谱方法求解水声传播问题的优化与并行

水声传播数值计算的效率是各类水声学应用关心的核心因素之一,谱方法作为求解微分方程的一种数值方法,具有精度高、收敛速度快等优点,因此,近年来利用简正波-谱方法求解水声传播方程引起了许多学者的关注;然而,谱方法计算量更大,计算时间更长,在求解大范围海域声传播问题时,难以满足实时性的需求.因此,需要借助现代高性能计算机系统,...

Optimization and parallelization of spectral method for solving underwater acoustic propagation

The efficiency of numerical calculation of underwater acoustic propagation is one of the key factors in various applications of underwater acoustic science. As a numerical method for solving diffe- rential equations, spectral method has the advantages of high accuracy and fast convergence. Therefore, using normal wave-spectrum method to solve underwater acoustic propagation equations has attracted the attentions of many scholars in recent years. However, the spectral method requires more computation, and the computational efficiency is still difficult to meet the real-time requirements when solving large-scale underwater acoustic propagation problems. Therefore, it is necessary to use a high- performance computing system to carry out performance optimization and program parallelization research on the typical spectral method to calculate the underwater sound propagation program to improve the computing performance. Firstly, the calculation flow and hotspot functions of the program are analyzed. Then, the optimization methods of compiler options, calling high-performance math library MKL, memory access optimization, and reduced computation are studied. Finally, multi-thread parallel acceleration processing is carried out on the many-core high-performance computing platform. Through testing and evaluation on the Tianhe-2 many-core platform, the results show that the running time of the final parallel optimized version of the deep-sea waveguide calculation example is reduced from 584 seconds to 24 seconds compared with the original serial version, which is 23.98 times faster. The calculation time verifies the validity of the used method , and is of great significance to the calculation of the water sound field in the ocean. Further analysis shows that these optimization and parallelization methods also have reference and reference significance for other scientific and engineering numerical calculation problems of the same type on the same platform.