Using a DSM application to locally align DNA sequences

Authors:
R. B. Batista;D. N. Silva;A. C. M. A. de Melo;L. Weigang
Affiliations:
Dept. of Comput. Sci., Univ. of Brasilia, Subsolo, Brazil;Dept. of Comput. Sci., Univ. of Brasilia, Subsolo, Brazil;Dept. of Comput. Sci., Univ. of Brasilia, Subsolo, Brazil;Dept. of Comput. Sci., Univ. of Brasilia, Subsolo, Brazil
Venue:
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Year:
2004

Citing 0
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Parallel Strategies for Local Biological Sequence Alignment in a Cluster of Workstations

IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 15 - Volume 16
Parallel strategies for the local biological sequence alignment in a cluster of workstations

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An exact parallel algorithm to compare very long biological sequences in clusters of workstations

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Parallel smith-waterman algorithm for local DNA comparison in a cluster of workstations

WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms

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Abstract

Sequence comparison is a basic operation in DNA sequencing projects, and most sequence comparison methods used are based on heuristics, that are faster but do not produce optimal alignments. Recently, many organisms have had their DNA entirely sequenced, and this reality presents the need for comparing long DNA sequences, which is a challenging task due to its high demands for computational power and memory. Although DSM is presented as a feasible parallel programming paradigm, much of the work in DSM is validated by benchmarks and there are only a few examples of real parallel applications running on DSM systems. In this article, we present and evaluate a parallelization strategy for implementing a local DNA sequence alignment algorithm. This strategy was implemented in JIAJIA, a scope consistent software DSM system. Our results on an eight-machine cluster presented very good speedups, which are comparable with the ones obtained with MPI, showing that our parallelization strategy and programming support were appropriate.