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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_sess326_spost114@linklings.com
SUMMARY:Studying the Impact of Power Capping on MapReduce-Based, Data-Inte
 nsive Mini-Applications on Intel KNL and KNM Architectures
DESCRIPTION:Joshua H. Davis (University of Delaware)\n\nIn this poster, we
  quantitatively measure the impacts of data movement on performance in Map
 Reduce-based applications when executed on HPC systems. We leverage the PA
 PI ‘powercap’ component to identify ideal conditions for execution of our 
 applications in terms of (1) dataset characteristics (i.e., unique words);
  (2) HPC system (i.e., KNL and KNM); and (3) implementation of the MapRedu
 ce programming model (i.e., with or without combiner optimizations). Resul
 ts confirm the high energy and runtime costs of data movement, and the ben
 efits of the combiner optimization on these costs.\n\nRegistration Categor
 y: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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