docker
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docker [2019/11/29 15:00] – [Proposed solution] mimbert | docker [2019/12/06 13:34] – [Proposed solution] mimbert | ||
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The proposed solution is to use [[https:// | The proposed solution is to use [[https:// | ||
- | * [[https:// | + | * [[https:// |
* Preparing an image is a much more convenient process than preparing a task, when it comes to complex software bundles such as TensorFlow, OpenBTS, etc. One just needs to install dependencies and build as if it was a real machine, there is no need to tweak or hack build steps, it just works directly. | * Preparing an image is a much more convenient process than preparing a task, when it comes to complex software bundles such as TensorFlow, OpenBTS, etc. One just needs to install dependencies and build as if it was a real machine, there is no need to tweak or hack build steps, it just works directly. | ||
* Image preparation can be an interactive process, or it can be automated with a [[https:// | * Image preparation can be an interactive process, or it can be automated with a [[https:// | ||
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* When running a task, images are instanciated to [[https:// | * When running a task, images are instanciated to [[https:// | ||
* The experiment results are structured differently. For each node, there is one directory per container, containing the stdout/ | * The experiment results are structured differently. For each node, there is one directory per container, containing the stdout/ | ||
- | | + | * The homes of the users are NFS mounted on the nodes, and the home of the user is mounted in the containers. This gives a lot of flexibility on the way to organize the experimental workflow, regarding input datasets, output datasets and experimental code. Input dataset and code can be put in the images, in the user's home or in the task's scenario. Output dataset can be put in the user's home or can be retrieved from the results. Some precautions have to be taken regarding performance, |
docker.txt · Last modified: 2023/09/28 17:24 by cmorin