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DTSTART:19700308T020000
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DTSTAMP:20260522T150129Z
LOCATION:D161
DTSTART;TZID=America/Chicago:20181112T144000
DTEND;TZID=America/Chicago:20181112T150000
UID:submissions.supercomputing.org_SC18_sess158_ws_lasalss102@linklings.co
 m
SUMMARY:Machine Learning-Aided Numerical Linear Algebra:  Convolutional Ne
 ural Networks for the Efficient Preconditioner Generation
DESCRIPTION:Markus Götz (Karlsruhe Institute of Technology)\n\nMarkus Götz
  received his Bachelors and Masters degree in Software Engineering from th
 e University of Potsdam in 2010 and 2014 respectively. Afterwards, he has 
 been with the Research Center Jülich and the University of Iceland, from w
 hich Markus obtained his PhD degree in Computational Engineering for his w
 orks on parallel data-analysis algorithms on high-performance computing (H
 PC) systems. Since the beginning of 2018 Markus is with the Steinbuch Cent
 re for Computing (SCC) at the Karlsruhe Institute of Technology (KIT). The
 re, he manages the Helmholtz Analytics Framework project, a german-wide in
 itiative with the aim of developing the data sciences in the Helmholtz Ass
 ociation. His research topics include applied machine learning, scalable d
 ata analysis frameworks and parallel algorithms.\n\nTag: Algorithms, Heter
 ogeneous Systems, Resiliency\n\nRegistration Category: Workshop Reg Pass\n
 \nSession Chairs: Vassil Alexandrov (Hartree Centre, STFC); Jack Dongarra 
 (University of Tennessee, Knoxville; Oak Ridge National Laboratory (ORNL))
 ; Christian Engelmann (Oak Ridge National Laboratory (ORNL)); and Al Geist
  (Oak Ridge National Laboratory (ORNL))\n\n
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