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Scalable hybrid implementation of graph coloring using MPI and OpenMP

  • Ohio State University

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

11 Scopus citations

Abstract

Graph coloring algorithms are commonly used in large scientific parallel computing either for identifying parallelism or as a tool to reduce computation, such as compressing Hessian matrices. Large scientific computations are nowadays either run on commodity clusters or on large computing platforms. In both cases, the current target platform is hierarchical with distributed memory at the node level and shared memory at the processor level. In this paper, we present a novel hybrid graph coloring algorithm and discuss how to obtain the best performance on such systems from algorithmic, system and engineering perspectives.

Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012
Pages1744-1753
Number of pages10
DOIs
StatePublished - 2012
Event2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012 - Shanghai, China
Duration: May 21 2012May 25 2012

Publication series

NameProceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012

Conference

Conference2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012
Country/TerritoryChina
CityShanghai
Period05/21/1205/25/12

Keywords

  • Distributed Memory
  • Graph algorithm
  • Graph coloring
  • Hybrid programming
  • Shared Memory

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