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PRODID:Linklings LLC
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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20210402T160549Z
LOCATION:Track 7
DTSTART;TZID=America/New_York:20201109T143000
DTEND;TZID=America/New_York:20201109T183000
UID:submissions.supercomputing.org_SC20_sess255_tut138@linklings.com
SUMMARY:Tools and Best Practices for Distributed Deep Learning on Supercom
 puter
DESCRIPTION:Tutorial\n\nTools and Best Practices for Distributed Deep Lear
 ning on Supercomputer\n\nXu, Zhang, Walling\n\nThis tutorial is a practica
 l guide on how to effectively run distributed deep learning over multiple 
 compute nodes. Domain scientists are embracing DL as both a standalone dat
 a science method and an effective approach to reducing dimensionality in t
 he traditional simulation. We have seen the fusion of DL and high-performa
 nce computing (HPC): supercomputers show an unparalleled capacity to reduc
 e DL training time; HPC techniques have been used to speed up parallel DL 
 training. Distributed deep learning has great potential to augment DL appl
 ications by leveraging existing high-performance computing clusters.  In t
 his tutorial, we will give an overview of the state-of-art approaches to e
 nabling deep learning at scale followed by an interactive hands-on session
  to help attendees running distributed deep learning on Frontera at the Te
 xas Advanced Computing Center.  Lastly, we will discuss best practices on 
 how to scale, evaluate and tune performance.\n\nTag: Best Practices, Big D
 ata, Machine Learning, Deep Learning and Artificial Intelligence\n\nRegist
 ration Category: Tutorial Reg Pass
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