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Fast Parallel FDFD Algorithm for Solving Electromagnetic Scattering Problems

Received: 25 November 2021     Accepted: 8 December 2021     Published: 24 December 2021
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Abstract

The finite difference frequency domain (FDFD) method is very suitable for working out narrowband problems and resonance problems. However, the FDFD method needs to solve a large complex sparse matrix equation. With the increase of computing scale, the dimension of matrix will increase rapidly, which is difficult to simulate. For improving the computational efficiency of solving the large complex sparse matrix equation and extend the application scope of the FDFD method, a fast parallel FDFD method on the basis of message passing interface (MPI) shared memory technology is proposed in this paper, which is used to solve the electromagnetic scattering problems of electrically large targets. Based on the conjugate gradient iterative algorithm, the large complex sparse matrix is reasonably distributed to each process according to the unequal row allocation scheme, so as to guarantee the load balancing of each process. In addition, the intermediate vectors utilized in total processes are stored in the shared memory of MPI, which reduces the communication time and the consumption of computer memory. The proposed parallel FDFD method is employed to solve the bistatic RCS of the PEC sphere, composite Von warhead and an automobile, compared with the serial FDFD method, the parallel FDFD method greatly improves the computational efficiency when the memory is not increased much.

Published in Journal of Electrical and Electronic Engineering (Volume 9, Issue 6)
DOI 10.11648/j.jeee.20210906.12
Page(s) 186-193
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

FDFD, Complex Sparse Matrix, Conjugate Gradient Iteration, MPI, Shared Memory

References
[1] K. S. Yee. Numerical solution of initial boundary value problems involving Maxwell's equations in isotropic media. IEEE Transactions on Antennas and Propagation, vol. 14, no. 3, pp. 302-307, May 1966.
[2] T. Namiki. A new FDTD algorithm based on alternating-direction implicit method. IEEE Transactions on Microwave Theory and Techniques, vol. 47, no. 10, pp. 2003-2007, Oct. 1999.
[3] T. An, M. Wei, S. Y. Li, et al. Study on the comparation of field-wire coupling effect for long wire in UWB with HEMP. Journal of Microwaves, vol. 26, no. 4, pp. 14-18, Apr. 2010.
[4] F. Xu, Y. L. Zhang, W. Hong, et al. Finite-difference frequency-domain algorithm for modeling guided-wave properties of substrate integrated waveguide. IEEE Transactions on Microwave Theory and Techniques, vol. 51, no. 11, pp. 2221-2227, Nov. 2003.
[5] A. G. Hanif, T. Arima, T. Uno. Finite-difference frequency-domain algorithm for band-diagram calculation of 2-D photonic crystals composed of Debye-type dispersive materials. IEEE Antennas and Wireless Propagation Letters, vol. 11, pp. 41-44, 2012.
[6] N. Neuss. A new sparse-matrix storage method for adaptively solving large systems of reaction-diffusion-transport equations. Computing, vol. 68, no. 1, pp. 19-36, Sep. 2001.
[7] D. A. H. Jacobs. A Generalization of the conjugate-gradient method to solve complex systems. IMA Journal of Numerical Analysis, vol. 6, no. 4, pp. 447-452, 1986.
[8] V. Demir, E. Alkan, A. Z. Elsherbeni, et al. An algorithm for efficient solution of finite-difference frequency-domain (FDFD) methods. IEEE Antennas and Propagation Magazine, vol. 51, no. 6, pp. 143-150, 2010.
[9] X. L. Li, B. Wei, X. B. He, et al. Parallel FDFD Algorithm Based on MPI and Its Application. 2020 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC), pp. 1-3, 2020.
[10] J. N. Hwang. A compact 2-D FDFD method for modeling microstrip structures with nonuniform grids and perfectly matched layer. IEEE Transactions on Microwave Theory and Techniques, vol. 53, no. 2, pp. 653-659, Feb. 2005.
[11] C. M. Rappaport, M. Kilmer, E. Miller. Accuracy considerations in using the PML ABC with FDFD Helmholtz equation computation. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, vol. 13, pp. 471-482, 2000.
[12] M. W. Chevalier, U. S. Inan. A technique for efficiently modeling long-path propagation for use in both FDFD and FDTD. IEEE Antennas and Wireless Propagation Letters, vol. 5, pp. 535-528, 2006.
[13] G. Zheng, B. Z. Wang. A hybrid MM-FDFD method for the analysis of waveguides with multiple discontinuities. IEEE Antennas and Wireless Propagation Letters, vol. 11, pp. 645-647, 2012.
[14] X. G. Xie, L. Wei, Ying L., et al. Using LU decomposition in FDFD for fast calculation of monostatic RCS, 2014 7th International Conference on Intelligent Computation Technology and Automation, pp. 887-889, 2014.
[15] K. Masumnia-Bisheh, K. Forooraghi, M. Ghaffari-Miab. Electromagnetic uncertainty analysis using stochastic FDFD method. IEEE Transactions on Antenna and Propagation, vol. 67, no. 5, pp. 3268-3277, May. 2019.
[16] X. Gu, X. L. Jin, J. X. Li, et al. Two-component compact 2-D FDFD method for waveguide structures with ARPACK. 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, pp. 187-188, 2019.
Cite This Article
  • APA Style

