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DTSTART:19700308T020000
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DTSTAMP:20260522T150110Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181114T083000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess323_post123@linklings.com
SUMMARY:Large Scale Computation of Quantiles Using MELISSA
DESCRIPTION:Alejandro Ribes (EDF Research and Development), Théophile Terr
 az (French Institute for Research in Computer Science and Automation (INRI
 A)), Yvan Fournier and Bertrand Iooss (EDF Research and Development), and 
 Bruno Raffin (French Institute for Research in Computer Science and Automa
 tion (INRIA))\n\nQuantiles being order statistics, the classical approach 
 for their computation requires availability of the full sample before rank
 ing it. This approach is not suitable at exascale. Large ensembles would n
 eed to gather a prohibitively large amount of data. We propose an iterativ
 e approach based on the stochastic quantile algorithm of Robbins-Monro. We
  rely on the Melissa framework, a file avoiding, adaptive, fault tolerant 
 and elastic framework in order to compute in transit ubiquitous quantiles.
  Quantiles are updated on-the-fly as soon as the in transit parallel serve
 r receives results from one of the running simulations. We run 80,000 flui
 d dynamics parallel simulations of 6M hexahedra and 100 timespteps. They w
 ere executed on up to 4800 cores,  avoiding 288 TB of file storage. We pro
 duce ubiquitous spatio-temporal maps of quantiles and inter-quantile based
  intervals.\n\nRegistration Category: Tech Program Reg Pass, Exhibits Reg 
 Pass\n\n
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