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aiidalab/aiidalab-docker-stack

By aiidalab

•Updated over 3 years ago

Docker stack for the AiiDA lab (https://aiidalab.materialscloud.org)

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aiidalab/aiidalab-docker-stack repository overview

⁠Docker Stack for AiiDAlab

This repo contains the Docker file used in the AiiDAlab⁠.

Docker images are available from Dockerhub via docker pull aiidalab/aiidalab-docker-stack:latest. See aiidalab/aiidalab-docker-stack⁠ for a list of available tags.

⁠Deploy on AiiDAlab server

To deploy changes, log into the AiiDAlab server and execute the following commands:

docker pull aiidalab/aiidalab-docker-stack:latest
docker tag aiidalab/aiidalab-docker-stack:latest aiidalab-docker-stack:latest

The users will gradually pick up the new image, whenever they restart their container via the Control Panel.

⁠Deploy locally

Make sure that Docker is installed on your machine, otherwise go to Docker installation page⁠ and follow the instructions for your operating system.

Then, start AiiDAlab:

./run.sh PORT PATH_TO_AIIDALAB_HOME_DIR

Where PORT is any free port on your machine (typically it is 8888) and PATH_TO_AIIDALAB_HOME_DIR is an absolute path to the folder where user's data will be stored (typically it is something like ${HOME}/aiidalab). The last line of the output of the command above will contain the link to access AiiDAlab in your browser.

⁠Slow IO

To check for issues with OpenStack's block storage observe the following command for a few minutes:

watch -n 0.1 "ps axu| awk '{print \$8, \"   \", \$11}' | sort | head -n 10"

Pretty much all processes should be in the S state. If a process stays in the D state for a longer time it is most likely waiting for slow IO.

⁠Citation

Users of AiiDAlab are kindly asked to cite the following publication in their own work:

A. V. Yakutovich et al., Comp. Mat. Sci. 188, 110165 (2021). DOI:10.1016/j.commatsci.2020.110165⁠

⁠Acknowledgements

This work is supported by the MARVEL National Centre for Competency in Research⁠ funded by the Swiss National Science Foundation⁠, as well as by the MaX European Centre of Excellence⁠ funded by the Horizon 2020 EINFRA-5 program, Grant No. 676598.

MARVEL MaX

Tag summary

Content type

Image

Digest

sha256:3ab7edc9a…

Size

1.8 GB

Last updated

over 3 years ago

docker pull aiidalab/aiidalab-docker-stack