docs: add developer guide for sgl-kernel (#3068)
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sgl-kernel/developer_guide.md
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sgl-kernel/developer_guide.md
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# Developer Guide for sgl-kernel
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## Development Environment Setup
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Use Docker to set up the development environment. See [Docker setup guide](https://github.com/sgl-project/sglang/blob/main/docs/developer/development_guide_using_docker.md#setup-docker-container).
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Create and enter development container:
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```bash
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docker run -itd --shm-size 32g --gpus all -v $HOME/.cache:/root/.cache --ipc=host --name sglang_zhyncs lmsysorg/sglang:dev /bin/zsh
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docker exec -it sglang_zhyncs /bin/zsh
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```
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## Project Structure
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### Dependencies
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Third-party libraries:
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- [CCCL](https://github.com/NVIDIA/cccl)
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- [CUTLASS](https://github.com/NVIDIA/cutlass)
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- [FlashInfer](https://github.com/flashinfer-ai/flashinfer)
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### Kernel Development
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Steps to add a new kernel:
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1. Implement in `sgl-kernel/src/sgl-kernel/csrc`
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2. Expose interface in `sgl-kernel/csrc/sgl_kernel_ops.cu` with pybind11
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3. Create Python wrapper in `sgl-kernel/src/sgl-kernel/ops/__init__.py`
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4. Expose Python interface in `sgl-kernel/src/sgl-kernel/__init__.py`
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### Build & Install
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Development build:
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```bash
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make build
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pip3 install dist/*whl --force-reinstall --no-deps
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# Or use: make install (runs pip install -e .)
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```
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### Testing & Benchmarking
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1. Add pytest tests in `sgl-kernel/tests/`
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2. Add benchmarks using [triton benchmark](https://triton-lang.org/main/python-api/generated/triton.testing.Benchmark.html) in `sgl-kernel/benchmark/`
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3. Run test suite
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