chenchenghao/sglang
1
0
Fork 0
Code Issues Pull Requests Actions 11 Packages Projects Releases Wiki Activity

Release sglang kernel 0.4.0 (#20440)

Browse Source 
Co-authored-by: Baizhou Zhang <sobereddiezhang@gmail.com>
This commit is contained in:
Xiaoyu Zhang
2026-03-16 20:34:58 +08:00
committed by GitHub
co-authored by Baizhou Zhang
parent 3d58cd16d9
commit 15097c5c3b
36 changed files with 188 additions and 146 deletions
Download Patch File Download Diff File Expand all files Collapse all files
sgl-kernel/README.md
+7 -7
View File
@@ -1,22 +1,22 @@
# sgl-kernel
# sglang-kernel (prior sgl-kernel)
[Kernel Library](https://github.com/sgl-project/sglang/tree/main/sgl-kernel) for LLM inference engines
<div align="center">
[![License: Apache-2.0](https://img.shields.io/badge/License-Apache--2.0-blue.svg)](https://github.com/sgl-project/sglang/blob/main/LICENSE)
[![PyPI](https://img.shields.io/pypi/v/sgl-kernel)](https://pypi.org/project/sgl-kernel)
[![PyPI](https://img.shields.io/pypi/v/sglang-kernel)](https://pypi.org/project/sglang-kernel)
</div>
sgl-kernel provides optimized compute primitives for LLM inference engines, enabling efficient inference for large language models and vision-language models through custom kernel operations. It has been used by [LightLLM](https://github.com/ModelTC/LightLLM), [SGLang](https://github.com/sgl-project/sglang) and so on.
`sglang-kernel` provides optimized compute primitives for LLM inference engines, enabling efficient inference for large language models and vision-language models through custom kernel operations. The source tree remains under the `sgl-kernel/` directory and the Python import path remains `sgl_kernel`.
## Installation
Requires torch == 2.9.1
```bash
# Latest version
pip3 install sgl-kernel --upgrade
pip3 install sglang-kernel --upgrade
```
## Building from Source
@@ -26,7 +26,7 @@ Requires
- scikit-build-core
- ninja(optional)
### Use Makefile to build sgl-kernel
### Use Makefile to build from the sgl-kernel source tree
```bash
make build
@@ -125,10 +125,10 @@ This tool requires `cubloaty` (install with `pip install cubloaty`) to work.
pip install cubloaty
# Analyze a wheel file
python analyze_whl_kernel_sizes.py path/to/sgl_kernel-*.whl
python analyze_whl_kernel_sizes.py path/to/sglang_kernel-*.whl
# Custom output file
python analyze_whl_kernel_sizes.py path/to/sgl_kernel-*.whl --output my_analysis.txt
python analyze_whl_kernel_sizes.py path/to/sglang_kernel-*.whl --output my_analysis.txt
```
The tool generates: