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用于求解广阔海域水下声场的射线模型动态混合并行计算

Dynamic hybrid parallel computing of the Ray Model for solving underwater acoustic fields in vast sea.

作者信息

Liao Siyuan, Xiao Wenbin, Wang Yongxian

机构信息

College of Meteorology and Oceanography, National University of Defense Technology, Changsha, 410073, China.

出版信息

Sci Rep. 2024 Oct 25;14(1):25385. doi: 10.1038/s41598-024-76564-x.

DOI:10.1038/s41598-024-76564-x
PMID:39455679
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11512006/
Abstract

Utilizing acoustic information for search route planning will greatly increase the success rate of searching for underwater targets, which requires rapid computing of numerous underwater acoustic fields. The efficiency of traditional computing methods is too low to meet the requirements of rapid applications. In this paper, a underwater multi-acoustic fields computing model is developed based on ray theory, and multi-level hybrid parallel computing strategies are designed based on the model characteristics, and a dynamic scheduling optimization algorithm at process level is introduced to solve the load imbalance problem. All parallel computing strategies are tested in Tianhe-II High Performance Computer (HPC) system, and the tests show that: 1. compared with the serial version, hybrid parallel computing strategy provides a Speedup of 75.7 under 240 cores; 2. after the introduction of the dynamic scheduling optimization algorithm, the speed of solving the underwater acoustic fields is further increased by 28.99% under the same computing resources, and the Speedup reaches 97.67; 3. the optimal combination of process/thread parameter on the Tianhe-II HPC system is given as 3/8, and the final Speedup reaches 112.13.

摘要

利用声学信息进行搜索路线规划将大大提高水下目标搜索的成功率，这需要快速计算大量的水下声场。传统计算方法的效率过低，无法满足快速应用的需求。本文基于射线理论建立了水下多声场计算模型，并根据模型特点设计了多级混合并行计算策略，引入了进程级动态调度优化算法来解决负载不平衡问题。所有并行计算策略均在天河二号高性能计算机（HPC）系统上进行了测试，测试结果表明：1. 与串行版本相比，混合并行计算策略在240个核心下的加速比为75.7；2. 引入动态调度优化算法后，在相同计算资源下，水下声场的求解速度进一步提高了28.99%，加速比达到97.67；3. 给出了天河二号HPC系统上进程/线程参数的最优组合为3/8，最终加速比达到112.13。

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本文引用的文献

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