Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 12
3611-3616

Parallel optimization algorithm of high resolution ocean data assimilation for HYCOM

Cao Lianyu1
Zhang Guizhao2
Xiao Junmin2
Hong Xuehai2
Tan Guangming2
1. School of Computer & Communication Engineering, University of Science & Technology Beijing, Beijing 100083, China
2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China
DOI: 10.19734/j.issn.1001-3695.2021.04.0141

Abstract

The HYCOM mode requires higher I/O throughput and less computation, which brings great challenges to the design of high salable parallel algorithm. Therefore, this paper designed a parallel optimization algorithm based on region decomposition for high-throughput ocean data assimilation. First of all, it proposed a flexible file access approach for reading a large number of data from disks. As a result, it avoided the data accessing conflict successfully, and decreased the frequency of disk addressing operations significantly. Next, it designed a communication-avoiding strategy to reduce the communication volume at the cost of some additional computations. Furthermore, it presented a pipe-flow scheme for data exchange to conduct conflict-free message passing. Consequently, it developed a fast data-obtaining algorithm for the data assimilation. The experiments show that the fast data-obtaining algorithm gains a performance of 5x speedup compared with the original one. More specifically, the new approach achieves 6x speedup on average for the file reading process and 2.7x speedup on average for the communication between processors.

Foundation Support

国家重点研发计划重点专项资助项目(2016YFC1401706)
国家自然科学基金资助项目(61802369)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.04.0141
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 12
Section: Algorithm Research & Explore
Pages: 3611-3616
Serial Number: 1001-3695(2021)12-015-3611-06

Publish History

[2021-12-05] Printed Article

Cite This Article

曹连雨, 张桂赵, 肖俊敏, 等. 面向HYCOM的高分辨率海洋数据同化并行算法优化 [J]. 计算机应用研究, 2021, 38 (12): 3611-3616. (Cao Lianyu, Zhang Guizhao, Xiao Junmin, et al. Parallel optimization algorithm of high resolution ocean data assimilation for HYCOM [J]. Application Research of Computers, 2021, 38 (12): 3611-3616. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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