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R0CKSTARandyeahdongcn
18b74ff68e
* musa: build the docker image and CI container from the MUSA SDK images
Use registry.mthreads.com/mcconline/musa_sdk:5.2.0-{devel,runtime}-ubuntu22.04-s5000
instead of registry.mthreads.com/mcconline/inference/pytorch:2.9.1.post1-py3.10-musa5.2.0-mp31-devel-ubuntu22.04-amd64
for the MUSA docker image and the MUSA CI container, and let the runtime stage use the
runtime image instead of reusing the devel one, which drops the MUSA toolchain from the
published images.
* musa: install the MUSA headers and loader path the SDK images omit
musa_sdk:5.2.0-*-s5000 does not ship the cub and thrust headers that the MUSA
backend builds against, and its runtime image does not register
/usr/local/musa/lib with the dynamic loader.
Install both header packages in the build stage and in the MUSA CI container,
and write the loader path in the runtime stage.
* musa: install libmthreads-compute for the MUSA runtime library
The MUSA SDK images do not install libmthreads-compute, which provides
libmusa.so.1 in /usr/lib/x86_64-linux-gnu, so linking anything against the
MUSA backend fails.
* musa: install libmthreads-compute in the runtime stages
The MUSA runtime image does not install libmthreads-compute, so the published
images would have no libmusa.so.1 at run time.
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Co-authored-by: yeahdongcn <yeahdongcn@users.noreply.github.com>
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Running MUSA CI in a Docker Container
Assuming $PWD is the root of the llama.cpp repository, follow these steps to set up and run MUSA CI in a Docker container:
1. Create a local directory to store cached models, configuration files and venv:
mkdir -p $HOME/llama.cpp/ci-cache
2. Create a local directory to store CI run results:
mkdir -p $HOME/llama.cpp/ci-results
3. Start a Docker container and run the CI:
docker run --privileged -it \
-v $HOME/llama.cpp/ci-cache:/ci-cache \
-v $HOME/llama.cpp/ci-results:/ci-results \
-v $PWD:/ws -w /ws \
registry.mthreads.com/mcconline/musa_sdk:5.2.0-devel-ubuntu22.04-s5000
Inside the container, execute the following commands:
apt update -y && apt install -y bc cmake ccache git python3.10-venv time unzip wget musa-mualg-5-2 musa-muthrust-5-2 libmthreads-compute
git config --global --add safe.directory /ws
GG_BUILD_MUSA=1 bash ./ci/run.sh /ci-results /ci-cache
This setup ensures that the CI runs within an isolated Docker environment while maintaining cached files and results across runs.