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SUMMARY:® Distributed Deep Learning in HPC: Challenges and Opportunities
DTSTART;VALUE=DATE-TIME:20231205T123000Z
DTEND;VALUE=DATE-TIME:20231205T125000Z
DTSTAMP;VALUE=DATE-TIME:20260310T190133Z
UID:indico-contribution-1920@events.chpc.ac.za
DESCRIPTION:Speakers: Albert Kahira (Julich Supercomputing Center)\nLarge-
 scale training of Deep Learning Models (DL) in High Performance Computing(
 HPC) systems has become increasingly common to achieve faster training tim
 e for larger models and datasets by alleviating memory constraints. Traini
 ng DL models in these systems cuts weeks or even months of training to mer
 e hours and facilitates faster prototyping and research in DL. Importantly
 \, training some of the larger models is only possible through these large
 -scale machines. This talk will provide participants with a foundational u
 nderstanding of the concepts and techniques involved in Deep Learning in H
 PC as well as challenges and opportunities for research in the area.\n\nht
 tps://events.chpc.ac.za/event/125/contributions/1920/
LOCATION:Skukuza 1-1-2+4 - Ndau + Nari
URL:https://events.chpc.ac.za/event/125/contributions/1920/
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