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Accelerating Protein Sequence Search in a Heterogeneous Computing System

Shucai Xiao, Heshan Lin, Wu-chun Feng
Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, Virginia 24061
IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2011

@inproceedings{xiao2011accelerating,

   title={Accelerating Protein Sequence Search in a Heterogeneous Computing System},

   author={Xiao, S. and Lin, H. and Feng, W.},

   booktitle={Parallel & Distributed Processing Symposium (IPDPS), 2011 IEEE International},

   pages={1212–1222},

   year={2011},

   organization={IEEE}

}

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The "Basic Local Alignment Search Tool” (BLAST) is arguably the most widely used computational tool in bioinformatics. However, the computational power required for routine BLAST analysis has been outstripping Moore’s Law due to the exponential growth in the size of the genomic sequence databases that BLAST searches on. To address the above issue, we propose the design and optimization of the BLAST algorithm for searching protein sequences (i.e., BLASTP) in a heterogeneous computing system. The end result is a BLASTP implementation that delivers a seven-fold speedup over the sequential BLASTP for the most computationally intensive phase (i.e., hit detection and ungapped extension) on a NVIDIA Fermi C2050 GPU. In addition, when pipelining the processing on a dual-core CPU and the NVIDIA Fermi GPU, our implementation can achieve a six-fold speedup for the overall program execution.
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