CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

An Efficient Parallel Algorithm for Self-Organizing Maps using MPI - OpenMP based Cluster

Published on February 2015 by Bhavik Patel, Anurag Jajoo, Yash Tibrewal, Amit Joshi
journal_cover_thumbnail

Advanced Computing and Communication Techniques for High Performance Applications
Foundation of Computer Science USA
ICACCTHPA2014 - Number 2
February 2015
Authors: Bhavik Patel, Anurag Jajoo, Yash Tibrewal, Amit Joshi
d88da66a-b2e5-44c8-bf66-6f96b68f6f88

Bhavik Patel, Anurag Jajoo, Yash Tibrewal, Amit Joshi . An Efficient Parallel Algorithm for Self-Organizing Maps using MPI - OpenMP based Cluster. Advanced Computing and Communication Techniques for High Performance Applications. ICACCTHPA2014, 2 (February 2015), 5-9.

@article{
author = { Bhavik Patel, Anurag Jajoo, Yash Tibrewal, Amit Joshi },
title = { An Efficient Parallel Algorithm for Self-Organizing Maps using MPI - OpenMP based Cluster },
journal = { Advanced Computing and Communication Techniques for High Performance Applications },
issue_date = { February 2015 },
volume = { ICACCTHPA2014 },
number = { 2 },
month = { February },
year = { 2015 },
issn = 0975-8887,
pages = { 5-9 },
numpages = 5,
url = { /proceedings/icaccthpa2014/number2/19437-6018/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Advanced Computing and Communication Techniques for High Performance Applications
%A Bhavik Patel
%A Anurag Jajoo
%A Yash Tibrewal
%A Amit Joshi
%T An Efficient Parallel Algorithm for Self-Organizing Maps using MPI - OpenMP based Cluster
%J Advanced Computing and Communication Techniques for High Performance Applications
%@ 0975-8887
%V ICACCTHPA2014
%N 2
%P 5-9
%D 2015
%I International Journal of Computer Applications
Abstract

Cluster Computing is based on the concept that an application can be divided into smaller subtasks which when distributed to different nodes on a cluster (using MPI) will enhance the performance of the application. We can further enhance the performance of that application using a shared programming interface like OpenMP. The Self-Organizing Maps which are extensively used in domains like speech recognition and data classification require considerable amount of time in the training process. This paper proposes a parallel algorithm on a MPI - OpenMP based cluster to reduce the time taken in training and enhance the performance of Self-Organizing Maps (SOM). The results of the algorithm demonstrated a speed-up of 15. 316 as compared to the sequential training of the SOM.

References
  1. Lawrence, Richard D. , George S. Almasi, and Holly E. Rushmeier. "A scalable parallel algorithm for self-organizing maps with applications to sparse data mining problems. " Data Mining and Knowledge Discovery 3. 2 pp. 171-195, 1999.
  2. Silva, Bruno, and N. C. Marques. "A hybrid parallel SOM algorithm for large maps in data-mining. " New Trends in Artificial Intelligence (2007).
  3. Ultsch, Alfred, and H. Peter Siemon. "Kohonen's Self Organizing Feature Maps for Exploratory Data Analysis. " Proc. INNC'90, Int. Neural Network Conf. pp. 305-308, 1990.
  4. Ultsch, Alfred. "Maps for the visualization of high-dimensional data spaces. " Proc. Workshop on Self organizing Maps. pp. 225-230, 2003.
  5. Stefanovic, Pavel, and Olga Kurasova. "Visual analysis of self-organizing maps. " Nonlinear Analysis 16. 4 pp. 488-504, 2011.
  6. Message Passing Interface: MPI http://www. mpi-forum. org?
  7. MPICH http://www. mpich. org
  8. OpenMP http://www. openmp. org/?
  9. UCI Machine Learning Repository http://http://archive. ics. uci. edu/ml/
  10. Radenski, Atanas. "Shared memory, message passing, and hybrid merge sorts for standalone and clustered smps. " Proc. PDPTA vol. 11, pp. 367-373, 2011.
  11. Kohonen, Teuvo. "The self-organizing map. " Proceedings of the IEEE 78, no. 9 pp. 1464-1480, 1990.
  12. Kohonen, Teuvo, Erkki Oja, Olli Simula, Ari Visa, and Jari Kangas. "Engineering applications of the self-organizing map. " Proceedings of the IEEE 84, no. 10 pp. 1358-1384, 1996.
Index Terms

Computer Science
Information Sciences

Keywords

Self-organizing Maps Mpi Openmp Hybrid Programming.