Lecture (Other)

FZJ-2025-01610

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Bringing Deep Learning Workloads to JSC supercomputers

Strube, A. (Corresponding author)FZJ*

2024

Abstract: This course will take place as an online event. The link to the online platform will be provided to the accepted registrants only.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.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)
2. Helmholtz AI Consultant Team FB Information (E54.303.11) (E54.303.11)

Appears in the scientific report 2024

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