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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
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Index Terms

Computer Science
Information Sciences

Keywords

Self-organizing Maps Mpi Openmp Hybrid Programming.