Energy Prediction of OpenMP Applications Using Random Forest Modeling Approach

Shajulin Benedict, R. S. Rejitha, Philipp Gschwandtner, Radu Prodan, Thomas Fahringer

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

20 Scopus citations

Abstract

OpenMP, with its extended parallelism features and support for radically changing HPC architectures, spurred to a surge in developing parallel applications among the HPC application developers community, leading to severe energy consumption issues. Consequently, a notion of addressing the energy consumption issue of HPC applications in an automated fashion increased among compiler developers although the underlying optimization search space could increase tremendously. This paper proposes a Random Forest Modeling (RFM) approach for predicting the energy consumption of OpenMP applications in compilers. The approach was tested using OpenMP applications, such as, NAS benchmarks, matrix multiplication, n-body simulations, and stencil applications while tuning the applications based on energy, problem size, and other performance concerns. The proposed RFM approach predicted the energy consumption of code variants with less than 0.699 Mean Square Error (MSE) and 0.998 R2 value when the testing dataset had energy variations between 0.024 joules and 150.23 joules. In addition, the influences of energy variations, number of independent variables used, and the proportion of testing dataset used during the RFM modeling process are discussed.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1251-1260
Number of pages10
ISBN (Electronic)0769555101, 9780769555102
DOIs
StatePublished - 29 Sep 2015
Externally publishedYes
Event29th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015 - Hyderabad, India
Duration: 25 May 201529 May 2015

Publication series

NameProceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015

Conference

Conference29th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015
Country/TerritoryIndia
CityHyderabad
Period25/05/1529/05/15

Keywords

  • Energy Prediction
  • HPC
  • Modeling
  • OpenMP
  • Scientific Applications

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