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VERSION:2.0
PRODID:Linklings LLC
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TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
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TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20191206T142522Z
LOCATION:Panorama 2
DTSTART;TZID=Europe/Stockholm:20180627T110000
DTEND;TZID=Europe/Stockholm:20180627T123000
UID:isc_hpc_ISC High Performance 2018_sess179@linklings.com
SUMMARY:IO and Storage for Large Scale Machine Learning
DESCRIPTION:Machine Learning Day\n\nRethinking Oil & Gas workflows with Ma
 chine Learning\n\nAraya-Polo\n\nWe will review our experiences when applyi
 ng deep learning techniques to a set of challenging problems at Shell, our
  novel approach to fault detection and velocity model building has open a 
 completely new way of detecting patterns in un-process seismic data. Also,
  another ground-breaking application...\n\n---------------------\nHPC-DA: 
 An Architecture on the Intersection between Flexibility and Maximum I/O Pe
 rformance\n\nKluge\n\nIn 2016 the ZIH of TU Dresden presented an innovativ
 e approach to the Deutsche Forschungsgemeinschaft (German Research Foundat
 ion) to build an HPC machine that is targeted at the technological interse
 ction of Big Data, Machine Learning and HPC. The system has been funded an
 d is currently under const...\n\n---------------------\nExploiting NVM for
  High-Performance I/O on POWER Architectures\n\nPleiter\n\nCognitive compu
 ting applications (including Deep Learning applications) increasingly ofte
 n face the challenge of being limited by system capabilities to provide fa
 st and fine-grained access to large-scale data sets. Storage devices based
  on non-volatile memory technologies do provide the necessary p...\n\n\nPa
 sses: Conference Pass, AI/Machine Learning/Deep Learning\n\nTag: Conferenc
 e Pass, AI/Machine Learning/Deep Learning
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