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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20181221T160911Z
LOCATION:C144
DTSTART;TZID=America/Chicago:20181112T083000
DTEND;TZID=America/Chicago:20181112T170000
UID:submissions.supercomputing.org_SC18_sess259_tut177@linklings.com
SUMMARY:Deep Learning at Scale
DESCRIPTION:Tutorial\nDeep Learning, Machine Learning, Tools, Tutorial Reg
  Pass\n\nDeep Learning at Scale\n\nFarrell, Bard, Ringenburg, Kurth, Prabh
 at\n\nDeep learning is rapidly and fundamentally transforming the way scie
 nce and industry use data to solve problems. Deep neural network models ha
 ve been shown to be powerful tools for extracting insights from data acros
 s a large number of domains. As these models grow in complexity to solve i
 ncreasingly challenging problems with larger and larger datasets, the need
  for scalable methods and software to train them grows accordingly.\n\nThe
  Deep Learning at Scale tutorial aims to provide attendees with a working 
 knowledge of deep learning on HPC class systems, including core concepts, 
 scientific applications, and techniques for scaling.  We will provide trai
 ning accounts and example Jupyter notebook-based exercises, as well as dat
 asets, to allow attendees to experiment hands-on with training, inference,
  and scaling of deep neural network machine learning models.
URL:https://sc18.supercomputing.org/presentation/?id=tut177&sess=sess259
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