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

被引:0
作者
Sita Rani
O. P. Gupta
机构
[1] I.K.G. Punjab Technical University,School of Electrical Engineering and Information Technology
[2] Punjab Agricultural University,undefined
来源
The Journal of Supercomputing | 2017年 / 73卷
关键词
Bioinformatics; BLAST; Compute Unified Device Architecture (CUDA); Graphical processing unit (GPU); High-performance computing; Sequence alignment;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:4580 / 4595
页数:15
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