Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster

Robert Springer, David K. Lowenthal, Barry Rountree, Vincent W. Freeh

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

65 Scopus citations

Abstract

Recently, the high-performance computing community has realized that power is a performance-limiting factor. One reason for this is that supercomputing centers have limited power capacity and machines are starting to hit that limit. In addition, the cost of energy has become increasingly significant, and the heat produced by higher-energy components tends to reduce their reliability. One way to reduce power (and therefore energy) requirements is to use high-performance cluster nodes that are frequency- and voltage-scalable (e.g., AMD-64 processors). The problem we address in this paper is: given a target program, a power-scalable cluster, and an upper limit for energy consumption, choose a schedule (number of nodes and CPU frequency) that simultaneously (1) satisfies an external upper limit for energy consumption and (2) minimizes execution time. There are too many schedules for an exhaustive search. Therefore, we find a schedule through a novel combination of performance modeling, performance prediction, and program execution. Using our technique, we are able to find a near-optimal schedule for all of our benchmarks in just a handful of partial program executions.

Original languageEnglish (US)
Title of host publicationProceedings of the 2006 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP'06
Pages230-238
Number of pages9
StatePublished - Nov 21 2006
Externally publishedYes
Event2006 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP'06 - New York, NY, United States
Duration: Mar 29 2006Mar 31 2006

Publication series

NameProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP
Volume2006

Other

Other2006 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP'06
CountryUnited States
CityNew York, NY
Period3/29/063/31/06

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Keywords

  • Energy
  • MPI
  • Modeling
  • Power
  • Prediction

ASJC Scopus subject areas

  • Software

Cite this

Springer, R., Lowenthal, D. K., Rountree, B., & Freeh, V. W. (2006). Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster. In Proceedings of the 2006 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP'06 (pp. 230-238). (Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP; Vol. 2006).