Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space
Department of Physics and Astronomy, Johns Hopkins University, Baltimore, Maryland 21218, USA
bioRxiv 007641, (1 August 2014)
DOI:10.1101/007641
@article{wilton2014faster,
title={Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space},
author={Wilton, Richard and Budavari, Tamas and Langmead, Ben and Wheelan, Sarah J and Salzberg, Steven and Szalay, Alex},
journal={bioRxiv},
pages={007641},
year={2014},
publisher={Cold Spring Harbor Labs Journals}
}
MOTIVATION: In computing pairwise alignments of biological sequences, software implementations employ a variety of heuristics that decrease the computational effort involved in computing potential alignments. A key element in achieving high processing throughput is to identify and prioritize potential alignments where high-scoring mappings can be expected. These tasks involve list-processing operations that can be efficiently performed on GPU hardware. RESULTS: We implemented a read aligner called A21 that exploits GPU-based parallel sort and reduction techniques to restrict the number of locations where potential alignments may be found. When compared with other high-throughput aligners, this approach finds more high-scoring mappings without sacrificing speed or accuracy. A21 running on a single GPU is about 10 times faster than comparable CPU-based tools; it is also faster and more sensitive in comparison with other recent GPU-based aligners.
August 10, 2014 by hgpu
