Parallel biological sequence comparison using prefix computations

Srinivas Aluru, Natsuhiko Futamura, Kishan Mehrotra

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

We present practical parallel algorithms using prefix computations for various problems that arise in pairwise comparison of biological sequences. We consider both constant and affine gap penalty functions, full-sequence and subsequence matching, and space-saving algorithms. Commonly used sequential algorithms solve the sequence comparison problems in O(mn) time and O(m + n) space, where m and n are the lengths of the sequences being compared. All the algorithms presented in this paper are time optimal with respect to the sequential algorithms and can use O(n/log n) processors where n is the length of the larger sequence. While optimal parallel algorithms for many of these problems are known, we use a simple framework and demonstrate how these problems can be solved systematically using repeated parallel prefix operations. We also present a space-saving algorithm that uses O(m + n/p) space and runs in optimal time where p is the number of the processors used. We implemented the parallel space-saving algorithm and provide experimental results on an IBM SP-2 and a Pentium cluster.

Original languageEnglish (US)
Pages (from-to)264-272
Number of pages9
JournalJournal of Parallel and Distributed Computing
Volume63
Issue number3
DOIs
StatePublished - Mar 1 2003

Keywords

  • Computational biology
  • Parallel algorithms
  • Parallel prefix
  • Sequence alignments
  • Space-efficient

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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