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DTSTART;TZID=America/Denver:20191118T103000
DTEND;TZID=America/Denver:20191118T113000
UID:submissions.supercomputing.org_SC19_sess124_pec274@linklings.com
SUMMARY:Keynote 2: Toward Scaling Deep Learning to 100,000 Processors - Th
 e Fugaku Challenge
DESCRIPTION:Workshop\n\nKeynote 2: Toward Scaling Deep Learning to 100,000
  Processors - The Fugaku Challenge\n\nMatsuoka\n\nModern AI with deep lear
 ning poses significant overhead in training over very large data sets, whe
 reby the use of HPC techniques to compute in parallel on a large machine i
 s becoming increasingly popular. However, most of the efforts have been on
  GPUs at relatively low scale, in the order of a few hundreds, up to a tho
 usand except on fairly limited sets of cases, due to inherent difficulties
 . On Fugaku we plan on extending the capabilities of deep learning by allo
 wing training to be done on the full machine, or more than 100,000 nodes. 
 This requires various technological underpinnings as well as new algorithm
 s for scalable training, the ongoing effort whose curent state will be des
 cribed.\n\nTag: Workshop Reg Pass, Algorithms, Scalable Computing\n\nRegis
 tration Category: Workshop Reg Pass, Algorithms, Scalable Computing
URL:https://sc19.supercomputing.org/presentation/?id=pec274&sess=sess124
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