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The Journal of Supercomputing

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07-04-2017

CLUS_GPU-BLASTP: accelerated protein sequence alignment using GPU-enabled cluster

Authors: Sita Rani, O. P. Gupta

Published in: The Journal of Supercomputing | Issue 10/2017

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Abstract

Basic Local Alignment Search Tool (BLAST) is one of the most frequently used algorithms for bioinformatics applications. In this paper, an accelerated implementation of protein BLAST, i.e., CLUS_GPU-BLASTP for multiple query sequence processing in parallel, on graphical processing unit (GPU)-enabled high-performance cluster is proposed. The experimental setup consisted of a high-performance GPU-enabled cluster. Each compute node of the cluster consisted of two hex-core Intel, Xeon 2.93 GHz processors with 50 GB RAM and 12 MB cache. Each compute node was also equipped with a NVIDIA M2050 GPU. In comparison with the famous GPU-BLAST, our BLAST implementation is 2.1 times faster on single compute node. On a cluster of 12 compute nodes, our implementation gave a speedup of 13.2X. In comparison with standard single-threaded NCBI-BLAST, our implementation achieves a speedup ranging from 7.4X to 8.2X.

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Title: CLUS_GPU-BLASTP: accelerated protein sequence alignment using GPU-enabled cluster
Authors: Sita Rani
O. P. Gupta
Publication date: 07-04-2017
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 10/2017
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-017-2036-4

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