Assessment of the parallelization approach of <i>d2_cluster</i> for high‐performance sequence clustering

200222 citationsJournal Article

Authors

Alan Christoffels · University of the Western Cape

Winston A. Hide · University of the Western Cape

Abstract

The exponential increase in expressed sequence tag (EST) sequence data amplifies the computational cost of clustering sequences such that new algorithms are required to analyze data at a greater rate. We have parallelized d2_cluster on a SGI Origin 2000 multiprocessor and observed a speedup of approximately 100x on 126 processors when processing a 15,876 EST dataset. The parallelized d2_cluster code is obtainable from the SANBI website (http://www.sanbi.ac.za/CODES).

Topics & Keywords

Algorithms and Data Compression Genomics and Phylogenetic Studies Gene expression and cancer classification

Publication Details

Published in: Journal of Computational Chemistry

Volume 23, Issue 7, pp. 755-757

DOI: 10.1002/jcc.10025

Field-Weighted Citation Impact: 2.58

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Assessment of the parallelization approach of <i>d2_cluster</i> for high‐performance sequence clustering

Authors

Abstract

Topics & Keywords

Publication Details