    Jianming Wu, Xinbo He, Bing Wei, Xianglin Li. (2021). Fast Parallel FDFD Algorithm for Solving Electromagnetic Scattering Problems. Journal of Electrical and Electronic Engineering, 9(6), 186-193. https://doi.org/10.11648/j.jeee.20210906.12

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    ACS Style

    Jianming Wu; Xinbo He; Bing Wei; Xianglin Li. Fast Parallel FDFD Algorithm for Solving Electromagnetic Scattering Problems. J. Electr. Electron. Eng. 2021, 9(6), 186-193. doi: 10.11648/j.jeee.20210906.12

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    AMA Style

    Jianming Wu, Xinbo He, Bing Wei, Xianglin Li. Fast Parallel FDFD Algorithm for Solving Electromagnetic Scattering Problems. J Electr Electron Eng. 2021;9(6):186-193. doi: 10.11648/j.jeee.20210906.12

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  • @article{10.11648/j.jeee.20210906.12,
      author = {Jianming Wu and Xinbo He and Bing Wei and Xianglin Li},
      title = {Fast Parallel FDFD Algorithm for Solving Electromagnetic Scattering Problems},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {9},
      number = {6},
      pages = {186-193},
      doi = {10.11648/j.jeee.20210906.12},
      url = {https://doi.org/10.11648/j.jeee.20210906.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20210906.12},
      abstract = {The finite difference frequency domain (FDFD) method is very suitable for working out narrowband problems and resonance problems. However, the FDFD method needs to solve a large complex sparse matrix equation. With the increase of computing scale, the dimension of matrix will increase rapidly, which is difficult to simulate. For improving the computational efficiency of solving the large complex sparse matrix equation and extend the application scope of the FDFD method, a fast parallel FDFD method on the basis of message passing interface (MPI) shared memory technology is proposed in this paper, which is used to solve the electromagnetic scattering problems of electrically large targets. Based on the conjugate gradient iterative algorithm, the large complex sparse matrix is reasonably distributed to each process according to the unequal row allocation scheme, so as to guarantee the load balancing of each process. In addition, the intermediate vectors utilized in total processes are stored in the shared memory of MPI, which reduces the communication time and the consumption of computer memory. The proposed parallel FDFD method is employed to solve the bistatic RCS of the PEC sphere, composite Von warhead and an automobile, compared with the serial FDFD method, the parallel FDFD method greatly improves the computational efficiency when the memory is not increased much.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Fast Parallel FDFD Algorithm for Solving Electromagnetic Scattering Problems
    AU  - Jianming Wu
    AU  - Xinbo He
    AU  - Bing Wei
    AU  - Xianglin Li
    Y1  - 2021/12/24
    PY  - 2021
    N1  - https://doi.org/10.11648/j.jeee.20210906.12
    DO  - 10.11648/j.jeee.20210906.12
    T2  - Journal of Electrical and Electronic Engineering
    JF  - Journal of Electrical and Electronic Engineering
    JO  - Journal of Electrical and Electronic Engineering
    SP  - 186
    EP  - 193
    PB  - Science Publishing Group
    SN  - 2329-1605
    UR  - https://doi.org/10.11648/j.jeee.20210906.12
    AB  - The finite difference frequency domain (FDFD) method is very suitable for working out narrowband problems and resonance problems. However, the FDFD method needs to solve a large complex sparse matrix equation. With the increase of computing scale, the dimension of matrix will increase rapidly, which is difficult to simulate. For improving the computational efficiency of solving the large complex sparse matrix equation and extend the application scope of the FDFD method, a fast parallel FDFD method on the basis of message passing interface (MPI) shared memory technology is proposed in this paper, which is used to solve the electromagnetic scattering problems of electrically large targets. Based on the conjugate gradient iterative algorithm, the large complex sparse matrix is reasonably distributed to each process according to the unequal row allocation scheme, so as to guarantee the load balancing of each process. In addition, the intermediate vectors utilized in total processes are stored in the shared memory of MPI, which reduces the communication time and the consumption of computer memory. The proposed parallel FDFD method is employed to solve the bistatic RCS of the PEC sphere, composite Von warhead and an automobile, compared with the serial FDFD method, the parallel FDFD method greatly improves the computational efficiency when the memory is not increased much.
    VL  - 9
    IS  - 6
    ER  - 

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Author Information
  • The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, China

  • School of Physics and Optoelectronic Engineering, Xidian University, Xi’an, China

  • School of Physics and Optoelectronic Engineering, Xidian University, Xi’an, China

  • School of Physics and Optoelectronic Engineering, Xidian University, Xi’an, China

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