Bounding energy consumption in large-scale MPI programs

Barry Rountree, David K. Lowenthal, Shelby Funk, Vincent W. Freeh, Bronis R. De Supinski, Martin Schulz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

109 Scopus citations

Abstract

Power is now a first-order design constraint in large-scale parallel computing. Used carefully, dynamic voltage scaling can execute parts of a program at a slower CPU speed to achieve energy savings with a relatively small (possibly zero) time delay. However, the problem of when to change frequencies in order to optimize energy savings is NP-complete, which has led to many heuristic energy-saving algorithms. To determine how closely these algorithms approach optimal savings, we developed a system that determines a bound on the energy savings for an application. Our system uses a linear programming solver that takes as inputs the application communication trace and the cluster power characteristics and then outputs a schedule that realizes this bound. We apply our system to three scientific programs, two of which exhibit load imbalance - particle simulation and UMT2K. Results from our bounding technique show particle simulation is more amenable to energy savings than UMT2K. (c) 2007 ACM.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 ACM/IEEE Conference on Supercomputing, SC'07
DOIs
StatePublished - Dec 1 2007
Externally publishedYes
Event2007 ACM/IEEE Conference on Supercomputing, SC'07 - Reno, NV, United States
Duration: Nov 10 2007Nov 16 2007

Publication series

NameProceedings of the 2007 ACM/IEEE Conference on Supercomputing, SC'07

Other

Other2007 ACM/IEEE Conference on Supercomputing, SC'07
CountryUnited States
CityReno, NV
Period11/10/0711/16/07

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Electrical and Electronic Engineering

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