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Reseach Article

A Hybrid OpenMP-MPI Parallelization of Structure Software

by Rafal Dobosz, Richard Hurley, Sabine Mcconnell
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 118 - Number 11
Year of Publication: 2015
Authors: Rafal Dobosz, Richard Hurley, Sabine Mcconnell
10.5120/20786-3434

Rafal Dobosz, Richard Hurley, Sabine Mcconnell . A Hybrid OpenMP-MPI Parallelization of Structure Software. International Journal of Computer Applications. 118, 11 ( May 2015), 1-9. DOI=10.5120/20786-3434

@article{ 10.5120/20786-3434,
author = { Rafal Dobosz, Richard Hurley, Sabine Mcconnell },
title = { A Hybrid OpenMP-MPI Parallelization of Structure Software },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 118 },
number = { 11 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume118/number11/20786-3434/ },
doi = { 10.5120/20786-3434 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:01:22.676998+05:30
%A Rafal Dobosz
%A Richard Hurley
%A Sabine Mcconnell
%T A Hybrid OpenMP-MPI Parallelization of Structure Software
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 11
%P 1-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Big Data has an increasing impact on the use of bioinformatics software. One way to deal with this challenge is through parallel computing. Using the program Structure as a case study, this paper investigates ways in which to counteract the challenges created by the growing datasets. This paper proposes an OpenMP-MPI hybrid parallelization of the MCMC steps, which are an integral part of Structure, and analyses the performance under various scenarios. The results indicate that the parallelization produce significant speedups over the serial version in all scenarios tested. This allows for the use of the hardware in a more efficient manner, by adapting the program to the parallel architecture. This is important because not only does it reduce the time required to perform existing analyses, but also opens the door to the analysis of previously impractically large datasets.

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Index Terms

Computer Science
Information Sciences

Keywords

MPI OpenMP parallelization Structure MCMC SPRNG SHARCNET speedup Big Data High Performance Computing