Literature Survey for the Comparative Study of Various High Performance Computing Techniques
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2015 by IJCTT Journal | ||
| Volume-27 Number-2 |
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| Year of Publication : 2015 | ||
| Authors : Zahid Ansari, Asif Afzal, Moomin Muhiuddeen, Sudarshan Nayak | ||
| DOI : 10.14445/22312803/IJCTT-V27P114 |
Zahid Ansari, Asif Afzal, Moomin Muhiuddeen, Sudarshan Nayak "Literature Survey for the Comparative Study of Various High Performance Computing Techniques". International Journal of Computer Trends and Technology (IJCTT) V27(2):80-86, September 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
The advent of high performance
computing (HPC) and graphics processing units
(GPU), present an enormous computation resource
for large data transactions (big data) that require
parallel processing for robust and prompt data
analysis. In this paper, we take an overview of four
parallel programming models, OpenMP, CUDA,
MapReduce, and MPI. The goal is to explore
literature on the subject and provide a high level view
of the features presented in the programming models
to assist high performance users with a concise
understanding of parallel programming concepts.
References
[1] OpenMP Architecture Review Board, ?OpenMP Application
Program Interface, 2008, http://www.openmp.org/mpdocuments/
spec30.pdf.
[2] B. Barney, Introduction to Parallel Computing, Lawrence
Livermore National Laboratory, 2007,
https://computing.llnl.gov/tutorials/parallel_comp/.
[3] J. Diaz, C.Munoz-Caro, and A. Nino, ?A survey of parallel
programming models and tools in the multi and many-core era,
IEEE Transactions on Parallel and Distributed Systems, vol. 23,
no.8, pp.1369–1386, 2012.
[4] W. Gropp, S. Huss-Lederman, A. Lumsdaine et al., MPI: The
Complete Reference, the MPI-2 Extensions, vol. 2, The MIT Press,
1998.
[5] G. Jost, H. Jin, D. Mey, and F. Hatay, ?Comparing the OpenMP,
MPI, and hybrid programming paradigm on an SMP cluster, in
Proceedings of the 5th European workshop on OpenMP
(EWOMP’03), 2003.
[6] J.Dean and S.Ghemawat, ?MapReduce: simplified data
processing on large clusters, Communications of the ACM, vol. 51,
no. 1, pp. 107–113, 2008.
[7] S. Ghemawat, H. Gobioff, and S.-T. Leung, ?The Google file
system, in Proceedings of the 19th ACM Symposium on Operating
Systems Principles (SOSP ’03), pp. 29–43, October 2003.
[8] C. Ranger, R. Raghuraman, A. Penmetsa, G. Bradski, and C.
Kozyrakis,?Evaluating MapReduce for multi-core and
multiprocessor systems, in Proceedings of the 13th IEEE
International Symposium on High Performance Computer
Architecture (HPCA’07), pp. 13–24, Scottsdale, AZ, USA, February
2007.
[9] S. J. Plimpton and K. D. Devine,?MapReduce in MPI for
largescale graph algorithms, Parallel Computing, vol. 37, no. 9,
pp.610–632, 2011.
[10]. NVIDIA, ?CUDA C Programming Guide, no. July. NVIDIA
Corporation, 2013.
[11]. Wikipedia, ?General-purpose computing on graphics
processing units, 2013.
[12]. Y.Charlie Hu, Honghui Lu, Alan L Cox and Willy
Zwaenepoel, ?OpenMp for Networks of SMPs, Parallel
Processing , 13th International and 10th Symposium on Parallel and
Distributed Processing, pp. 302-310, 1999.
[13]. John Bircsak, Peter Craig, RaeLyn Crowell, Zarka Cvetanovic,
Jonathan Harris, C. Alexander Nelson and Carl D. Offner,
?Extending OpenMP For NUMA Machines, SC `00 Proceedings
of the 2000 ACM/IEEE conference on Supercomputing, Article no.
48, 2000.
