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ESA: An efficient sequence alignment algorithm for biological database search on Sunway TaihuLight

文献类型：期刊论文

作者Zhang, Hao3; Huang, Zhiyi3; Chen, Yawen3; Liang, Jianguo1; Gao, Xiran2,4
刊名PARALLEL COMPUTING
出版日期2023-09-01
卷号117页码:11
关键词Hybrid sequence alignment Biological database search Sunway TaihuLight SW26010 Heterogeneous architecture
ISSN号0167-8191
DOI10.1016/j.parco.2023.103043
英文摘要In computational biology, biological database search has been playing a very important role. Since the COVID19 outbreak, it has provided significant help in identifying common characteristics of viruses and developing vaccines and drugs. Sequence alignment, a method finding similarity, homology and other information between gene/protein sequences, is the usual tool in the database search. With the explosive growth of biological databases, the search process has become extremely time-consuming. However, existing parallel sequence alignment algorithms cannot deliver efficient database search due to low utilization of the resources such as cache memory and performance issues such as load imbalance and high communication overhead. In this paper, we propose an efficient sequence alignment algorithm on Sunway TaihuLight, called ESA, for biological database search. ESA adopts a novel hybrid alignment algorithm combining local and global alignments, which has higher accuracy than other sequence alignment algorithms. Further, ESA has several optimizations including cache-aware sequence alignment, capacity-aware load balancing and bandwidth-aware data transfer. They are implemented in a heterogeneous processor SW26010 adopted in the world's 6th fastest supercomputer, Sunway TaihuLight. The implementation of ESA is evaluated with the Swiss-Prot database on Sunway TaihuLight and other platforms. Our experimental results show that ESA has a speedup of 34.5 on a single core group (with 65 cores) of Sunway TaihuLight. The strong and weak scalabilities of ESA are tested with 1 to 1024 core groups of Sunway TaihuLight. The results show that ESA has linear weak scalability and very impressive strong scalability. For strong scalability, ESA achieves a speedup of 338.04 with 1024 core groups compared with a single core group. We also show that our proposed optimizations are also applicable to GPU, Intel multicore processors, and heterogeneous computing platforms.
资助项目Shandong Provincial Natural Science Foundation, China[ZR2022MF274] ; Shandong Provincial Natural Science Foundation, China[uoo03531]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001073947400001
出版者ELSEVIER
源URL[http://119.78.100.204/handle/2XEOYT63/21161]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhang, Hao
作者单位1.Shandong Univ Sci & Technol, Coll Comp Sci & Engn, Qingdao 266590, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Univ Otago, Dept Comp Sci, Dunedin 9054, New Zealand
4.Chinese Acad Sci, ICT, State Key Lab Proc, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Hao,Huang, Zhiyi,Chen, Yawen,et al. ESA: An efficient sequence alignment algorithm for biological database search on Sunway TaihuLight[J]. PARALLEL COMPUTING,2023,117:11.
APA Zhang, Hao,Huang, Zhiyi,Chen, Yawen,Liang, Jianguo,&Gao, Xiran.(2023).ESA: An efficient sequence alignment algorithm for biological database search on Sunway TaihuLight.PARALLEL COMPUTING,117,11.
MLA Zhang, Hao,et al."ESA: An efficient sequence alignment algorithm for biological database search on Sunway TaihuLight".PARALLEL COMPUTING 117(2023):11.

入库方式： OAI收割

来源：计算技术研究所

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