compute_ru - compute

asdf

Anonymous (anonymous@undisclosed.example.com) — 2024-12-09T09:55:36+00:00

ASDF Simple, run git init, clone, update your environment setting, add pyhton plugin * git init * git clone ~/.asdf --branch v0.14.1 * echo “. $HOME/.asdf/asdf.sh” >> ~/.bashrc * source .bashrc * asdf plugin-add python Now just choose what version of python you need (but more than one can be installed)

begin

Anonymous (anonymous@undisclosed.example.com) — 2024-12-12T10:44:43+00:00

How-To for beginners with examples We recommend using , and this how-to is base on it, but other editors can also be used 1. Connecting with VScode * Install Visual Studio Code on you computer * Add the Remote-SSH extension * In the search box select Show and run commands [Ctrl]-[shift]-[p]

getstart

Anonymous (anonymous@undisclosed.example.com) — 2024-12-11T15:09:31+00:00

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.

gpupython

Anonymous (anonymous@undisclosed.example.com) — 2024-12-09T10:25:40+00:00

Using GPU with python Python offers some modules to communicate with a GPU Both Tensorflow and Torch have been used on this cluster succesfully. Some version of python and these modules might not work with the GPU Those version have been used before and do work

hardware

Anonymous (anonymous@undisclosed.example.com) — 2024-10-14T14:24:02+00:00

2x Cisco HX-C240-M5SXP (Hyperflex) server 4x Nvidia Tesla A100 GPU

miniconda

Anonymous (anonymous@undisclosed.example.com) — 2024-12-02T10:55:18+00:00

Miniconda Easiest is to always choose the default option, but user must enter [Yes] to agree

price

Anonymous (anonymous@undisclosed.example.com) — 2024-10-14T14:24:02+00:00

A small committee, Ragnheiður, Björn Ingi + put together a price document, in spring/early summer 2022

pythongpu

Anonymous (anonymous@undisclosed.example.com) — 2024-12-11T15:48:14+00:00

Using GPU with python Python offers some modules to communicate with a GPU Both Tensorflow and Torch have been used on this cluster succesfully. An example setup using Python venv, run these commands : python3 -m venv myTorch source myTorch/bin/activate

step2

Anonymous (anonymous@undisclosed.example.com) — 2024-10-14T14:24:02+00:00

What's next ? Home folder for students is /student/ Most users are using Python for their jobs Setup your environment, Python virtual environment/Anaconda and install in you home folder the necessary libraries for your project When you are ready to send your job to the slurm queue, adjust the slurm command script

tobegin

Anonymous (anonymous@undisclosed.example.com) — 2024-12-02T09:55:56+00:00

An How-To example for beginners. Connect to the cluster with you user and pass. To utilize the power of the cluster you to add you code (project files) onto your home directory, then run it. If you examine you home directory (use the command “ls

venvpython

Anonymous (anonymous@undisclosed.example.com) — 2024-12-02T13:26:07+00:00

Python3 virtual environments Creating your virtual environment * Python3 has a module venv which can be used to create your environment (python3 -m venv myProject) * Another way is to install virtualenv with Pip (pip install virtualenv) * Miniconda can be set up with the command

vscodessh

Anonymous (anonymous@undisclosed.example.com) — 2024-12-02T09:53:58+00:00

Connecting with VScode * Install Visual Studio Code on you computer and add the Remote-SSH extension * In VSCode, select Remote-SSH: Connect to Host... from the [Command] Palette * Connect with your user and pass, server is compute.ru.is (user & pass you received in a email) *