IN5490 - Autumn 2021

Computational Resources

For your projects, you may require some extra resources to do your experiments. Here is information about your options. If you have any questions about them, please contact one of us in the course staff or your supervisor. It is also a good idea to check out these lecture slides when considering your computational resources.

ML-Nodes

This is the main resource for those of you doing GPU-intensive jobs, such as in Deep Learning. The service is quite easy to get started with, check out their instructions here. The machines are set up to allow you to use typical deep learning frameworks. However if there is any software you are missing on the machines, you can contact the AI-Hub team (itf-ai-support@usit.uio.no) and they are quick to install it for you. You can also install additional Python packages yourself.

Sigma2 NIRD Platform

Use Saga instead (see below)

The NIRD platform is a good service for quick and easy access to some CPUs. The NIRD platform grants every student of this course 20 CPU cores from 1 October 2021 to the 1 January 2022 . The supplied services run in containers to ensure high portability of the tools and reproducibility of the results and is easy to use. To get access to this service platform you will need to

  •  Submit a user application to project ns9989k through the following form: https://www.metacenter.no/user/application/form/norstore/
  • Fill in the start dates and end dates as (if prompted):

    • Start date 2021-10-01

    • End date 2022-01-01

  • It is important that you fill in your full Feide username in the last field (EduPPN) in order to access the project in the Toolkit.

Saga

Saga is a super computer in Trondheim designed to run heavy duty CPU/GPU jobs. It contains over 300 ndes with each more than 40 cores to run your jobs on. This is an excellent resource for evolutionary experiments to run many jobs in parallel. To get access to saga you will have to fill out the following form: https://www.metacenter.no/user/application/form/notur . Saga uses the SLURM job scheduler. More information on the resource can be found here.

Fox

Fox has both CPUs and GPUs that you can use, and could be a good choice, since it is new, not too much utilized yet, and easy to get access to. To get access, follow the steps below:

1. Go to https://research.educloud.no/register
2. Select “Apply for access to a project”
3. Click “Next” until you can select which project to join
4. Select “ec12: Fox”
5. Wait for approval
6. Login with ssh -J <username>@login.uio.no <educloud-username>@fox.educloud.no
           a. Your Educloud username will likely be “ec-<UiO username>”

ROBIN-HPC

Check out the Sigma2 NIRD service platform before considering this.

This is a local service at ROBIN that may be useful for those of you running CPU-jobs. You can get access for it by filling out this form. Software: Both pip and conda is installed so you can install python packages (in pip, remember pip install --user <some_package>). For other needs, please contact robin-engineer@ifi.uio.no

ROBIN-workstations

These are local GPU-machines that can be useful if any of you have very specific requirements that mean your experiments cannot run on an external service. There is no queue management on these machines, so the policy is "first comes, first served". If you are a ROBIN-student, you already have access (see how to access the machines here). If you are not a ROBIN-student and need access please contact robin-engineer@ifi.uio.no.

Software: Both pip and conda is installed so you can install python packages (in pip, remember pip install --user <some_package>). For other needs, please contact robin-engineer@ifi.uio.no.

Course-resources as a service

Information about this coming soon

Published June 8, 2021 1:39 PM - Last modified Oct. 5, 2021 4:07 PM
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