Energy-efficient computing for HPC workloads on heterogeneous manycore chips

Akhil Langer, Ehsan Totoni, Udatta S. Palekar, Laxmikant V. Kalé

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

Abstract

Power and energy efficiency is one of the major challenges to achieve exascale computing in the next several years. While chips operating at low voltages have been studied to be highly energyefficient, low voltage operations lead to heterogeneity across cores within the microprocessor chip. In this work, we study chips with low voltage operation and discuss programming systems, and performance modeling in the presence of heterogeneity. We propose an integer linear programming based approach for selecting optimal configuration of a chip that minimizes its energy consumption. We obtain an average of 26% and 10.7% savings in energy consumption of the chip for two HPC mini-applications - miniMD and Jacobi, respectively. We also evaluate the energy savings with execution time constraints, using the proposed approach. These energy savings are significantly more than the savings by sub-optimal configurations obtained from heuristics.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2015
EditorsPavan Balaji, Minyi Guo, Zhiyi Huang
PublisherAssociation for Computing Machinery, Inc
Pages11-19
Number of pages9
ISBN (Electronic)9781450334044
DOIs
StatePublished - Feb 7 2015
Event6th International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2015 - San Francisco Bay Area, United States
Duration: Feb 7 2015Feb 8 2015

Publication series

NameProceedings of the 6th International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2015

Other

Other6th International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2015
Country/TerritoryUnited States
CitySan Francisco Bay Area
Period2/7/152/8/15

Keywords

  • Energy
  • Heterogeneity
  • Integer Programming
  • Low Voltage Computing
  • Multicore chips
  • Near Threshold Voltage Computing
  • Optimization
  • Power
  • Process Variation
  • Quadratic Integer Programming

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Software

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