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LOCATION:Track 8
DTSTART;TZID=America/New_York:20201118T150000
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UID:submissions.supercomputing.org_SC20_sess355_spostg103@linklings.com
SUMMARY:Optimizing Vector Particle-In-Cell (VPIC) for Memory Constrained S
 ystems Using Half-Precision
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster\n\nOptimizing Vector Particle-
 In-Cell (VPIC) for Memory Constrained Systems Using Half-Precision\n\nTan\
 n\nVector Particle-In-Cell (VPIC) is one of the fastest plasma simulation 
 codes in the world, with particle numbers ranging from one trillion on the
  first petascale system, Roadrunner, to more recent 10 trillion particles 
 on the Trinity supercomputer. Current memory systems limit VPIC simulation
 s greatly as the maximum number of particles that can be simulated directl
 y depends on the available memory. In this work we present a suite of VPIC
  optimizations (i.e., particle weight storage and half-precision position 
 storage optimizations) that enable significant increases to the number of 
 particles. We assess the optimizations' impact on a GPU-accelerated Power9
  system. We show how our optimizations enable a 40% increase in the number
  of particles simulated in VPIC.\n\nTag: Student Program\n\nRegistration C
 ategory: Tech Program Reg Pass
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