Using Performance-Power Modeling to Improve Energy Efficiency of HPC Applications.

Energy-efficient scientific applications require insight into how high-performance computing system features impact the applications' power and performance. This insight results from the development of performance and power models. When used with an earthquake simulation and an aerospace application...

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Bibliographic Details
Published in:Computer (00189162) Vol. 49; no. 10; pp. 20 - 30
Main Authors: Wu, Xingfu, Taylor, Valerie, Cook, Jeanine, Mucci, Philip J.
Format: Article
Published: IEEE Oct2016
Subjects:
Online Access:View this record in EBSCOhost
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        10.1109/MC.2016.311
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        atl: Using Performance-Power Modeling to Improve Energy Efficiency of HPC Applications.
      aug:
        au:
          Wu, Xingfu
          Taylor, Valerie
          Cook, Jeanine
          Mucci, Philip J.
        affil:
          Texas A&M University
          Sandia National Laboratories
          Minimal Metrics, LLC
      su:
        Computer systems
        Computer performance
        Computer simulation
        Aerospace computing
        Energy consumption
      sug:
        subj:
          Computer systems
          Computer performance
          Computer simulation
          Aerospace computing
          Energy consumption
      keyword:
        Computational modeling
        Energy efficiency
        Energy management
        energy optimization
        energy-efficient computing
        high-performance computing
        HPC systems
        Mathematical model
        performance counters
        Performance evaluation
        performance modeling
        Power demand
        power modeling
        Power system modeling
        Radiation detectors
        Runtime
      ab: Energy-efficient scientific applications require insight into how high-performance computing system features impact the applications' power and performance. This insight results from the development of performance and power models. When used with an earthquake simulation and an aerospace application, a proposed modeling framework reduces energy consumption by up to 48.65 percent and 30.67 percent, respectively.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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