[14]. Zaid Abdi Alkareem Alyasseri , Kadhim Al-Attar, Mazin
Nasser and Ismail, ?Parallelize Bubble and Merge Sort Algorithms
Using Message Passing Interface (MPI), Publication eprint
arXiv:1411.5283, 2014.
[15]. Pavan Balaji, Darius Buntinas, David Goodell, William
Gropp, Torsten Hoefler, Sameer Kumar, Ewing Lusk, Rajeev
Thakur and Jesper Larsson Traff, ?MPI on Millions of Core,
Parallel Proceesing Letter, vol. 21, issue 01, 2011.
[16]. Colby Ranger, Ramanan Raghuraman, Arun Penmetsa, Gary
Bradski and Christos Kozyrakis, ?Evaluating MapReduce for Multicore
and Multiprocessor Systems, in Proceedings of the 13th IEEE
International Symposium on High Performance Computer
Architecture (HPCA `07), pp. 13-24, Scottsdale, AZ, USA,
February 2007.
[17]. Hung-chih Yang, Ali Dasdan, Ruey-Lung Hsiao and D. Stott
Parker,?Map-reduce-merge: Simplified Relational Data Processing
on Large Clusters, in Proceedings ACM SIGMOD international
Conference on Management of Data, pp. 1029-1040, 2007.
[18]. Wladimir J. van der Laan, Andrei C. Jalba, and Jos B.T.M.
Roerdink, ?Accelerating Wavelet Lifting on Graphics Hardware
Using CUDA, IEEE transactions on Parallel and Distributed, vol.
22, issue 01, pp. 132-146, 2010.
[19]. Jedrzej Kowalczuk, Eric T. Psota, Lance C. Pérez, ?Real-time
Stereo Matching on CUDA using an Iterative Refinement Method
for Adaptive Support-Weight Correspondences, IEEE transactions
on Circuits and System for Video Technologies, vol. 23,isuue 01,
pp. 94-104,2012.
[20]. The OpenMp Forum. OpenMp Fortran Application Program
Interface, Version 1.0, http:/www.openmp.org, Oct 1997.
[21]. The OpenMp Forum. OpenMp C and C++ Application
Program Interface, Version 1.0, http:/www.openmp.org, Oct 1998.
[22]. CUDA Zone,
http://www.nvidia.com/object/cuda_home_new.html, Oct. 2011.
[23]. Nvidia Developer Zone, http://developer.nvidia.com, Oct.
2011.
[24]. D. Kirk and W. Hwu, Programming Massively Parallel
Processors: A Hands-on Approach. Morgan Kaufmann, 2010.
[25]. Nvidia Company. Nvidia CUDA Programming Guide, v3.0,
2010.
[26]. Nvidia Company. Nvidia CUDA C Programming Best
Practices Guide, Version 3.0, 2010.
[27]. T.G. Mattson, B.A. Sanders, and B. Massingill, Patterns for
Parallel Programming. Addison-Wesley Professional, 2005.
[28]. Sol Ji Kang, Sang Yeon Lee, and KeonMyung Lee,
?Performance Comparison of OpenMP, MPI, and MapReduce in
Practical Problems, Advances in Multimedia, Research Article,
2014.
[29]. Shuai Che_, Michael Boyer, Jiayuan Meng, David Tarjan,
Jeremy W. Sheaffer, Kevin Skadron, ?A performance study of
general-purpose applications on graphics processors using CUDA,
Published in J. Parallel Distrib. Comput.,vol. 68, pp. 1370-1380,
2008.
[30]. Cleverson Lopes Ledur, Carlos M. D. Zeve, Julio C. S. dos
Anjos, ?Comparative Analysis of OpenACC, OpenMP and CUDA
using Sequential and Parallel Algorithms, 11th Workshop on
Parallel and Distributed Processing (WSPPD), Universidade
Luterana do Brasil, Information Systems, BR 116, n. 5.724,
Moradas da Colina – Guaba/RS.
Keywords
OpenMP, MPI, CUDA, MapReduce,
GPU.