MSA-CUDA: Multiple Sequence Alignment on Graphics Processing Units with CUDA

Yongchao Liu, B. Schmidt, D. Maskell
{"title":"MSA-CUDA: Multiple Sequence Alignment on Graphics Processing Units with CUDA","authors":"Yongchao Liu, B. Schmidt, D. Maskell","doi":"10.1109/ASAP.2009.14","DOIUrl":null,"url":null,"abstract":"Progressive alignment is a widely used approach for computing multiple sequence alignments (MSAs). However, aligning several hundred or thousand sequences with popular progressive alignment tools such as ClustalW requires hours or even days on state-of-the-art workstations. This paper presents MSA-CUDA, a parallel MSA program, which parallelizes all three stages of the ClustalW processing pipeline using CUDA and achieves significant speedups compared to the sequential ClustalW for a variety of large protein sequence datasets. Our tests on a GeForce GTX 280 GPU demonstrate average speedups of 36.91 (for long protein sequences), 18.74 (for average-length protein sequences), and 11.27 (for short protein sequences) compared to the sequential ClustalW running on a Pentium 4 3.0 GHz processor. Our MSA-CUDA outperforms ClustalW-MPI running on 32 cores of a high performance workstation cluster.","PeriodicalId":202421,"journal":{"name":"2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"93","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASAP.2009.14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 93

Abstract

Progressive alignment is a widely used approach for computing multiple sequence alignments (MSAs). However, aligning several hundred or thousand sequences with popular progressive alignment tools such as ClustalW requires hours or even days on state-of-the-art workstations. This paper presents MSA-CUDA, a parallel MSA program, which parallelizes all three stages of the ClustalW processing pipeline using CUDA and achieves significant speedups compared to the sequential ClustalW for a variety of large protein sequence datasets. Our tests on a GeForce GTX 280 GPU demonstrate average speedups of 36.91 (for long protein sequences), 18.74 (for average-length protein sequences), and 11.27 (for short protein sequences) compared to the sequential ClustalW running on a Pentium 4 3.0 GHz processor. Our MSA-CUDA outperforms ClustalW-MPI running on 32 cores of a high performance workstation cluster.
MSA-CUDA:在CUDA图形处理单元上的多序列对齐
渐进式比对是一种广泛使用的多序列比对方法。然而,使用流行的渐进式对齐工具(如ClustalW)对齐数百或数千个序列需要在最先进的工作站上花费数小时甚至数天的时间。本文介绍了MSA-CUDA,一个并行MSA程序,它使用CUDA并行化ClustalW处理管道的所有三个阶段,并且与序列ClustalW相比,在各种大型蛋白质序列数据集上实现了显着的加速。我们在GeForce GTX 280 GPU上的测试显示,与在Pentium 4 3.0 GHz处理器上运行的序列ClustalW相比,平均速度为36.91(长蛋白质序列),18.74(平均长度蛋白质序列)和11.27(短蛋白质序列)。我们的MSA-CUDA优于在高性能工作站集群的32核上运行的ClustalW-MPI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信