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DTSTAMP:20210402T160550Z
LOCATION:Poster Module
DTSTART;TZID=America/New_York:20201119T083000
DTEND;TZID=America/New_York:20201119T170000
UID:submissions.supercomputing.org_SC20_sess341_spostg111@linklings.com
SUMMARY:Optimizing Performance in Power Bounded GPU Computing
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nOptimizing Perform
 ance in Power Bounded GPU Computing\n\nAllen\n\nPower is consistently cons
 idered as a top challenge in HPC. To address the power challenge, power ef
 ficient GPU accelerators have become a standard component in mainstream sy
 stems and contribute the majority of compute capacity. Nevertheless, GPUs 
 are still constrained by limited permissible power and required to sustain
  performance growth. In many situations, there is a need to set a power ca
 p on GPUs. In our research we find the default hardware power capping on G
 PUs loses performance by up to 35%, in comparison to the maximum achievabl
 e performance. We demonstrate that performance can be improved by a large 
 margin for the applications studied, compared to the default power capping
  and allocation.\n\nTag: Student Program\n\nRegistration Category: Tech Pr
 ogram Reg Pass, Exhibits Reg Pass
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