TLM、FDTD和Haar小波MRTD算法在电磁仿真中的性能比较

E. Hu, P. So, M. Fujii, W. Liu, W. Hoefer
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引用次数: 0

摘要

测试了TLM、FDTD、0-0阶和1阶Haar小波MR.TD算法在计算时间、计算机内存和计算精度方面的性能。结果表明:(1)FDTD算法的速度约为TLM算法的1.25倍。0阶和1阶mr - td的CPU运行时间几乎与FDTD相同,尽管在相同的持续时间内,0阶和1阶MRTD所需的时间步长要少得多。CPU运行时随时间步长呈线性变化。因此,每个算法的CPU运行时间主要取决于每个时间步必须从内存中检索和存储的变量的数量;(2)由于每个时间步的数值比较和内存重新分配,阈值大大增加了计算负荷;(3)一阶Haar小波MRTD可以节省更多的内存。最佳相对阈值分数约为0.01%,在保持合理精度的同时可以节省大量内存。但是CPU运行时间对于使用阈值技术的0-0阶和1阶MRTD来说太长了。因此,应该考虑计算效率和内存节省之间的权衡。一个最佳的过程和精心设计的数据结构是必要的,以确保内存需求保持在最低限度,同时保持计算效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance comparison of TLM, FDTD and Haar wavelet MRTD algorithms for electromagnetic simulations
The performance in computation time, computer memory and computation accuracy of the TLM, FDTD, 0-0rder and 1st-Order Haar wavelet MR.TD algorithms have been tested. The results show: (1) The FDTD algorithm is about 1.25 times as fast as TLM. The CPU runtimes for the 0- and 1st-Order MR.TD are almost the same as that of FDTD although much less time steps are required in the 0- and 1st-Order MRTD for the same time duration. The CPU runtimes linearly vary with the time step. Thus the CPU runtime of each algorithm is mainly determined by the number of variables that must be retrieved from, and stored in memory at each time step; (2) Because of the numerical comparison and memory reallocation in each time step, thresholding greatly increases computing load; (3) The 1st-Order Haar wavelet MRTD can save much more memory. The optimal relative threshold fraction is about 0.01 % and large memory savings are attainable while maintaining reasonable accuracy. But the CPU runtimes are too long for the 0-0rder and 1st-Order MRTD with thresholding technique. Thus the tradeoff between computational efficiency and memory saving should be taken into consideration. An optimum procedure and well-designed data structures are necessary to ensure that memory requirements are kept at a minimum while maintaining computational efficiency at the same time.
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