ML nodes

University IT department provides resources and services for machine learning and deep learning tasks at UiO. This page describes the available resources on the so-called ML-nodes, how to get access to them, how to use them and how to get support in using them.

Note that there is no batch system, i.e you can not run jobs that span over two machines (like on a typical HPC system). There is therefore no queue system, so use the machines in a solidaric way!

 

Alternatives:

For machine-learning there is also  Fox in Educloud. Fox has a job submission queueing  system and has a somewhat more streamlined setup, in addition to interactive nodes similar to the ML-nodes.

Looking for some other computing service? This page may help you.

 

 
Table of Contents

Available hardware resources

Name Status

CPUs/

RAM(GiB)

 GPU Shared home area OS and software Comments

ml1.hpc.uio.no

ml2.hpc.uio.no

ml3.hpc.uio.no

 Production 28 cores (Intel Xeon)/128 4 X RTX2080Ti Yes RHEL 8.7 with module system

on ML1 on 3 GPUs functional

 

ml4.hpc.uio.no

 Production 32 cores (AMD)/128 2 X AMD Vega 10 XL/XT Yes RHEL 8.7 with module system

 

 
ml6.hpc.uio.no Reserved for a course 32 cores (AMD)/256 8 X RTX2080Ti Yes RHEL 8.7 with module system

 

ml7.hpc.uio.no

 Production 32 cores (AMD)/256 8 X RTX2080Ti Yes RHEL 8.7 with module system

 
ml8.hpc.uio.no Production 2x 48 core (AMD)/1024 4 X Nvidia-A-100 Yes RHEL 8.7 with module system Will be moved to Fox
ml9.hpc.uio.no Production 2x 48 core (AMD)/1024 4 X NVIDIA GeForce RTX 3090 Yes RHEL 8.7 with module system

reserved for INF5310 course
09-10-2024 to 19-11-2024

How to get access

Apply for access at the following nettskjema.

How to login

The ml nodes are behind a jump host as a security measure. Which means that you need to be logged in to a UiO computer before you SSH to a ML node. You can achieve this in two ways.

  1. Login to a computer inside UiO network (login.uio.no)
  2. Login to the ml nodes from that computer

 UIO-USER-NAME is your user name at University of Oslo

{MYUSER@laptop:~] $ ssh UIO-USER-NAME@login.uio.no

[UIO-USER-NAME@gothmog ~]$ ssh ml1.hpc.uio.no

You could combine the above two steps using the following command

 ssh -J UIO-USER-NAME@login.uio.no  UIO-USER-NAME@ml1.hpc.uio.no

 

Login problems.

If you could not login to ML nodes, this could mean many things. So if you send us a mail asking for help with only "I can not login, it is difficult to provide a solution. Please go through the list and see what information you should gather.

  1. "The authenticity of host '....uio.no (129.240...)' can't be established. This can happen when we change the server key or you are login in for the first time . The solution is to get/update the key, for this refer the section "Key changed when trying to log in" below.  After you verify that you are connecting to the correct machine, you should type "yes" to accept the new key
  2. Wrong username or password. For ML nodes you should use the UiO username and password. If you get the username-password combination wrong for more than three times, then your account would be blocked for that machine for one hour.
  3. Your password is case sensitive.
  4. Jump host. Make sure that you follow the jump host instructions above.
  5. Did you type the correct host-name. Please check the correct names in the above table (Available hardware resources).
  6. When sending support requests, please include the details below.
    1.  Exact command you used to login with username used and hostname (the ML machine your are trying to login) . Never include password.
    2. Where are you login in from. Is it office ? from your laptop from home ?.  Please send the IP address of the machine if you know how to get it (if you do not know what that is do not worry)
    3. If you are login from a terminal please send the full debug info. e.g.
      1. ssh -vvv MY_USERNAME@ml1.hpc.uio.no

 

Please note that you nee