokens cppsrc/ascend/transform/lower_tile_op.cc:515–1154⇆src/transform/lower_tile_op.cc:457–1096
- 495 lines · 4,279 tokens cppsrc/ascend/transform/thread_storage_sync.cc:61–555⇆src/transform/thread_storage_sync.cc:58–552
- 364 lines · 3,464 tokens cppsrc/ascend/transform/thread_storage_sync.cc:193–556⇆src/transform/thread_storage_sync.cc:190–553
- 287 lines · 1,807 tokens cppsrc/cuda/transform/ptx_async_copy_injector.cc:389–675⇆src/rocm/transform/async_copy_injector.cc:391–677
- 24 lines · 1,743 tokens c-header3rdparty/hip-headers/include/hip/hip_runtime_api.h:4102–4125⇆3rdparty/hip-headers/include/hip/hip_runtime_api.h:4141–4164
- 182 lines · 1,727 tokens txtTHIRDPARTYNOTICES.txt:5–186⇆THIRDPARTYNOTICES.txt:210–391
- 182 lines · 1,727 tokens txtTHIRDPARTYNOTICES.txt:5–186⇆THIRDPARTYNOTICES.txt:415–596
- 144 lines · 1,606 tokens pythonexamples/deepseek_nsa/benchmark/benchmark_nsa_fwd.py:306–449⇆examples/deepseek_nsa/reference.py:9–152
Trending appearances
| Day | Rank | Stars | Files | Lines | Clones | Duplication | Health | Commit |
|---|---|---|---|---|---|---|---|---|
| Oct 2, 2026 | #6 | 8,159 (+163) | 1,897 | 531,916 | 5,837 | 15% | D 43.8 | 994b44e |
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