430 Int. J. Bioinformatics Research and Applications, Vol. 2, No. 4, 2006 Copyright © 2006 Inderscience Enterprises Ltd. Optimised fine and coarse parallelism for sequence homology search Xiandong Meng* Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA E-mail: meng@ece.eng.wayne.edu *Corresponding author Vipin Chaudhary Institute for Scientific Computing, Wayne State University, Detroit, MI 48202, USA Fax: 313-577-6868 E-mail: vipin@wayne.edu Abstract: New biological experimental techniques are continuing to generate large amounts of data using DNA, RNA, human genome and protein sequences. The quantity and quality of data from these experiments makes analyses of their results very time-consuming, expensive and impractical. Searching on DNA and protein databases using sequence comparison algorithms has become one of the most powerful techniques to better understand the functionality of particular DNA, RNA, genome, or protein sequence. This paper presents a technique to effectively combine fine and coarse grain parallelism using general-purpose processors for sequence homology database searches. The results show that the classic Smith-Waterman sequence alignment algorithm achieves super linear performance with proper scheduling and multi-level parallel computing at no additional cost. Keywords: sequence homology search; FASTA; Smith-Waterman algorithm; SSE2; fine grain parallelism; coarse grain parallelism; cluster computing; bioinformatics research and applications. Reference to this paper should be made as follows: Meng, X. and Chaudhary, V. (2006) ‘Optimised fine and coarse parallelism for sequence homology search’, Int. J. Bioinformatics Research and Applications, Vol. 2, No. 4, pp.430–441. Biographical notes: Xiandong Meng is a PhD Candidate in the Department of Electrical and Computer Engineering of Wayne State University. He received his MS Degree in Computer Engineering from Wayne State University. He works in the Parallel and Distributed Computing Lab. His research involves high-throughput bioinformatics computing and reconfigurable computer architecture. Vipin Chaudhary is an Associate Professor in the Department of Computer Science and Director of Institute for Scientific Computing at Wayne State University. He received his MS and PhD Degrees in Computer Science and Electrical and Computer Engineering from the University of Texas at Austin, respectively. He has authored/co-authored over 85 publications. His current