GPU-ClustalW: Using Graphics Hardware to Accelerate Multiple Sequence Alignment
School of Computer Engineering, Nanyang Technological University Centre for Advanced Media Technology, SINGAPOUR
High Performance Computing – HiPC 2006 In High Performance Computing – HiPC 2006 , Vol. 4297 (2006), pp. 363-374.
@article{liu2006gpu,
title={GPU-ClustalW: Using graphics hardware to accelerate multiple sequence alignment},
author={Liu, W. and Schmidt, B. and Voss, G. and M{\”u}ller-Wittig, W.},
journal={High Performance Computing-HiPC 2006},
pages={363–374},
year={2006},
publisher={Springer}
}
Molecular Biologists frequently compute multiple sequence alignments (MSAs) to identify similar regions in protein families. However, aligning hundreds of sequences by popular MSA tools such as ClustalW requires several hours on sequential computers. Due to the rapid growth of biological sequence databases biologists have to compute MSAs in a far shorter time. In this paper we present a new approach to reduce this runtime using graphics processing units (GPUs). To derive an efficient mapping onto this type of architecture, we have reformulated the computationally most expensive part of ClustalW in terms of computer graphics primitives. This results in a high-speed implementation with significant runtime savings on a commodity graphics card.
November 1, 2010 by hgpu
