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Ying YAN Xunwang ZHAO Yu ZHANG Changhong LIANG Zhewang MA
In this paper, a novel hybrid technique for analyzing complex antennas around the coated object is proposed, which is termed as “iterative vector fields with Physical Optics (PO)”. A closed box is used to enclose the antennas and the complex field vectors on the box' surfaces can then be obtained using Huygens principle. The equivalent electromagnetic currents on Huygens surfaces are computed by Higher-order Method of Moments (HOB-MoM) and the fields scattered from the coated object are calculated by PO method. In addition, the parallel technique based on Message Passing Interface (MPI) and Scalable Linear Algebra Package (ScaLAPACK) is employed so as to accelerate the computation. Numerical examples are presented to validate and to show the effectiveness of the proposed method on solving the practical engineering problem.
Yan CHEN Yu ZHANG Guanghui ZHANG Xunwang ZHAO ShaoHua WU Qing ZHANG XiaoPeng YANG
In this paper, a Many Integrated Core Architecture (MIC) accelerated parallel method of moment (MoM) algorithm is proposed to solve electromagnetic problems in practical applications, where MIC means a kind of coprocessor or accelerator in computer systems which is used to accelerate the computation performed by Central Processing Unit (CPU). Three critical points are introduced in this paper in detail. The first one is the design of the parallel framework, which ensures that the algorithm can run on distributed memory platform with multiple nodes. The hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) programming model is designed to achieve the purposes. The second one is the out-of-core algorithm, which greatly breaks the restriction of MIC memory. The third one is the pipeline algorithm which overlaps the data movement with MIC computation. The pipeline algorithm successfully hides the communication and thus greatly enhances the performance of hybrid MIC/CPU MoM. Numerical result indicates that the proposed algorithm has good parallel efficiency and scalability, and twice faster performance when compared with the corresponding CPU algorithm.