标题:BGSA: a bit-parallel global sequence alignment toolkit for multi-core and many-core architectures
作者:Zhang, Jikai; Lan, Haidong; Chan, Yuandong; Shang, Yuan; Schmidt, Bertil; Liu, Weiguo
作者机构:[Zhang, Jikai; Lan, Haidong; Chan, Yuandong; Liu, Weiguo] Shandong Univ, Sch Software, Jinan, Shandong, Peoples R China.; [Shang, Yuan] Zhengzhou Un 更多
通讯作者:Liu, WG;Liu, WG
通讯作者地址:[Liu, WG]Shandong Univ, Sch Software, Jinan, Shandong, Peoples R China;[Liu, WG]Natl Supercomp Ctr Wuxi, Wuxi, Jiangsu, Peoples R China.
来源:BIOINFORMATICS
出版年:2019
卷:35
期:13
页码:2306-2308
DOI:10.1093/bioinformatics/bty930
摘要:Motivation Modern bioinformatics tools for analyzing large-scale NGS datasets often need to include fast implementations of core sequence alignment algorithms in order to achieve reasonable execution times. We address this need by presenting the BGSA toolkit for optimized implementations of popular bit-parallel global pairwise alignment algorithms on modern microprocessors.; Results BGSA outperforms Edlib, SeqAn and BitPAl for pairwise edit distance computations and Parasail, SeqAn and BitPAl when using more general scoring schemes for pairwise alignments of a batch of sequence reads on both standard multi-core CPUs and Xeon Phi many-core CPUs. Furthermore, banded edit distance performance of BGSA on a Xeon Phi-7210 outperforms the highly optimized NVBio implementation on a Titan X GPU for the seed verification stage of a read mapper by a factor of 4.4.; Availability and implementation BGSA is open-source and available at https://github.com/sdu-hpcl/BGSA.
收录类别:SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069762861&doi=10.1093%2fbioinformatics%2fbty930&partnerID=40&md5=921f7fcd4f4513dee2eab0bb9af2bc8f
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