H-BLAST：一种用于具有图形处理器的异构计算机的快速蛋白质序列比对工具包。

H-BLAST: a fast protein sequence alignment toolkit on heterogeneous computers with GPUs.

作者信息

Ye Weicai, Chen Ying, Zhang Yongdong, Xu Yuesheng

机构信息

School of Data and Computer Science, and Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, People's Republic of China.

Professor Emeritus of Department of Mathematics, Syracuse University, Syracuse, NY 13244, USA.

出版信息

Bioinformatics. 2017 Apr 15;33(8):1130-1138. doi: 10.1093/bioinformatics/btw769.

DOI:10.1093/bioinformatics/btw769

PMID:28087515

Abstract

MOTIVATION

The sequence alignment is a fundamental problem in bioinformatics. BLAST is a routinely used tool for this purpose with over 118 000 citations in the past two decades. As the size of bio-sequence databases grows exponentially, the computational speed of alignment softwares must be improved.

RESULTS

We develop the heterogeneous BLAST (H-BLAST), a fast parallel search tool for a heterogeneous computer that couples CPUs and GPUs, to accelerate BLASTX and BLASTP-basic tools of NCBI-BLAST. H-BLAST employs a locally decoupled seed-extension algorithm for better performance on GPUs, and offers a performance tuning mechanism for better efficiency among various CPUs and GPUs combinations. H-BLAST produces identical alignment results as NCBI-BLAST and its computational speed is much faster than that of NCBI-BLAST. Speedups achieved by H-BLAST over sequential NCBI-BLASTP (resp. NCBI-BLASTX) range mostly from 4 to 10 (resp. 5 to 7.2). With 2 CPU threads and 2 GPUs, H-BLAST can be faster than 16-threaded NCBI-BLASTX. Furthermore, H-BLAST is 1.5-4 times faster than GPU-BLAST.

AVAILABILITY AND IMPLEMENTATION

https://github.com/Yeyke/H-BLAST.git.

CONTACT

yux06@syr.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

序列比对是生物信息学中的一个基本问题。BLAST是为此目的经常使用的工具，在过去二十年中有超过118000次引用。随着生物序列数据库规模呈指数级增长，比对软件的计算速度必须提高。

结果

我们开发了异构BLAST（H-BLAST），这是一种用于异构计算机的快速并行搜索工具，它结合了CPU和GPU，以加速NCBI-BLAST的BLASTX和BLASTP基本工具。H-BLAST采用局部解耦的种子扩展算法以在GPU上获得更好的性能，并提供性能调优机制以在各种CPU和GPU组合中提高效率。H-BLAST产生与NCBI-BLAST相同的比对结果，并且其计算速度比NCBI-BLAST快得多。H-BLAST相对于顺序NCBI-BLASTP（分别为NCBI-BLASTX）实现的加速比大多在4到10（分别为5到7.2）之间。使用2个CPU线程和2个GPU时，H-BLAST可以比16线程的NCBI-BLASTX更快。此外，H-BLAST比GPU-BLAST快1.5到4倍。