gpu-deploy

Fabric library for Docker GPU deployment

Requirements: nvidia-docker 2.0.3, nvidia-container-runtime 1.0.0

On all host machines, set the default docker runtime to nvidia by adding the line "default-runtime": "nvidia" to /etc/docker/daemon.json

Instalation

pip3 install Fabric3
pip3 install git+https://github.com/atlab/gpu-deploy.git

Usage

See the fabfile.py in the example/ folder for an example usage of gpu_deploy. /example/ is a template for organizing required files; notice how these files are organized in directories: Dockerfile and docker-compose.yml must be together in a directory, all *.py scripts must be together in another directory, and the .env file can be in any location specified by the user.

Navigate to the example directory:

    cd example

To launch 2 jupyter notebook containers on the host at-gpu-ex.bdc.bcm.edu with 3 gpus per container:

    fab -H at-gpu-ex.bdc.bcm.edu deploy_atlab:n=2,gpus=3

To stop all of these jupyter notebook containers:

    fab -H at-gpu-ex.bdc.bcm.edu stop_atlab

To run 4 hello.py jobs on the host at-gpu-ex.bdc.bcm.edu with 1 gpu per container:

    fab -H at-gpu-ex.bdc.bcm.edu deploy_atlab:hello,n=4

To stop these hello.py jobs:

    fab -H at-gpu-ex.bdc.bcm.edu stop_atlab:hello