[Kernel] Move sgl-kernel under sglang.kernels.aot (#32648)
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@@ -14,7 +14,7 @@ Add a new operation that scales each element of a tensor by a scalar factor:
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- Input: tensor `x` (CUDA) and scalar `factor` (float)
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- Output: `x * factor` (element-wise, in-place or into pre-allocated `out`)
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- Supported dtypes: **FP16 (`torch.float16`), BF16 (`torch.bfloat16`), FP32 (`torch.float32`)**
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- Dispatched via `DISPATCH_PYTORCH_DTYPE_TO_CTYPE_FLOAT_FP16` macro (defined in `sgl-kernel/include/utils.h`)
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- Dispatched via `DISPATCH_PYTORCH_DTYPE_TO_CTYPE_FLOAT_FP16` macro (defined in `python/sglang/kernels/aot/include/utils.h`)
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## Two rules of thumb (must follow)
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@@ -33,13 +33,13 @@ In addition, every new kernel must ship with:
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You will typically touch these files/areas:
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- Implementation: `sgl-kernel/csrc/elementwise/scale.cu` (pick the right subdirectory)
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- Public declarations: `sgl-kernel/include/sgl_kernel_ops.h`
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- Torch extension registration: `sgl-kernel/csrc/common_extension.cc`
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- Build: `sgl-kernel/CMakeLists.txt` (`set(SOURCES ...)`)
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- Python API: `sgl-kernel/python/sgl_kernel/` and `sgl-kernel/python/sgl_kernel/__init__.py`
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- Tests: `sgl-kernel/tests/test_scale.py`
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- Benchmarks: `sgl-kernel/benchmark/bench_scale.py`
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- Implementation: `python/sglang/kernels/aot/csrc/elementwise/scale.cu` (pick the right subdirectory)
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- Public declarations: `python/sglang/kernels/aot/include/sgl_kernel_ops.h`
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- Torch extension registration: `python/sglang/kernels/aot/csrc/common_extension.cc`
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- Build: `python/sglang/kernels/aot/CMakeLists.txt` (`set(SOURCES ...)`)
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- Python API: `python/sglang/kernels/aot/python/sgl_kernel/` and `python/sglang/kernels/aot/python/sgl_kernel/__init__.py`
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- Tests: `python/sglang/kernels/aot/tests/test_scale.py`
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- Benchmarks: `python/sglang/kernels/aot/benchmark/bench_scale.py`
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---
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@@ -50,7 +50,7 @@ Pick the right subdirectory:
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- `csrc/elementwise/` — for element-wise ops (our example)
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- `csrc/gemm/`, `csrc/attention/`, `csrc/moe/` — for other categories
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Create `sgl-kernel/csrc/elementwise/scale.cu`:
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Create `python/sglang/kernels/aot/csrc/elementwise/scale.cu`:
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```cpp
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#include <ATen/cuda/CUDAContext.h>
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@@ -115,7 +115,7 @@ void scale(at::Tensor& out, const at::Tensor& input, double factor) {
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## Step 2: Add a C++ declaration in `include/sgl_kernel_ops.h`
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Edit `sgl-kernel/include/sgl_kernel_ops.h`, add to the elementwise section:
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Edit `python/sglang/kernels/aot/include/sgl_kernel_ops.h`, add to the elementwise section:
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```cpp
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void scale(at::Tensor& out, const at::Tensor& input, double factor);
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@@ -125,7 +125,7 @@ void scale(at::Tensor& out, const at::Tensor& input, double factor);
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## Step 3: Register the op in `csrc/common_extension.cc`
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Edit `sgl-kernel/csrc/common_extension.cc`, inside `TORCH_LIBRARY_FRAGMENT(sgl_kernel, m)`:
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Edit `python/sglang/kernels/aot/csrc/common_extension.cc`, inside `TORCH_LIBRARY_FRAGMENT(sgl_kernel, m)`:
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```cpp
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// From csrc/elementwise
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@@ -143,7 +143,7 @@ m.impl("scale", torch::kCUDA, &scale);
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## Step 4: Add the new source file to `CMakeLists.txt`
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Edit `sgl-kernel/CMakeLists.txt`, add to `set(SOURCES ...)`:
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Edit `python/sglang/kernels/aot/CMakeLists.txt`, add to `set(SOURCES ...)`:
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```cmake
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csrc/elementwise/scale.cu
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@@ -156,14 +156,14 @@ csrc/elementwise/scale.cu
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---
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## Step 5: Expose a Python API under `sgl-kernel/python/sgl_kernel/`
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## Step 5: Expose a Python API under `python/sglang/kernels/aot/python/sgl_kernel/`
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Prefer following the existing module organization first. For elementwise kernels, the usual pattern is:
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- implement the Python wrapper in `sgl-kernel/python/sgl_kernel/elementwise.py`
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- then re-export it from `sgl-kernel/python/sgl_kernel/__init__.py`
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- implement the Python wrapper in `python/sglang/kernels/aot/python/sgl_kernel/elementwise.py`
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- then re-export it from `python/sglang/kernels/aot/python/sgl_kernel/__init__.py`
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For example, in `sgl-kernel/python/sgl_kernel/elementwise.py`, add:
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For example, in `python/sglang/kernels/aot/python/sgl_kernel/elementwise.py`, add:
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```python
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import torch
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@@ -190,13 +190,13 @@ def scale(
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return out
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```
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Then re-export it from `sgl-kernel/python/sgl_kernel/__init__.py` following the existing import style used by other kernels.
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Then re-export it from `python/sglang/kernels/aot/python/sgl_kernel/__init__.py` following the existing import style used by other kernels.
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---
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## Step 6: Write tests (required)
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Create `sgl-kernel/tests/test_scale.py`:
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Create `python/sglang/kernels/aot/tests/test_scale.py`:
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```python
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import pytest
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@@ -241,7 +241,7 @@ if __name__ == "__main__":
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## Step 7: Add a benchmark (required)
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Create `sgl-kernel/benchmark/bench_scale.py`:
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Create `python/sglang/kernels/aot/benchmark/bench_scale.py`:
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```python
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import itertools
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@@ -306,14 +306,14 @@ if __name__ == "__main__":
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Build:
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```bash
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cd sgl-kernel
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cd python/sglang/kernels/aot
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make build -j16
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```
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If you need to limit host resource usage:
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```bash
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cd sgl-kernel
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cd python/sglang/kernels/aot
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make build -j1 MAX_JOBS=2 CMAKE_ARGS="-DSGL_KERNEL_COMPILE_THREADS=1"
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```
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@@ -324,8 +324,8 @@ make build -j1 MAX_JOBS=2 CMAKE_ARGS="-DSGL_KERNEL_COMPILE_THREADS=1"
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After building successfully, run the test and benchmark:
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```bash
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pytest sgl-kernel/tests/test_scale.py -q
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python sgl-kernel/benchmark/bench_scale.py
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pytest python/sglang/kernels/aot/tests/test_scale.py -q
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python python/sglang/kernels/aot/benchmark/bench_scale.py
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```
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PR CI also runs `pr-test-sgl-kernel.yml`, including the B200 job
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@@ -339,29 +339,29 @@ Blackwell coverage signal for AOT `sgl-kernel` changes.
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- **Async CUDA errors**: `CUDA_LAUNCH_BLOCKING=1`
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- **Memory errors**: `compute-sanitizer --tool memcheck python ...`
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- **Build is too slow / OOM**: reduce `MAX_JOBS` and `SGL_KERNEL_COMPILE_THREADS`
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- **Binary bloat**: use `sgl-kernel/analyze_whl_kernel_sizes.py`
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- **Binary bloat**: use `python/sglang/kernels/aot/analyze_whl_kernel_sizes.py`
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- **CMake sources list**: if your `.cu` file is missing from `SOURCES`, the symbol will be undefined at link time
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---
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## References
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- `sgl-kernel/README.md`
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- `sgl-kernel/include/sgl_kernel_ops.h`
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- `sgl-kernel/csrc/common_extension.cc`
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- `sgl-kernel/CMakeLists.txt`
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- `sgl-kernel/include/utils.h` — `DISPATCH_PYTORCH_DTYPE_TO_CTYPE_FLOAT_FP16` macro and friends
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- `sgl-kernel/csrc/elementwise/activation.cu` — reference for the FP16/BF16/FP32 dispatch pattern
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- `python/sglang/kernels/aot/README.md`
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- `python/sglang/kernels/aot/include/sgl_kernel_ops.h`
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- `python/sglang/kernels/aot/csrc/common_extension.cc`
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- `python/sglang/kernels/aot/CMakeLists.txt`
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- `python/sglang/kernels/aot/include/utils.h` — `DISPATCH_PYTORCH_DTYPE_TO_CTYPE_FLOAT_FP16` macro and friends
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- `python/sglang/kernels/aot/csrc/elementwise/activation.cu` — reference for the FP16/BF16/FP32 dispatch pattern
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## Summary of Files Created/Modified
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```
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sgl-kernel/csrc/elementwise/scale.cu # NEW: CUDA kernel + launcher
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sgl-kernel/include/sgl_kernel_ops.h # MODIFIED: C++ declaration
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sgl-kernel/csrc/common_extension.cc # MODIFIED: schema + dispatch registration
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sgl-kernel/CMakeLists.txt # MODIFIED: add source file (alphabetical)
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sgl-kernel/python/sgl_kernel/elementwise.py # MODIFIED: Python wrapper
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sgl-kernel/python/sgl_kernel/__init__.py # MODIFIED: re-export Python API
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sgl-kernel/tests/test_scale.py # NEW: tests
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sgl-kernel/benchmark/bench_scale.py # NEW: benchmark
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python/sglang/kernels/aot/csrc/elementwise/scale.cu # NEW: CUDA kernel + launcher
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python/sglang/kernels/aot/include/sgl_kernel_ops.h # MODIFIED: C++ declaration
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python/sglang/kernels/aot/csrc/common_extension.cc # MODIFIED: schema + dispatch registration
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python/sglang/kernels/aot/CMakeLists.txt # MODIFIED: add source file (alphabetical)
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python/sglang/kernels/aot/python/sgl_kernel/elementwise.py # MODIFIED: Python wrapper
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python/sglang/kernels/aot/python/sgl_kernel/__init__.py # MODIFIED: re-export Python API
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python/sglang/kernels/aot/tests/test_scale.py # NEW: tests
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python/sglang/kernels/aot/benchmark/bench_scale.py # NEW: benchmark
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```
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