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

doi:10.1016/j.parco.2023.103043

	ESA: An efficient sequence alignment algorithm for biological database search on Sunway TaihuLight
	Zhang, Hao 1; Huang, Zhiyi 1; Chen, Yawen 1; Liang, Jianguo 2; Gao, Xiran 3,4
	2023-09-01
发表期刊	PARALLEL COMPUTING
ISSN	0167-8191
卷号	117 页码:11
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.
关键词	Hybrid sequence alignment Biological database search Sunway TaihuLight SW26010 Heterogeneous architecture
DOI	10.1016/j.parco.2023.103043
收录类别	SCI
语种	英语
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
WOS类目	Computer Science, Theory & Methods
WOS记录号	WOS:001073947400001
出版者	ELSEVIER
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21162
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.Univ Otago, Dept Comp Sci, Dunedin 9054, New Zealand 2.Shandong Univ Sci & Technol, Coll Comp Sci & Engn, Qingdao 266590, Peoples R China 3.Chinese Acad Sci, ICT, State Key Lab Proc, Beijing, Peoples R China 4.Univ Chinese Acad Sci, 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.