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JUWELS Booster -- A Supercomputer for Large-Scale AI Research

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arxiv 2108.11976 v1 pith:ZGL25LT7 submitted 2021-06-30 cs.DC cs.LG

JUWELS Booster -- A Supercomputer for Large-Scale AI Research

Stefan Kesselheim , Andreas Herten , Kai Krajsek , Jan Ebert , Jenia Jitsev , Mehdi Cherti , Michael Langguth , Bing Gong
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Scarlet Stadtler Amirpasha Mozaffari Gabriele Cavallaro Rocco Sedona Alexander Schug Alexandre Strube Roshni Kamath Martin G. Schultz Morris Riedel Thomas Lippert
This is my paper
classification cs.DC cs.LG
keywords researchlarge-scalesystemarchitectureboosterjuwelsapplicationapplications
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In this article, we present JUWELS Booster, a recently commissioned high-performance computing system at the J\"ulich Supercomputing Center. With its system architecture, most importantly its large number of powerful Graphics Processing Units (GPUs) and its fast interconnect via InfiniBand, it is an ideal machine for large-scale Artificial Intelligence (AI) research and applications. We detail its system architecture, parallel, distributed model training, and benchmarks indicating its outstanding performance. We exemplify its potential for research application by presenting large-scale AI research highlights from various scientific fields that require such a facility.

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