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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| Veröffentlicht in: | Advances in Multimedia Jg. 2015; H. 2015; S. 132 - 140 |
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Cairo, Egypt
Hindawi Limiteds
01.01.2015
Hindawi Publishing Corporation John Wiley & Sons, Inc Wiley |
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| Abstract | 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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| AbstractList | 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. 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 frameworkhas 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. |
| Audience | Academic |
| Author | Lee, Sang Yeon Lee, Keon Myung Kang, Sol Ji |
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| Cites_doi | 10.1145/1365490.1365500 10.1145/1272998.1273005 10.1007/11892960_49 10.1145/1327452.1327492 10.1109/3477.552189 10.1109/TPDS.2011.308 10.1016/j.parco.2011.02.004 10.1109/MC.2003.1236476 |
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| Copyright | Copyright © 2015 Sol Ji Kang et al. COPYRIGHT 2015 John Wiley & Sons, Inc. Copyright © 2015 Sol Ji Kang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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| References | OpenMP Architecture Review Board OpenMP Application Program Interface 2008, http://www.openmp.org/mp-documents/spec30.pdf Resch M. Sander B. Loebich I. A comparison of OpenMP and MPI for the parallel CFD test case Proceedings of the 1st European Workshop on OpenMP 1999 71 75 Alexandrov A. Ewen S. Heimel M. MapReduce and PACT—comparing data parallel programming models Proceedings of the 14th Conference on Database Systems for Business, Technology, and Web (BTW '11) 2011 25 44 Sodan A. C. Message-passing and shared-data programming models—wish vs. reality Proceedings of the 19th International Symposium on High Performance Computing Systems and Applications (HPCS '05) May 2005 131 139 10.1109/HPCS.2005.34 2-s2.0-28744435996 (11) 2008; 51 Culler D. E. Singh J. P. Gupta A. Parallel Computer Architecture: A Hardware/software Approach 1999 Gulf Professional Coarfa C. Dotsenko Y. Mellor-Crummey J. Cantonnet F. Ei-Ghazawi T. Mohanti A. Yao Y. Chavarría-Miranda D. An evaluation of global address space languages: co-array fortran and Unified Parallel C Proceedings of the 10th ACM SIGPLAN Symposium on Principles and Practise of Parallel Programming June 2005 36 47 10.1145/1065944.1065950 2-s2.0-31844441256 Lee S. W. Kim J. T. Sohn B. K. Lee K. M. Jeon J. W. Lee S. Real-Time System-on-a-Chip Architecture for Rule-Based Context-Aware Computing 2005 3681 Lecture Notes in Computer Science Ghemawat S. Gobioff H. Leung S.-T. The google file system Proceedings of the 19th ACM Symposium on Operating Systems Principles (SOSP '03) October 2003 29 43 2-s2.0-21644437974 10.1145/945445.945450 (15) 2003; 36 Lee K. M. Lee K. M. Similar pair identification using locality-sensitive hashing technique Proceedings of 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems (SCIS/ISIS '12) 2012 2117 2119 (17) 2007; 41 Gropp W. Huss-Lederman S. Lumsdaine A. Lusk E. Nitzberg B. Saphir W. Snir M. MPI: The Complete Reference, the MPI-2 Extensions 1998 2 The MIT Press Jost G. Jin H. Mey D. Hatay F. Comparing the OpenMP, MPI, and hybrid programming paradigm on an SMP cluster Proceedings of the 5th European workshop on OpenMP (EWOMP '03) 2003 Ravela S. C. Comparison of shared memory based parallel programming models 2010 MSC-2010-01 Blekinge Institute of Technology Barney B. Introduction to Parallel Computing 2007 Lawrence Livermore National Laboratory https://computing.llnl.gov/tutorials/parallel_comp (21) 2011; 37 (5) 2006; 4251 (24) 2008; 6 (4) 1997; 27 Ranger C. Raghuraman R. Penmetsa A. Bradski G. Kozyrakis C. Evaluating MapReduce for multi-core and multiprocessor systems Proceedings of the 13th IEEE International Symposium on High Performance Computer Architecture (HPCA '07) February 2007 Scottsdale, Ariz, USA 13 24 2-s2.0-34547679939 10.1109/HPCA.2007.346181 Cormen T. H. Leiserson C. E. Rivest R. L. Stein C. Introduction to Algorithms 2009 MIT Press MR2572804 POSIX-IEEE Standards Association 2014, http://standards.ieee.org/develop/wg/POSIX.html (7) 2012; 23 (12) 2007; 41 13 24 (5) 2007 (8) 1998; 2 19 (23) 2005; 3681 4 (21) 2006; 4251 (1) 1999 20 (17) 2009 10 |
