Overview of the computing resources at the University of Oslo

UiO offers a series of computing resources that are available for your research project. Here is an overview of the computing resources and guide on how to choose one that fits your purpose and style.

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What’s your style?

To get started, you can use Jupyter (4) and VDI (3) which are good for developing and prototyping. Then to scale up, you can use the options: 7, 9, 11. If you need the most power or flexibility, use the services from the Norwegian e-infrastructure for Research & Education (Sigma2) for your data storage and computation (Apply for Sigma2 resources and account required for 10 and 11).

If you need simple applications with a graphical interface, try 3 (VDI).

If you use your own laptop/desktop (1, 2), then it’s good for getting started but you have to copy your data and code back and forth once you need to scale up.

Summary list for remote data analysis workflows

  • Good for data security: 3, 5, 6, 7, 10, 11

  • Good for prototyping, working on the go, doing tests, interactive work: 1, 2, 3, 4, 5, 6, 8

  • Shares UiO data (e.g. home folders): 2, 3, 6,

  • Easy to scale up, shares software, data, etc: 5, 9, 11

  • Largest resources available 11 (medium: 9, 10)

  • GPUs resources available 7, 9 (and to some extent 11)

Except if stated otherwise you will not be able to access your UiO data (UiO home & astra).

Note

If you are dealing with sensitive data, you would need to use dedicated services for sensitive data.

1. Own laptop/desktop computer

  • Can work from anywhere. Does not require internet connection. You are in control.
  • Not good for personal or confidential data. Computing resources might not be enough. Accessing large data remotely stored at UiO might be problematic - you will end up having to copy a lot. You have to manage software yourself.
  • Excellent for prototyping, working on the go, doing tests, interactive work (e.g. making figures). Don’t use it with large data or confidential / personal data.

2. UiO laptop

  • Same as above, plus same tools available as UiO employer. The list of tools pre-installed on your laptop usually may depends on your institute or department or local group policy (in particular for some paid software).

  • Usually not allowed to install yourself software/packages

  • Access to your UiO home area and ASTRA storage

3. Remote virtual machine (https://view.uio.no/)

  • Computing happens on remote. Data access happens on remote, so it is more secure.

  • Computing resources are limited.

  • Many packages available (often many more than what you can have on your laptop)

  • Excellent for prototyping, working on the go, doing tests, interactive work (e.g. making figures). More secure access to data.

  • Can access your home area

4. UiO Jupyterhub (https://jupyterhub.uio.no/)

  • Cloud based - resume work from anywhere. Includes command line via Jupyter Terminal. Local data can be copied (a procedure is available if this service is used for teaching) but no access to your UiO data.

  • Jupyter can become a mess if you aren’t careful. You need to plan to scale up with #8 or #9 eventually, once your needs increase.

  • Excellent for prototyping, working on the go, doing tests, interactive work (e.g. making figures).

  • Mostly used for teaching

5. Interactive graphical session on UiO servers (ssh -X freebio.hpc.uio.no or on request to bioint01.hpc.uio.no)

  • Graphical programs.

  • Lost once your internet connection dies, needs fast internet connection.

  • A general workhorse once you get comfortable with shell - many people work here.

6. Interactive command line session on UiO servers (ssh login.uio.no)

  • Works from anywhere. Few resources and for a short time.

  • Limited time limits, must be used manually.

  • Mostly used to “enter” University network and gain access to other UiO services.

  • Can access your home area and ASTRA storage

7. GPU / Machine learning resources

  • Works from anywhere. Dedicated to machine learning and deep learning tasks.

  • No time limits

  • Need to request access (send a mail to itf-ai-support@usit.uio.no )

  • Priority for GPU intensive tasks

  • Infrastructure support for course in machine learning

  • More details are available on "Ml-nodes" page

8. Norwegian Research and Education Cloud

  • Fast, standardized servers and storage for the Norwegian higher education sector.

  • Get access to a self-service, modern and secure cloud infrastructure, available when you need it.

  • HPC-cloud can be requested too.

  • Small projects available to everyone by default and for larger projects by using this web form.

  • Basically you are on your own (root user) so this service is recommended to more advanced users.

9. Google Cloud Platform

  • Very similar to NREC (for advanced users)

  • Gives you access to more computing power (including HPC-cloud), analytics, machine learning products, developer tools and much more (including Speech to Text AI for automatic transcription).

  • Very versatile (more options than for NREC for processors, memories, disks including SSDs).

  • Price depends on the performance, data location, access, etc.

10. NIRD Service Platform

  • On-demand data analytics services, such as AI/ML algorithm, JupyterHub and Jupyter Notebook.

  • Cannot access UiO storage but can access NIRD project areas.

  • Require to submit an application for data storage (evaluated and granted by a resource allocation committee twice a year).

  • Minimum storage 10TB.

  • NIRD project managers need to request access to this service.

  • Require “advanced” knowledge to customize services for your needs.

11. Non-interactive batch HPC computing on Sigma2 (ssh + sbatch)

See also

IT Services for Research: Portal of available IT services and infrastructure for UiO researchers as well as useful information, guidance, and contact list.

Credit

Aalto University, Aalto Scientific Computing

By Anne Fouilloux, Sabry Razick, Naoe Tatara
Published Jan. 31, 2021 3:14 PM - Last modified Feb. 22, 2021 8:13 AM