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

S Rani, OP Gupta - The Journal of Supercomputing, 2017 - Springer
The Journal of Supercomputing, 2017Springer
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, ie, 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 …
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.
Springer
以上显示的是最相近的搜索结果。 查看全部搜索结果

Google学术搜索按钮

example.edu/paper.pdf
搜索
获取 PDF 文件
引用
References