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An ansible playbook to deploy a complete standalone neuroimaging workstation

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NeuroAnsible

An ansible playbook to deploy a complete standalone neuroimaging workstation.

Sponsorship

This software is developed and supported by Gabriel Devenyi Consulting.

To request support in the use of this deployment software, or request additional software be added, please contact us.

Prerequisites

This ansible playbook was developed on Ubuntu 22.04 and 24.04 and likely works on all variants (Ubuntu, Kubuntu, Lubuntu, etc.)

This playbook also succcessfully executes on WSL installations on Ubuntu.

Prerequistes to use this playbook is installation of ansible.

Total installation size as of 2024-05-24 is approximately 110GB.

This can be significantly reduced by skipping the installation of the resources with --skip-tags resources

Software Requirements

This playbook uses ansible to deploy on the machine controlling the setup. This machine does not need to be the machine that will ultimately be the setup workstation.

See the Ansible installation guide.

Once ansible is installed, you will need to pull in a external role used by this package:

$ ansible-galaxy role install mambaorg.micromamba

Use

Clone a copy of the repository and run the ansible playbook

You must have sudo access to make changes to the system.

Now you can setup the system by running the ansible playbook:

$ ansible-playbook --ask-become-pass deploy.yml

Ansible will prompt you for a sudo password (--ask-become-pass). If you have passwordless sudo you can omit this.

Customize Software

The playbook is customizable with tags, by default all tags are executed.

See ansible-playbook --list-tags deploy.yml for tags available to limit execution.

You can either select specific tags with --tags as an option to the playbook call, or skip specific tasks with --skip-tags

MATLAB users may be interested in the optional matlab tag, which provides a number of MATLAB toolboxes.

NVidia users should include the nvidia tag to install the nvhpc packages to provide all currently supported versions of cuda as modules.

Using the installed software

All software is installed using the lmod module system. Once deployment is complete the next time a terminal is opened, the command module avail will list the software which can be used. Use module load to make a specific package available in the terminal.

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