Bringing Deep Learning Workloads to JSC supercomputers

[surak]

Bringing Deep Learning Workloads to JSC supercomputers

Responsible person(s)

Sabrina Benassou (JSC - Helmholtz AI Jülich), Alexandre Strube (JSC - Helmholtz AI Jülich)

Format

Tutorial

Timeframe

Can be any - we have material for both

Description

Fancy using High Performance Computing machines for AI? Fancy learning how to run your code one of Europe's fastest computers JUWELS Booster at FZJ?

In this workshop, we will guide you through the first steps of using the supercomputer machines for your own AI application. This workshop should be tailored to your needs - and our team will guide you through questions like:

How do I get access to the machines?
How do I use the pre-installed, optimized software?
How can I run my own code?
How can I store data so I can access it fast in training?
How can parallelize my training and use more than one GPU?
In this workshop, we will try to get your code and your workflow running and would like to make the start on a supercomputer as smooth as possible. After this course, you are not only ready to use not only HAICORE but you have made your first step into unlocking compute resources even on the largest scale with a compute time application at the Gauss Supercomputing Center.

This workshop will be held in a small group size with enough space to address your questions. Please give us an indication on what topics you are interested in and we will try to adjust.

Requirements

• Teaching room
• Each student brings their laptop.
• Eduroam
• VSCode/VSCodium/WSL (on windows)
• Preferably, some ML code to try on the supercomputer