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BEGIN:VEVENT
DTSTAMP:20210402T160550Z
LOCATION:Track 6
DTSTART;TZID=America/New_York:20201110T143000
DTEND;TZID=America/New_York:20201110T183000
UID:submissions.supercomputing.org_SC20_sess269_tut106@linklings.com
SUMMARY:Deep Learning at Scale
DESCRIPTION:Tutorial\n\nDeep Learning at Scale\n\nBhimji, Farrell, Mustafa
 , Ringenburg, Kurth...\n\nDeep learning is rapidly and fundamentally trans
 forming the way science and industry use data to solve problems. Deep neur
 al network models have been shown to be powerful tools for extracting insi
 ghts from data across a large number of domains. As these models grow in c
 omplexity to solve increasingly challenging problems with larger and large
 r datasets, the need for scalable methods and software to train them grows
  accordingly.\n\nThe Deep Learning at Scale tutorial aims to provide atten
 dees with a working knowledge on deep learning on HPC class systems, inclu
 ding performance optimization, techniques for scaling and scientific appli
 cations. We will not cover deep learning basics in detail but will provide
  introductory resources. We will give demos and provide code examples with
  datasets to show attendees how to effectively utilize HPC systems for opt
 imized, scalable distributed training and hyperparameter optimization.\n\n
 Tag: Big Data, Machine Learning, Deep Learning and Artificial Intelligence
 , Scalable Computing\n\nRegistration Category: Tutorial Reg Pass
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