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A Critical Study of Efficient Multi-core EM Clustering

by D. J. Nagendra Kumar, J. V. R. Murthy, N. B. Venkateswarlu
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 23
Year of Publication: 2012
Authors: D. J. Nagendra Kumar, J. V. R. Murthy, N. B. Venkateswarlu
10.5120/6423-8926

D. J. Nagendra Kumar, J. V. R. Murthy, N. B. Venkateswarlu . A Critical Study of Efficient Multi-core EM Clustering. International Journal of Computer Applications. 43, 23 ( April 2012), 41-44. DOI=10.5120/6423-8926

@article{ 10.5120/6423-8926,
author = { D. J. Nagendra Kumar, J. V. R. Murthy, N. B. Venkateswarlu },
title = { A Critical Study of Efficient Multi-core EM Clustering },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 23 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number23/6423-8926/ },
doi = { 10.5120/6423-8926 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:34:08.419623+05:30
%A D. J. Nagendra Kumar
%A J. V. R. Murthy
%A N. B. Venkateswarlu
%T A Critical Study of Efficient Multi-core EM Clustering
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 23
%P 41-44
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The state-of-the-art computer hardware is coming with multi-core processors. Even mobile phones are coming with dual-core processors. OpenMP is one technology supporting parallel programming on multi-core shared memory systems with the help of threads. In this paper, we observed the execution times Serial EM Clustering running on single-core and Parallel EM Clustering methods using OpenMP on I3 system. Observations are made varying number of threads, samples, dimensions and clusters. The results show that OpenMP Lower Triangular Canonical Form with Forward Substitution and Winograd’s approach (OLFW) EM gives a considerable speed-up of 2.7 over serial standard EM.

References
  1. Manasi N. Joshi, "Parallel K-means Algorithm on Distributed Memory Multiprocessors", Project Report, Computer Science Department, University of Minnesota, Twin Cities, Spring 2003.
  2. S. N. Tirumala Rao, E. V. Prasad, and N. B. Venkateswrlu, “A Critical Performance Study of Memory Mapping on Multi-core Processors: An Experiment with K-means Algorithm with Large Data Mining Data Sets”, IJCA (0975-8887) 2010 Volume 1-No. 9.
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  5. Waghmare, Vivek N. and Kulkarni, Dinesh B., “Convex Hull Using K-means Clustering in Hybrid (MPI/OpenMP) Environment”, Int. Conf. on Computational Intelligence and Communication Networks 2010, pp. 150-153.
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  7. D. J. Nagendra Kumar and J. V. R. Murthy, “Some Studies of Expectation Maximization Clustering Algorithm to Enhance Performance”, Research Cell: An International Journal of Engineering Sciences, ISSN: 2229-6913, Vol. 2, July 2011, pp. 254-269.
  8. D. J. Nagendra Kumar, J. V. R. Murthy and N. B. Venkateswarlu, “Fast Expectation Maximization Clustering Algorithm”, International Journal of Computational Intelligence Research (IJCIR) ISSN: 0973-1873, Vol. 8, No. 2 (2012), pp. 71-94.
  9. D. J. Nagendra Kumar, J. V. R. Murthy and N. B. Venkateswarlu, “Computation Reduction of Expectation Maximization Clustering Using Winograd's Method”, Proceedings of IEEE International Conference on Electronics Computer Technology ICECT-2012, pp. 255-259.
  10. A. P. Dempster and N. M. Laird and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of The Royal Statistical Society, Series B, 39(1):1--38, 1977.
Index Terms

Computer Science
Information Sciences

Keywords

Openmp Multi-core Parallel Programming Expectation Maximization Em

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