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[MUSA] Add installation guide and Dockerfile (#36709)

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Co-authored-by: zhiguo.qin <zhiguo.qin@mthreads.com>
Co-authored-by: Kangyan-Zhou <zky314343421@gmail.com>
This commit is contained in:
ori
2026-09-06 20:13:53 -05:00
committed by GitHub
co-authored by zhiguo.qin Kangyan-Zhou
parent 707da81e84
commit 39a80354aa
6 changed files with 244 additions and 19 deletions
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docker/musa.Dockerfile
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# syntax=docker/dockerfile:1.7
# Usage:
# docker build -f docker/musa.Dockerfile -t sglang:main-musa .
# docker run --rm -it --network=host \
# --env MTHREADS_VISIBLE_DEVICES=0 \
# --env MTHREADS_DRIVER_CAPABILITIES=all \
# --shm-size=32g \
# sglang:main-musa
ARG BASE_IMAGE=ubuntu:22.04
FROM ${BASE_IMAGE}
SHELL ["/bin/bash", "-o", "pipefail", "-c"]
ARG DEBIAN_FRONTEND=noninteractive
ARG MUSA_APT_SOURCE=https://dl.mthreads.com/repo/repository/ubuntu2204/
ARG MUSA_PIP_INDEX_URL=https://dl.mthreads.com/repo/api/pypi/pypi/simple
ARG PYPI_INDEX_URL=https://pypi.org/simple
ENV MUSA_HOME=/usr/local/musa \
MATE_MUSA_ARCH_LIST=3.1 \
PATH=/usr/local/musa/bin:/usr/local/musa/mudnn/bin:${PATH} \
LD_LIBRARY_PATH=/usr/local/musa/lib:/usr/local/musa/mudnn/lib:/usr/local/mtshmem/lib:/usr/local/lib \
TORCH_EXTENSIONS_DIR=/root/.cache/torch_extensions \
TRITON_CACHE_DIR=/root/.triton/cache
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
bash \
build-essential \
ca-certificates \
cmake \
curl \
ffmpeg \
g++ \
gcc \
git \
libmkl-core \
libmkl-def \
libmkl-gnu-thread \
libmkl-intel-lp64 \
libmkl-vml-def \
libomp-dev \
libopenmpi3 \
libsndfile1 \
ninja-build \
pkg-config \
python-is-python3 \
python3 \
python3-dev \
python3-pip \
sox \
&& true
RUN echo "deb [trusted=true] ${MUSA_APT_SOURCE} jammy main" \
> /etc/apt/sources.list.d/mthreads-musa.list \
&& apt-get update \
&& apt-get install -y --no-install-recommends \
libmthreads-compute \
libmthreads-mtml \
libmublas-5-2 \
libmublaslt-5-2 \
libmudnn3-dev-musa-5-2 \
libmudnn3-musa-5-2 \
libmufft-5-2 \
libmupp-5-2 \
libmurand-5-2 \
libmusolver-5-2 \
libmusparse-5-2 \
mccl-s5000 \
mccl-s5000-dev \
mtcc-5-2 \
musa-mualg-5-2 \
musa-mupti-5-2 \
musa-musart-5-2 \
musa-muthrust-5-2 \
musa-toolkit-5-2 \
musa-toolkit-5-2-config-common \
&& printf '%s\n' \
"${MUSA_HOME}/lib" \
"${MUSA_HOME}/mudnn/lib" \
"/usr/local/mtshmem/lib" \
"/usr/lib/x86_64-linux-gnu" \
> /etc/ld.so.conf.d/musa-runtime.conf \
&& ln -sf /usr/lib/x86_64-linux-gnu/libmkl_intel_lp64.so /usr/lib/x86_64-linux-gnu/libmkl_intel_lp64.so.2 \
&& ln -sf /usr/lib/x86_64-linux-gnu/libmkl_core.so /usr/lib/x86_64-linux-gnu/libmkl_core.so.2 \
&& ln -sf /usr/lib/x86_64-linux-gnu/libmkl_gnu_thread.so /usr/lib/x86_64-linux-gnu/libmkl_gnu_thread.so.2 \
&& ldconfig
RUN python -m pip install --upgrade pip "setuptools<82" wheel
WORKDIR /workspace/sglang
COPY . .
