Table of Contents
Getting started with the School of Technology computing cluster
The cluster compute.ru.is is a linux environment, connect with SSH
The easy way to connect and do your work the cluster is with an editor on your local computer, for example 
Visual Studio Code, but other editors can be used, if they can make a SSH connection to a remote host.
To setup and connect to the cluster with Visual Studio Code using SSH extension, see how to.
Terminal connection :
Open a terminal to log-in ssh user@compute.ru.is
In Windows you can for example use Putty or Powershell 
to connect
In Mac
or Linux
search for terminal
About the user environment :
Each user has his home folder, for student the path is [/student/<username>]
Staff members and researchers are on a different filesystem [/home/<username>]
- The first step for users is to make sure their working environment fits their needs, might have to be reconfigure.
User can install different version of Python and all necessary modules for their work.
For those who are using Python, we recommend, for ease of use, using a Python virtual environment
More detailed instruction and tips for beginners.
- Each user directory has a few files an readMe.lst file and template (slurm) script file (myJob.sh)
Every user needs to use a script file for instructing the cluster what to do
- The cluster gives users access to memory, cpu and GPU. Slurm is used as workload manager/scheduler system
To execute your job on the cluster, first update myJob.sh to run your code (or make a copy)
Then submit your job to the queue with command sbatch myJob.sh - Please refrain from running heavy interactive jobs on the login node.
The template script file looks like this
#!/bin/bash
#SBATCH --account=student
#SBATCH --job-name=MyJob
#SBATCH --gpus-per-node=1
#SBATCH --mem-per-cpu=2G
#SBATCH --partition=basic
#SBATCH --output=myBatch.log
This example file is in each user's home folder, to view the content use the command cat myJob.sh
Useful commands
| cmd | Descr |
|---|---|
| squeue | Show all jobs on the queue |
| sinfo | Information about the cluster |
| sbatch <job.sh> | Submit job |
| sacct | My jobs |
| srun | Run job interactively |
| scancel <id> | kill job with <id> |
Prefered practices :
- What are the steps you job needs, does one part have to finish before another can run etc
- An estimate of the how many tasks
- what resource each task needs (CPU, memory, GPU)
- Does every step require the same resources
- An estimate of how long the will run
To request access
send email to (help@ru.is) with your full name
Additional information
Slurm
Visual Studio Code can also be used through SSH
Use this email help@ru.is for access requests, inquiries etc.
Using GPU with python