Bio‐inspired optimization for electromagnetic structure design using full‐wave techniques on GPUs

SUMMARY The electromagnetic modeling of antennas and radio frequency devices has become increasingly challenging as the applications demand intricate and complex designs, such as fine features embedded in electrically large structures or integrated systems (e.g., antennas on vehicles). Often the design stage is further challenged by the need to find an optimal solution, which results in a numerically intensive problem. The objective of this paper is to investigate the use of graphics processing units (GPUs) in such challenging design and optimizations. Two full-wave approaches (method of moments and rigorous coupled wave analysis) are discussed along with a bio-inspired optimization technique, namely the particle swarm optimization. The inherent parallel nature of the GPUs is utilized in implementing the most numerically intensive parts of these full-wave methods. Furthermore, the independent search mechanism employed by the particle swarm optimization in its agent-based search renders itself to parallelism offered by GPUs. The paper demonstrates the acceleration achieved by the GPUs in designing a variety of radio frequency structures such as reconfigurable patch antennas and antireflective surfaces. Copyright © 2013 John Wiley & Sons, Ltd.

[1]  Atef Z. Elsherbeni,et al.  Optimization and parameter exploration using GPU based FDTD solvers , 2008, 2008 IEEE MTT-S International Microwave Symposium Digest.

[2]  John L. Volakis,et al.  Electromagnetics: computational methods and considerations , 1995 .

[3]  Hao Wang,et al.  Introduction to Genetic Algorithms in Electromagnetics , 1995 .

[4]  Yahya Rahmat-Samii,et al.  Micro-actuated pixel patch antenna design using particle swarm optimization , 2011, 2011 IEEE International Symposium on Antennas and Propagation (APSURSI).

[5]  K. Yee.  Numerical solution of initial boundary value problems involving maxwell's equations in isotropic media , 1966 .

[6]  Steve Mann,et al.  Computer vision signal processing on graphics processing units , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[7]  Vinh Dang,et al.  Hardware accelerated computing for electromagnetics applications , 2011, CEM'11 Computational Electromagnetics International Workshop.

[8]  T. Gaylord,et al.  Rigorous coupled-wave analysis of planar-grating diffraction , 1981 .

[9]  L M Bernardo,et al.  Antireflection structures with use of multilevel subwavelength zero-order gratings. , 1997, Applied optics.

[10]  Renato A. Krohling,et al.  Swarm's flight: Accelerating the particles using C-CUDA , 2009, 2009 IEEE Congress on Evolutionary Computation.

[11]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[12]  Miguel A. Vega-Rodríguez,et al.  Accelerating Particle Swarm Algorithm with GPGPU , 2011, 2011 19th International Euromicro Conference on Parallel, Distributed and Network-Based Processing.

[13]  Thomas K. Gaylord,et al.  Rigorous coupled-wave analysis of metallic surface-relief gratings , 1986 .

[14]  E. K. Miller,et al.  A selective survey of computational electromagnetics , 1988 .

[15]  Vikram K. Narayana,et al.  GPU Resource Sharing and Virtualization on High Performance Computing Systems , 2011, 2011 International Conference on Parallel Processing.

[16]  J. Fung,et al.  Using multiple graphics cards as a general purpose parallel computer: applications to computer vision , 2004, ICPR 2004.

[17]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[18]  Mir Mojtaba Mirsalehi,et al.  Comparison of antireflection surfaces based on two-dimensional binary gratings and thin-film coatings. , 2005, Applied optics.

[19]  B. Party.  Name of Candidate , 2016 .

[20]  Y. Rahmat-Samii,et al.  Particle swarm optimization in electromagnetics , 2004, IEEE Transactions on Antennas and Propagation.

[21]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[22]  J N Mait,et al.  Broadband Antireflective Properties of Inverse Motheye Surfaces , 2010, IEEE Transactions on Antennas and Propagation.

[23]  S.H. Zainud-Deen,et al.  A Hybrid Finite Difference Frequency Domain and Particle Swarm Optimization Techniques for Forward and Inverse Electromagnetic Scattering Problems , 2007, 2007 National Radio Science Conference.

[24]  John E. Stone,et al.  GPU clusters for high-performance computing , 2009, 2009 IEEE International Conference on Cluster Computing and Workshops.

[25]  Steve Mann,et al.  Mediated reality using computer graphics hardware for computer vision , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[26]  Danilo De Donno,et al.  Parallel efficient method of moments exploiting graphics processing units , 2010 .

[27]  Z. Nie,et al.  Acceleration of the Method of Moments Calculations by Using Graphics Processing Units , 2008, IEEE Transactions on Antennas and Propagation.

[28]  D. Wilton,et al.  Electromagnetic scattering by surfaces of arbitrary shape , 1980 .

[29]  S. M. Rao.  Electromagnetic scattering and radiation of arbitrarily shaped surfaces by triangular patch modeling , 1980 .

[30]  Thomas K. Gaylord,et al.  Stable implementation of the rigorous coupled-wave analysis for surface-relief gratings: enhanced transmittance matrix approach , 1995 .

[31]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[32]  Russell C. Eberhart,et al.  Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.

[33]  Lifeng Li,et al.  New formulation of the Fourier modal method for crossed surface-relief gratings , 1997 .

[34]  Y. Rahmat-Samii,et al.  Advances in Particle Swarm Optimization for Antenna Designs: Real-Number, Binary, Single-Objective and Multiobjective Implementations , 2007, IEEE Transactions on Antennas and Propagation.

[35]  Allen W. Glisson,et al.  A simple numerical solution procedure for statics problems involving arbitrary-shaped surfaces , 1979 .

[36]  O. Bryngdahl,et al.  Design of antireflection gratings with approximate and rigorous methods. , 1994, Applied optics.

[37]  Tomasz Topa,et al.  Adapting MoM With RWG Basis Functions to GPU Technology Using CUDA , 2011, IEEE Antennas and Wireless Propagation Letters.

[38]  T. Gaylord,et al.  Three-dimensional vector coupled-wave analysis of planar-grating diffraction , 1983 .

[39]  Fabio Daolio,et al.  Evaluation of parallel particle swarm optimization algorithms within the CUDA™ architecture , 2011, Inf. Sci..

[40]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[41]  Frederica Darema,et al.  The SPMD Model : Past, Present and Future , 2001, PVM/MPI.

[42]  Philippe Lalanne,et al.  Improved formulation of the coupled-wave method for two-dimensional gratings , 1997 .

[43]  Steve Mann,et al.  An EyeTap video-based featureless projective motion estimation assisted by gyroscopic tracking for wearable computer mediated reality , 2003, Personal and Ubiquitous Computing.

[44]  Mark S. Mirotznik,et al.  Bio-inspired optimization techniques for the design of millimeter wave antireflective surfaces , 2010, EuCAP 2010.

[45]  Eric J. Kelmelis,et al.  CULA: hybrid GPU accelerated linear algebra routines , 2010, Defense + Commercial Sensing.

[46]  Ying Tan,et al.  GPU-based parallel particle swarm optimization , 2009, 2009 IEEE Congress on Evolutionary Computation.

[47]  E Lezar,et al.  GPU-Accelerated Method of Moments by Example: Monostatic Scattering , 2010, IEEE Antennas and Propagation Magazine.