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TZID:America/Chicago
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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260522T150119Z
LOCATION:C155/156
DTSTART;TZID=America/Chicago:20181114T171500
DTEND;TZID=America/Chicago:20181114T184500
UID:submissions.supercomputing.org_SC18_sess451_bof218@linklings.com
SUMMARY:Exascale Machine Learning
DESCRIPTION:Naoya Maruyama and Brian Van Essen (Lawrence Livermore Nationa
 l Laboratory) and Satoshi Matsuoka (RIKEN, Tokyo Institute of Technology)\
 n\nHPC has been making a profound impact in recent success of data-driven 
 machine learning. Training deep learning models such as convolutional and 
 recurrent neural networks with big data is an extremely compute intensive 
 task that routinely benefits from parallel and distributed processing. Upc
 oming exascale machines are expected to further accelerate the advance of 
 data-oriented machine learning. This BoF starts with short talks by expert
 s from academia, national labs and industry about the current state of the
  art in HPC-based machine learning, and concludes with a panel session tha
 t provides a forum to discuss opportunities and challenges with future exa
 scale systems.\n\nTag: Machine Learning\n\nRegistration Category: Tech Pro
 gram Reg Pass, Exhibits Reg Pass, Exhibits - Exhibit Hall Only Reg Pass\n\
 n
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