Simulating power scheduling at scale

Daniel Ellsworth, Tapasya Patki, Martin Schulz, Barry Rountree, Allen Malony

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Comparison of power scheduling strategies at scale is challenging due to the limited availability of high performance computing (HPC) systems exposing power control to researchers. In this paper we describe PowSim, a simulator for comparing different power management strategies at large-scale for HPC systems. PowSim enables light-weight simulation of dynamically-changing hardware-enforced processor power caps at the scale of an HPC cluster, supporting power scheduling research. PowSim’s architecture supports easily changing power scheduler, job scheduler, and application models to enable comparison studies. Preliminary results comparing generalized power scheduling strategies are also presented.

Original languageEnglish
Title of host publicationProceedings of E2SC 2017
Subtitle of host publication5th International Workshop on Energy Efficient Supercomputing - Held in conjunction with SC 2017: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherAssociation for Computing Machinery, Inc
ISBN (Print)9781450351324
DOIs
StatePublished - 12 Nov 2017
Externally publishedYes
Event5th International Workshop on Energy Efficient Supercomputing, E2SC 2017 - Held in conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2017 - Denver, United States
Duration: 12 Nov 201717 Nov 2017

Publication series

NameProceedings of E2SC 2017: 5th International Workshop on Energy Efficient Supercomputing - Held in conjunction with SC 2017: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference5th International Workshop on Energy Efficient Supercomputing, E2SC 2017 - Held in conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2017
Country/TerritoryUnited States
CityDenver
Period12/11/1717/11/17

Keywords

  • Power capping
  • Power scheduling
  • Simulation

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