# Pip does not prioritize --index-url over --extra-index-url for equal-version
# candidates. Reinstall Triton from the MUSA index in this same layer.
RUN cp python/pyproject_other.toml python/pyproject.toml \
&& python -m pip install -e "python[all_musa]" \
--index-url "${MUSA_PIP_INDEX_URL}" \
--extra-index-url "${PYPI_INDEX_URL}" \
--trusted-host dl.mthreads.com \
--no-build-isolation \
&& python -m pip install --no-cache-dir --force-reinstall --no-deps \
--index-url "${MUSA_PIP_INDEX_URL}" \
--trusted-host dl.mthreads.com \
"triton==3.2.0" \
&& python -c "import triton.backends.mtgpu" \
&& ! python -m pip freeze | grep -E '^(nvidia-|cuda-)'
RUN cd python/sglang/kernels/aot \
&& cp pyproject_musa.toml pyproject.toml \
&& MTGPU_TARGET=mp_31 python setup_musa.py install
# Keep this check in a single shell command: the legacy Docker builder does not
# reliably preserve Dockerfile heredocs and can turn the check into a silent
# `python -` EOF success.
RUN python -c \
"import torch; \
assert getattr(torch.version, 'musa', None), torch.__version__; \
assert hasattr(torch, 'musa'); \
import torchada, triton, tilelang, sglang; \
import triton.backends.mtgpu"
CMD ["/bin/bash"]
docs/docs/hardware-platforms/mthreads_gpu.mdx
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@@ -4,7 +4,20 @@ metatags:
description: "Run SGLang on Moore Threads GPUs."
---
This document describes how run SGLang on Moore Threads GPUs. If you encounter issues or have questions, please [open an issue](https://github.com/sgl-project/sglang/issues).
This document describes how to run SGLang on Moore Threads GPUs. If you
encounter issues or have questions, please [open an issue](https://github.com/sgl-project/sglang/issues).
SGLang uses the MUSA runtime through
[`torch_musa`](https://github.com/MooreThreads/torch_musa) and
[`torchada`](https://github.com/MooreThreads/torchada). The
`python[all_musa]` extra installs the MUSA torch, Triton, TileLang, MATE, and
runtime Python stack from the Moore Threads package index, with public PyPI as
the fallback for common Python dependencies.
## Prerequisites
Install the Moore Threads driver and MUSA toolkit before installing SGLang. For
MTT S5000, follow the [official driver installation guide](https://docs.mthreads.com/driver-linux-server/driver-linux-server-doc-online/MTT_S5000/install_guide).
## Install SGLang
@@ -12,18 +25,92 @@ You can install SGLang using one of the methods below.
### Install from Source
```bash
# Use the default branch
Start from an environment with the prerequisites above installed.
```bash Command
git clone https://github.com/sgl-project/sglang.git
cd sglang
# Compile sgl-kernel
pip install --upgrade pip
cd python/sglang/kernels/aot
python setup_musa.py install
python -m pip install --upgrade pip "setuptools<82" wheel
cp python/pyproject_other.toml python/pyproject.toml
python -m pip install -e "python[all_musa]" \
--index-url https://dl.mthreads.com/repo/api/pypi/pypi/simple \
--extra-index-url https://pypi.org/simple \
--trusted-host dl.mthreads.com \
--no-build-isolation
# Install sglang python package along with diffusion support
cd ../../../..
rm -f python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
pip install -e "python[all_musa]"
# Ensure the MUSA Triton wheel (with triton.backends.mtgpu) is installed.
python -m pip install --no-cache-dir --force-reinstall --no-deps \
--index-url https://dl.mthreads.com/repo/api/pypi/pypi/simple \
--trusted-host dl.mthreads.com \
triton==3.2.0
python -c 'import triton.backends.mtgpu'
cd python/sglang/kernels/aot
cp pyproject_musa.toml pyproject.toml
MTGPU_TARGET=mp_31 python setup_musa.py install
```
### Install Using Docker
The Dockerfile installs the MUSA runtime and Python stack declared by
`python/pyproject_other.toml`.