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Message-passing and shared-data programming models—wish vs. reality Proceedings of the 19th International Symposium on High Performance Computing Systems and Applications (HPCS '05) May 2005 131 139 10.1109/HPCS.2005.34 2-s2.0-28744435996 – reference: POSIX-IEEE Standards Association 2014, http://standards.ieee.org/develop/wg/POSIX.html – volume: 37 start-page: 610 issue: 9 year: 2011 end-page: 632 ident: 21 article-title: MapReduce in MPI for large-scale graph algorithms – reference: Lee K. M. Lee K. M. Similar pair identification using locality-sensitive hashing technique Proceedings of 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems (SCIS/ISIS '12) 2012 2117 2119 – volume: 51 start-page: 107 issue: 1 year: 2008 end-page: 113 ident: 11 article-title: MapReduce: simplified data processing on large clusters – reference: Cormen T. H. Leiserson C. E. Rivest R. L. Stein C. Introduction to Algorithms 2009 MIT Press MR2572804 – reference: Gropp W. Huss-Lederman S. Lumsdaine A. Lusk E. Nitzberg B. Saphir W. Snir M. MPI: The Complete Reference, the MPI-2 Extensions 1998 2 The MIT Press – reference: Alexandrov A. Ewen S. Heimel M. MapReduce and PACT—comparing data parallel programming models Proceedings of the 14th Conference on Database Systems for Business, Technology, and Web (BTW '11) 2011 25 44 – reference: Ghemawat S. Gobioff H. Leung S.-T. The google file system Proceedings of the 19th ACM Symposium on Operating Systems Principles (SOSP '03) October 2003 29 43 2-s2.0-21644437974 10.1145/945445.945450 – volume: 27 start-page: 105 issue: 1 year: 1997 end-page: 108 ident: 4 article-title: Hierarchical partition of nonstructured concurrent systems – reference: Ranger C. Raghuraman R. Penmetsa A. Bradski G. Kozyrakis C. 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Mohanti A. Yao Y. Chavarría-Miranda D. An evaluation of global address space languages: co-array fortran and Unified Parallel C Proceedings of the 10th ACM SIGPLAN Symposium on Principles and Practise of Parallel Programming June 2005 36 47 10.1145/1065944.1065950 2-s2.0-31844441256 – volume: 41 start-page: 59 issue: 3 year: 2007 end-page: 72 ident: 17 article-title: Dryad: distributed data-parallel programs from sequential building blocks – reference: OpenMP Architecture Review Board OpenMP Application Program Interface 2008, http://www.openmp.org/mp-documents/spec30.pdf – volume: 4251 start-page: 401 year: 2006 end-page: 408 ident: 5 article-title: Architecture of RETE network hardware accelerator for real-time context-aware system – ident: 24 doi: 10.1145/1365490.1365500 – volume: 41 start-page: 59 issue: 3 year: 2007 ident: 12 publication-title: ACM SIGOPS Operating Systems Review doi: 10.1145/1272998.1273005 – volume: 3681 year: 2005 ident: 23 – year: 2007 ident: 5 – volume: 4251 start-page: 401 year: 2006 ident: 21 publication-title: Lecture Notes in Computer Science doi: 10.1007/11892960_49 – volume: 2 year: 1998 ident: 8 – ident: 13 doi: 10.1145/1327452.1327492 – year: 1999 ident: 1 – year: 2009 ident: 17 – ident: 19 doi: 10.1109/3477.552189 – ident: 4 doi: 10.1109/TPDS.2011.308 – ident: 20 doi: 10.1016/j.parco.2011.02.004 – ident: 10 doi: 10.1109/MC.2003.1236476 |
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| Title | Performance Comparison of OpenMP, MPI, and MapReduce in Practical Problems |
| URI | https://www.airitilibrary.com/Article/Detail/P20150716004-201512-201709250027-201709250027-132-140 https://search.emarefa.net/detail/BIM-1052643 https://dx.doi.org/10.1155/2015/575687 https://www.proquest.com/docview/1704316921 https://doaj.org/article/2f6102cae4874ea7b76b5031b7c44e61 |
| Volume | 2015 |
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