A Case Study of OpenMP applied to Map/Reduce-style Computations

Mahwish Arif, Hans Vandierendonck

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

3 Citations (Scopus)
1466 Downloads (Pure)

Abstract

As data analytics are growing in importance they are also quickly becoming one of the dominant application domains that require parallel processing. This paper investigates the applicability of OpenMP, the dominant shared-memory parallel programming model in high-performance computing, to the domain of data analytics. We contrast the performance and programmability of key data analytics benchmarks against Phoenix++, a state-of-the-art shared memory map/reduce programming system. Our study shows that OpenMP outperforms the Phoenix++ system by a large margin for several benchmarks. In other cases, however, the programming model is lacking support for this application domain.
Original languageEnglish
Title of host publicationOpenMP: Heterogenous Execution and Data Movements
Pages162-174
Volume9342
ISBN (Electronic)978-3-319-24595-9
DOIs
Publication statusPublished - Nov 2015
Event11th International Workshop on OpenMP, IWOMP 2015 - Aachen, Germany
Duration: 01 Oct 201502 Oct 2015
http://www.iwomp.org/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
ISSN (Print)0302-9743

Conference

Conference11th International Workshop on OpenMP, IWOMP 2015
CountryGermany
CityAachen
Period01/10/201502/10/2015
Internet address

Keywords

  • OpenMP
  • map/reduce
  • REDUCTION

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