```bash Command
git clone https://github.com/sgl-project/sglang.git
cd sglang
docker build -f docker/musa.Dockerfile -t sglang:main-musa .
```
Run the image with MUSA devices exposed by the host container toolkit.
```bash Command
alias drun='docker run -it --rm --network=host \
--env MTHREADS_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
--env MTHREADS_DRIVER_CAPABILITIES=all \
--shm-size=32g \
-v ~/.cache/huggingface:/root/.cache/huggingface'
drun sglang:main-musa \
python3 -c 'import triton.backends.mtgpu; print("MUSA Triton backend OK")'
```
Launch the server:
```bash Command
drun sglang:main-musa \
python3 -m sglang.launch_server \
--model-path Qwen/Qwen3-8B \
--host 0.0.0.0 \
--port 30000
```
When the server displays `The server is fired up and ready to roll!`, startup is
successful.
## Verify
You can send an OpenAI-compatible request to the engine:
```bash Command
curl http://127.0.0.1:30000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "Qwen/Qwen3-8B",
"messages": [{"role": "user", "content": "Hello!"}],
"max_tokens": 32
}'
```
Or run a benchmark:
```bash Command
drun sglang:main-musa \
python3 -m sglang.bench_serving \
--backend sglang \
--dataset-name random \
--num-prompts 4000 \
--random-input 128 \
--random-output 128
```
docs/docs/hardware-platforms/overview.mdx
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@@ -10,3 +10,4 @@ description: Platform-specific guides for running SGLang on GPUs, TPUs, NPUs, CP
- [NVIDIA Jetson Orin](./nvidia_jetson)
- [TPU](./tpu)
- [XPU](./xpu)
- [Moore Threads GPUs](./mthreads_gpu)
docs/index.mdx
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@@ -50,7 +50,7 @@ import { PopularModels } from "/src/snippets/_popular_models.jsx";
<Card title="Extensive Hardware Support" icon="microchip">
Native support across <a href="./docs/hardware-platforms/overview">Hardware Platforms</a>
including NVIDIA, AMD, Intel Xeon, Google TPU, and Ascend NPU accelerators.
including NVIDIA, AMD, Intel Xeon, Google TPU, Ascend NPU, and Moore Threads MUSA accelerators.
</Card>
<Card title="Community & Training" icon="users">
python/pyproject_other.toml
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@@ -144,15 +144,26 @@ srt_hpu = ["sglang[runtime_common]"]
# https://docs.sglang.io/platforms/mthreads_gpu.md
srt_musa = [
"deep-gemm>=0.1.3",
"flash_attn_3>=0.1.4",
"mate>=0.2.0",
"apache-tvm-ffi==0.1.11.post1+musa.1",
"deep_ep==1.1.0+musa5.2.0torch2.11.0.post1",
"deep-gemm==0.2.6+musa",
"flash_attn_3==0.2.6+musa",
"flash_mla==0.2.6+musa",
"flashinfer-python==0.2.6+musa",
"mate==0.2.6",
"mate-mubin==0.2.6",
"mthreads-ml-py",
"numpy<2.0",
"sageattention==0.2.6+musa",
"sglang[runtime_common]",
"torch",
"torch_musa",
"torchada>=0.1.74",
"tilelang_musa==0.1.12+musa.2",
"torch==2.11.0.post1+musa5.2.0",
"torch-c-dlpack-ext==0.1.5",
"torch_musa==2.11.0.post1+musa5.2.0",
"torchada>=0.1.86",
"torchaudio==2.11.0+musa5.2.0",
"torchvision==0.26.0.post1+musa5.2.0",
"triton==3.2.0",
]
diffusion_musa = [
python/sglang/kernels/aot/pyproject_musa.toml
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@@ -3,7 +3,7 @@ requires = [
"setuptools>=75.0",
"scikit-build-core>=0.10",
"torch",
"torchada>=0.1.74",
"torchada>=0.1.86",
"wheel",
]
build-backend = "setuptools.build_meta"