A performance evaluation of a local DNA sequence alignment algorithm on a cluster of workstations

Summary form only given. Biological inspired techniques have proven to be efficient in solving a variety of real problems using parallel and distributed processing. In this paper, we wish to study the DNA sequencing problem known for its computational requirements which far exceed the computing capabilities of the fastest available sequential machines. Sequence comparison is a basic operation of the DNA sequencing problem, mainly due to the large number of DNA sequences. While most of the methods used are based on heuristic paradigms and have relatively a fast execution time, they do not produce optimal alignments sought by most biologists. Recently, many organisms 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 requirements (power and memory). In this paper, we present an efficient parallel strategy for implementing a sequence alignment algorithm for long sequences, and evaluate its performance using a cluster of workstations. This strategy was implemented in JIAJIA, a scope consistent software DSM system. Our results indicate clearly that our scheme is feasible, achieve a good speedup and can help in obtaining a better solution to the DNA sequencing problem when compared to previous schemes.