[CCCL] 瘦身 + 补全: 移除 cudax/python/libcudacxx-tests 冗余文件, 新增 c2h 测试助手 + cmake 构建系统 + 8 个 CUDA thrust examples
变更摘要:
- 删除: cudax/ (783 files, 7.2M) — 实验性组件，竞赛不需要
- 删除: python/ (226 files, 2.0M) — Python 绑定，竞赛不需要
- 删除: libcudacxx/{test,benchmarks,codegen,cmake,share} (4432 files, 31M)
保留: libcudacxx/include/ (1463 headers, cuda::std 编译依赖)
- 新增: c2h/ (27 files) — CUB Catch2 测试辅助头文件，编译 243 个测试必需
- 新增: cmake/ (29 files) — CCCL 原生 CMake 构建系统
- 新增: thrust/examples/cuda/ (7 files) + cpp_integration/ (1 file)
async_reduce, custom_temporary_allocation, explicit_cuda_stream,
global_device_vector, range_view, unwrap_pointer, wrap_pointer, device
结果: cccl_upstream 从 74M→35M (瘦身 53%), 核心内容 100% 保留:
27/27 tuning headers, 78 benchmarks, 243 tests,
60 thrust examples, 18 CUB examples, 全部编译头文件
This commit is contained in:
muh-bot
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# cuda.compute Benchmarks
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Compare Python `cuda.compute` performance against C++ CUB implementations.
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## Setup
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This project uses [pixi](https://pixi.sh) to manage environments and dependencies.
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Two environments are available:
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- **`wheel`** - Uses the released `cuda-cccl` package
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- **`source`** - Builds `cuda-cccl` from the local repository
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### Build C++ Benchmarks
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Build CUB benchmarks using the CI script (one-time, ~13 minutes):
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```bash
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cd /path/to/cccl
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./ci/build_cub.sh -arch 89 # Use your GPU arch (89=RTX 4090, 80=A100, 90=H100)
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```
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Binaries are built to: `build/cub/bin/`
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## Run Benchmarks
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### Using pixi tasks
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```bash
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# Run Python benchmarks (released cuda-cccl)
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pixi run -e wheel bench
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# Run Python benchmarks (local source build)
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pixi run -e source bench
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# Run Python benchmarks with reduced parameter set
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pixi run -e wheel bench-quick
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# Run just one benchmark
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pixi run -e wheel bench -b transform/fill
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# Run C++ benchmarks
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pixi run -e wheel bench-cpp
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# Run both Python and C++ benchmarks
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pixi run -e wheel bench-all
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```
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### Using run_benchmarks.py directly
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```bash
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# Run both C++ and Python (default)
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pixi run -e wheel python run_benchmarks.py -b transform/fill -d 0
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# Run only C++
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pixi run -e wheel python run_benchmarks.py -b transform/fill --cpp
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# Run only Python
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pixi run -e wheel python run_benchmarks.py -b transform/fill --py
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# Show help
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pixi run -e wheel python run_benchmarks.py --help
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```
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To run the benchmarks using the "quick" configuration:
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```bash
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pixi run -e wheel python run_benchmarks.py --quick
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```
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## Compare Results
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```bash
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pixi run -e wheel python analysis/python_vs_cpp_summary.py -b transform/fill
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```
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## Web Report
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A simple page used to visualize a set of results.
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- Requires `results/` to be populated with benchmark results.
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First generate a manifest:
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```bash
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pixi run -e wheel python analysis/generate_web_report_manifest.py \
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--results-dir results \
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--output results/manifest.json
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```
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Build the web report single file app:
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```bash
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cd analysis/web-report
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npm install
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npm run build
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```
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This will output a single file app to `analysis/web-report/dist/` copy it to the `results/` directory and:
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```bash
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cd results/
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python3 -m http.server
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```
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Now its possible to share the results directory as a zip/tar file.
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## Manual Usage
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### List benchmark configurations
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```bash
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# Python
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pixi run -e wheel python transform/fill.py --list
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# C++
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/path/to/cccl/build/cub/bin/cub.bench.transform.fill.base --list
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```
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### Run with custom options
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```bash
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# Python - specific type and size
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pixi run -e wheel python transform/fill.py --axis "T=I32" --axis "Elements[pow2]=20" --devices 0
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# C++ - save JSON
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/path/to/cccl/build/cub/bin/cub.bench.transform.fill.base \
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--json results/transform/fill_cpp.json \
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--devices 0
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```
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### Compare manually
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```bash
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pixi run -e wheel python analysis/python_vs_cpp_summary.py \
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results/transform/fill_py.json \
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results/transform/fill_cpp.json \
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--device 0
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```
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## AI commands
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These are using the .opencode folder but can be moved to other Agents.
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### /migration-status
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Generates a report of the migration status for each benchmark in CUB.
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