Docker Installation (CPU Only)
no-gpu Deployment¶
Suitable for users without a GPU or who only need logic testing.
- step 0 Pull the Docker base image
For users in China, it is recommended to pull the base image from a domestic mirror first:
docker pull docker.m.daocloud.io/library/ubuntu:24.04
docker tag docker.m.daocloud.io/library/ubuntu:24.04 ubuntu:24.04
- step 1 Disable CUDA
Create a config.mk.local file in the project root directory (not inside the docker_install folder) to disable CUDA:
- step 2 Build the Docker image
# a. Using Tsinghua mirror (recommended for users in China):
docker build -t psum:no-gpu \
--build-arg MIRROR_URL=//mirrors.tuna.tsinghua.edu.cn \
-f docker_install/dockerfile_no_gpu .
- step 3 Start the container
Run the following command in the project root directory to enter the container. Note that the -v flag maps your current source directory to the container's /workspace:
- step 4 Compile inside the container
After entering the container terminal, execute the following standard procedure:
Build results:
- Field solver: CPU ✅ | Multigrid ✅ | Direct ✅ | GPU ❌ (no-gpu version)
- Pypsum serialization: ✅ Build succeeded | ✅ Python interaction test passed
Since -v $(pwd):/workspace is used, code modifications made via VS Code on the host machine will be synchronized inside the container, and make or test executions will take effect accordingly.
After configuration, you should be able to correctly compile and run PSuM code inside the container.
Finally, add the contents of env_load.sh from the project folder to the ~/.bashrc file inside the container, so that environment variables are automatically loaded when entering the container.
Later, to re-enter the container: