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DTSTAMP:20260522T150116Z
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DTSTART;TZID=America/Chicago:20181114T143000
DTEND;TZID=America/Chicago:20181114T150000
UID:submissions.supercomputing.org_SC18_sess177_pap365@linklings.com
SUMMARY:A Lightweight Model for Right-Sizing Master-Worker Applications
DESCRIPTION:Nathaniel Kremer-Herman, Benjamin Tovar, and Douglas Thain (Un
 iversity of Notre Dame)\n\nWhen running a parallel application at scale, a
  resource provisioning policy should minimize over-commitment (idle resour
 ces) and under-commitment (resource contention). However, users seldom kno
 w the quantity of resources to appropriately execute their application. Ev
 en with such knowledge, over- and under-commitment of resources may still 
 occur because the application does not run in isolation. It shares resourc
 es  such as network and filesystems.\n\nWe formally define the capacity of
  a parallel application as the quantity of resources that may effectively 
 be provisioned for the best  execution time in an environment.  We present
  a model to compute an estimate of the capacity of master-worker applicati
 ons as they run based on execution and data-transfer times. We demonstrate
  this model with two bioinformatics workflows, a machine learning applicat
 ion, and one synthetic application.  Our results show the model correctly 
 tracks the known value of capacity in scaling,  dynamic task behavior, and
  with improvements in task throughput.\n\nTag: Clouds and Distributed Comp
 uting, Resource Management, Scheduling\n\nRegistration Category: Tech Prog
 ram Reg Pass\n\nSession Chair: Shantenu Jha (Rutgers University; PPPL, Pri
 nceton University)\n\n
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