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MSA-CUDA: Multiple Sequence Alignment on Graphics Processing Units with CUDA

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell
School of Computer Engineering, Nanyang Technological University, Singapore, 639798
Application-Specific Systems, Architectures and Processors, IEEE International Conference on In 2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors, Vol. 0 (July 2009), pp. 121-128.

@conference{liu2009msa,

   title={MSA-CUDA: multiple sequence alignment on graphics processing units with CUDA},

   author={Liu, Y. and Schmidt, B. and Maskell, D.L.},

   booktitle={Application-specific Systems, Architectures and Processors, 2009. ASAP 2009. 20th IEEE International Conference on},

   pages={121–128},

   issn={1063-6862},

   year={2009},

   organization={IEEE}

}

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Progressive alignment is a widely used approach for computing multiple sequence alignments (MSAs). However, aligning several hundred or thousand sequences with popular progressive alignment tools such as ClustalW requires hours or even days on state-of-the-art workstations. This paper presents MSA-CUDA, a parallel MSA program, which parallelizes all three stages of the ClustalW processing pipeline using CUDA and achieves significant speedups compared to the sequential ClustalW for a variety of large protein sequence datasets. Our tests on a GeForce GTX 280 GPU demonstrate average speedups of 36.91 (for long protein sequences), 18.74 (for average-length protein sequences), and 11.27 (for short protein sequences) compared to the sequential ClustalW running on a Pentium 4 3.0 GHz processor. Our MSA-CUDA outperforms ClustalW-MPI running on 32 cores of a high performance workstation cluster.
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