• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2021, Vol. 43 ›› Issue (11): 1920-1925.

• 高性能计算 • 上一篇    下一篇

水声环境特征参数并行预报方法研究

范培勤1,2,过武宏1,2,韩梅1,2,唐帅1,2,张驰1,2   

  1. (1.海军潜艇学院,山东 青岛 266199;2.青岛海洋科学与技术试点国家实验室,山东 青岛 266000 )
  • 收稿日期:2020-08-16 修回日期:2020-11-30 接受日期:2021-11-25 出版日期:2021-11-25 发布日期:2021-11-19
  • 基金资助:
    国防科技创新特区项目(18-H863-05-ZT-001-012-06);基础计划加强重点基础研究项目(2019-JCJQ-ZD-149)

A parallel predication method of underwater acoustic environment characteristic parameters

FAN Pei-qin1,2,GUO Wu-hong1,2,HAN Mei1,2,TANG Shuai1,2,Zhang Chi1,2   

  1. (1.Navy Submarine Academy,Qingdao 266199;

    2.Pilot National Laboratory for Marine Science and Technology,Qingdao 266000,China)

  • Received:2020-08-16 Revised:2020-11-30 Accepted:2021-11-25 Online:2021-11-25 Published:2021-11-19

摘要: 随着水声装备的快速发展,其性能发挥与海洋环境的耦合越来越紧密,如何为水声传感器提供长时间、大范围、精细化水声环境参数信息,对优化水声传感器设计,充分发挥其探测性能,实现海洋环境与传感器性能发挥的最佳匹配具有重要意义。利用MPI并行编程环境开发了水声环境特征参数并行预报程序,实现了水声环境特征参数的快速预报,针对并行程序存在的任务负载不均衡问题,分析了造成负载分配不均衡的原因,给出了性能优化的策略和方法。测试结果表明,优化后的并行程序,负载均衡问题得到了有效改善,计算时间大幅缩短,大大提升了水声环境参数预报能力。

关键词: 水声环境, 特征参数, 并行计算, MPI

Abstract: With the rapid development of underwater acoustic equipment, the coupling between its performance and ocean environment is becoming stronger and stronger. How to provide long-time, wide-ranger and fine underwater acoustic characteristic parameter information for underwater acoustic sensors is of great importance for optimizing the design of underwater acoustic sensors and making full use of their detection performance to realize the best matching between ocean environment and sensor performance. The parallel prediction program of underwater acoustic environment characteristic parameters is developed by using the MPI parallel programming environment. Aiming at the problem of uneven load distribution in parallel programs, the causes of uneven load distribution are analyzed, the strategies and methods of performance optimization are given. The results show that the load balancing problem of the optimized parallel program is improved, the computing time is greatly reduced, and the prediction ability of underwater acoustic environment parameters is greatly improved.

Key words: underwater acoustic environment, characteristic parameter, parallel computing, MPI