基于GPU加速FDTD算法的掠入射下一维大尺度粗糙面电磁散射研究.doc

文档介绍：
基于 GPU 加速 FDTD 算法的掠入射下一维
大尺度粗糙面电磁散射研究#
贾春刚,郭立新,李娟*
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(西安电子科技大学物理与光电工程学院,西安 710071)
摘要: 本文基于硬件平台 GPU(Graphic Processor Unit)加速时域有限差分方法(Finite
Difference Time Domain Method,FDTD),即 GPU-based FDTD 方法,研究了一维大尺度指
数随机粗糙面掠入射下的电磁散射问题,利用共享存储器(Shared Memory)和纹理存储器
(Texture Memory)对并行算法进行优化,进而得到了很好的加速比,并通过与传统串行算法
进行比较,证明了该方法的准确性。进一步分析并讨论了入射角、均方根高度以及相关长度
对后向散射的影响。结果表明,与传统串行 FDTD 算法相比,GPU-based FDTD 算法在解决
大尺度粗糙面电磁散射问题时具有很大的优越性。
关键词:电磁散射;并行 FDTD;掠入射;随机粗糙面;GPU
中图分类号:TN011
GPU accelerated FDTD method for investigation on the
ic scattering from 1-D large scale rough soil
surface under low grazing incidence
Jia Chungang, Guo Lixin, Li Juan
(School of Physics and Optoelectronic Engineering, Xidian University, Xi’an, China (710071))
Abstract: In this paper, the graphic processor unit (GPU) implementation of the finite-difference time
domain (FDTD) algorithm is presented to investigate the ic (EM) scattering from one
dimensional (1-D) large scale exponential rough soil surface with low grazing incident angle. The
FDTD lattices are truncated by uniaxial perfectly matched layer (UPML), in which the finite-difference
equations are carried out for the putation domain. pute Unified Device
Architecture (CUDA) technology, significant speedup ratios are achieved for different incident
frequencies, which demonstrates the efficiency of GPU accelerated t