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DTSTAMP:20181221T160903Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181115T083000
DTEND;TZID=America/Chicago:20181115T170000
UID:submissions.supercomputing.org_SC18_sess324_post123@linklings.com
SUMMARY:Large Scale Computation of Quantiles Using MELISSA
DESCRIPTION:Poster\nTech Program Reg Pass, Exhibits Reg Pass\n\nLarge Scal
 e Computation of Quantiles Using MELISSA\n\nRibes, Terraz, Fournier, Iooss
 , Raffin\n\nQuantiles being order statistics, the classical approach for t
 heir computation requires availability of the full sample before ranking i
 t. This approach is not suitable at exascale. Large ensembles would need t
 o gather a prohibitively large amount of data. We propose an iterative app
 roach based on the stochastic quantile algorithm of Robbins-Monro. We rely
  on the Melissa framework, a file avoiding, adaptive, fault tolerant and e
 lastic framework in order to compute in transit ubiquitous quantiles. Quan
 tiles are updated on-the-fly as soon as the in transit parallel server rec
 eives results from one of the running simulations. We run 80,000 fluid dyn
 amics parallel simulations of 6M hexahedra and 100 timespteps. They were e
 xecuted on up to 4800 cores,  avoiding 288 TB of file storage. We produce 
 ubiquitous spatio-temporal maps of quantiles and inter-quantile based inte
 rvals.
URL:https://sc18.supercomputing.org/presentation/?id=post123&sess=sess324
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