Towards optimizing energy costs of algorithms for shared memory architectures

Vijay Anand Korthikanti, Gul Agha

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

Abstract

Energy consumption by computer systems has emerged as an important concern. However, the energy consumed in executing an algorithm cannot be inferred from its performance alone: it must be modeled explicitly. This paper analyzes energy consumption of parallel algorithms executed on shared memory multicore processors. Specifically, we develop a methodology to evaluate how energy consumption of a given parallel algorithm changes as the number of cores and their frequency is varied. We use this analysis to establish the optimal number of cores to minimize the energy consumed by the execution of a parallel algorithm for a specific problem size while satisfying a given performance requirement. We study the sensitivity of our analysis to changes in parameters such as the ratio of the power consumed by a computation step versus the power consumed in accessing memory. The results show that the relation between the problem size and the optimal number of cores is relatively unaffected for a wide range of these parameters.

Original languageEnglish (US)
Title of host publicationSPAA'10 - Proceedings of the 22nd Annual Symposium on Parallelism in Algorithms and Architectures
Pages157-165
Number of pages9
DOIs
StatePublished - Jul 30 2010
Event22nd ACM Symposium on Parallelism in Algorithms and Architectures, SPAA'10 - Thira, Santorini, Greece
Duration: Jun 13 2010Jun 15 2010

Publication series

NameAnnual ACM Symposium on Parallelism in Algorithms and Architectures

Other

Other22nd ACM Symposium on Parallelism in Algorithms and Architectures, SPAA'10
Country/TerritoryGreece
CityThira, Santorini
Period6/13/106/15/10

Keywords

  • Energy
  • Parallel algorithms
  • Performance
  • Shared memory architectures

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

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