Performance Comparison of OpenMP, MPI, and MapReduce in Practical Problems

With problem size and complexity increasing, several parallel and distributed programming models and frameworks have been developed to efficiently handle such problems. This paper briefly reviews the parallel computing models and describes three widely recognized parallel programming frameworks: Ope...

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Vydáno v:Advances in Multimedia Ročník 2015; číslo 2015; s. 132 - 140
Hlavní autoři: Kang, Sol Ji, Lee, Keon Myung, Lee, Sang Yeon
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cairo, Egypt Hindawi Limiteds 01.01.2015
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Wiley
Témata:
Comparative analysis
Computer programming
ISSN:1687-5680, 1687-5699
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Shrnutí:With problem size and complexity increasing, several parallel and distributed programming models and frameworks have been developed to efficiently handle such problems. This paper briefly reviews the parallel computing models and describes three widely recognized parallel programming frameworks: OpenMP, MPI, and MapReduce. OpenMP is the de facto standard for parallel programming on shared memory systems. MPI is the de facto industry standard for distributed memory systems. MapReduce framework has become the de facto standard for large scale data-intensive applications. Qualitative pros and cons of each framework are known, but quantitative performance indexes help get a good picture of which framework to use for the applications. As benchmark problems to compare those frameworks, two problems are chosen: all-pairs-shortest-path problem and data join problem. This paper presents the parallel programs for the problems implemented on the three frameworks, respectively. It shows the experiment results on a cluster of computers. It also discusses which is the right tool for the jobs by analyzing the characteristics and performance of the paradigms.
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ISSN:1687-5680
1687-5699
DOI:10.1155/2015/575687