Authors: Ning Weng, Benfano Soewito
Addresses: Department of Electrical and Computer Engineering, Southern Illinois University, 1230 Lincoln Drive, Carbondale, IL 62901, USA. ' Department of Electrical and Computer Engineering, Southern Illinois University, 1230 Lincoln Drive, Carbondale, IL 62901, USA
Abstract: Sequence searching is one of major operations in modern bioengineering. Recent emerging multicore provides a promising technology to enhance sequence searching performance. However, efficiently employing the multicore for a uniprocessor-oriented algorithm is a difficult task. This paper presents a methodology to profile processing requirements for DNA sequence search algorithms, parallelise them onto multicore, and analytically evaluate their performance. The key feature of this methodology is that entire processes are automated and it requires users little understanding of the complexity of algorithms and multicore hardware architecture. Our methodology considers three approaches to parallelise searching operations: queries, database, and task segmentation.
Keywords: sequence searching; search algorithms; parallel processing; multicore; performance evaluation; DNA sequences; computational biology.
International Journal of Computational Biology and Drug Design, 2008 Vol.1 No.3, pp.313 - 327
Available online: 26 Nov 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article