SWAMP: Smith-Waterman using associative massive parallelism

One of the most commonly used tools by computational biologists is some form of sequence alignment. Heuristic alignment algorithms developed for speed and their multiple results such as BLAST [1] and FASTA [2] are not a total replacement for the more rigorous but slower algorithms like SmithWaterman [3]. The different techniques complement one another. A heuristic can filter dissimilar sequences from a large database such as GenBank [4] and the Smith-Waterman algorithm performs more detailed, in-depth alignment in a way not adequately handled by heuristic methods. An associative parallel Smith-Waterman algorithm has been improved and further parallelized. Analysis between different algorithms, different types of file input, and different input sizes have been performed and are reported here. The newly developed associative algorithm reduces the running time for rigorous pairwise local sequence alignment.

• Type: Conference
• Year: 2008
• Where: IPPS
• Authors: Shannon Steinfadt, Johnnie W. Baker
• Keywords: Distributed And Parallel Computing, Heuristic Alignment Algorithms, IPPS 2008, Sequence Alignment, Smith-Waterman Algorithm