Open-Source Software for Electromagnetic Scattering Simulation: The Case of Antenna Design

Electromagnetic scattering simulation is an extremely wide and interesting field, and its continuous evolution is associated with the development of computing resources. Undeniably, antenna design at all levels strongly relies on electromagnetic simulation software. However, despite the large number and the high quality of the available open-source simulation packages, most companies have no doubts about the choice of commercial program suites. At the same time, in the academic world, it is frequent to develop in-house simulation software, even from scratch and without proper knowledge of the existing possibilities. The rationale of the present paper is to review, from a practical viewpoint, the open-source software that can be useful in the antenna design process. To this end, an introductory overview of the usual design workflow is firstly presented. Subsequently, the strengths and weaknesses of open-source software compared to its commercial counterpart are analyzed. After that, the main open-source packages that are currently available online are briefly described. The last part of this paper is devoted to a preliminary numerical benchmark for the assessment of the capabilities and limitations of a subset of the presented open-source programs. The benchmark includes the calculation of some fundamental antenna parameters for four different typologies of radiating elements

Review on Computational Electromagnetics

Computational electromagnetics (CEM) is applied to model the interaction of electromagnetic fields with the objects like antenna, waveguides, aircraft and their environment using Maxwell equations.  In this paper the strength and weakness of various computational electromagnetic techniques are discussed. Performance of various techniques in terms accuracy, memory and computational time for application specific tasks such as modeling RCS (Radar cross section), space applications, thin wires, antenna arrays are presented in this paper

Accelerating the Performance of a Novel Meshless Method Based on Collocation With Radial Basis Functions By Employing a Graphical Processing Unit as a Parallel Coprocessor

In recent times, a variety of industries, applications and numerical methods including the meshless method have enjoyed a great deal of success by utilizing the graphical processing unit (GPU) as a parallel coprocessor. These benefits often include performance improvement over the previous implementations. Furthermore, applications running on graphics processors enjoy superior performance per dollar and performance per watt than implementations built exclusively on traditional central processing technologies. The GPU was originally designed for graphics acceleration but the modern GPU, known as the General Purpose Graphical Processing Unit (GPGPU) can be used for scientific and engineering calculations. The GPGPU consists of massively parallel array of integer and floating point processors. There are typically hundreds of processors per graphics card with dedicated high-speed memory. This work describes an application written by the author, titled GaussianRBF to show the implementation and results of a novel meshless method that in-cooperates the collocation of the Gaussian radial basis function by utilizing the GPU as a parallel co-processor. Key phases of the proposed meshless method have been executed on the GPU using the NVIDIA CUDA software development kit. Especially, the matrix fill and solution phases have been carried out on the GPU, along with some post processing. This approach resulted in a decreased processing time compared to similar algorithm implemented on the CPU while maintaining the same accuracy

Uso de arquitecturas MIC para la aceleración de soluciones numéricas en electromagnetismo

La mejora en la eficiencia de recursos computacionales para la resolución de problemas electromagnéticos es un tema complejo y de gran interés. La aparición en la última década de GPUs y tarjetas coprocesadoras Xeon Phi en las listas de los supercomputadores con mayor rendimiento, ha llevado a los investigadores a tratar de sacar el máximo provecho de estas nuevas tecnologías. El objetivo principal de esta Tesis es mejorar la eficiencia del método MoM (Method of Moments) mediante la paralelización de algunos de sus algoritmos en procesadores con arquitectura Intel MIC (Many Integrated Core). Para ello, se realiza el modelado de un problema electromagnético mediante la metodología SIE-MoM (Surface Integral Equation-Method of Moments), y se desarrollan nuevos algoritmos para su ejecución en tarjetas coprocesadoras Intel Xeon Phi. Los resultados obtenidos tras evaluar los tiempos de computación comparativamente entre las tarjetas Intel Xeon Phi y las CPUs Intel Xeon, indican que la arquitectura Intel MIC podría resultar adecuada en simulaciones electromagnéticas como complemento a CPUs.Improving the efficiency of computational resources for solving electromagnetic problems is a complex subject of great interest. The growth of GPUs (Graphics Processing Unit) and Xeon Phi coprocessor boards on the lists of top-performing supercomputers over the past decade has led researchers to try to make the most of these new technologies. The main objective of this Thesis is to improve the efficiency of the MoM method by parallelizing some of its algorithms on processors with Intel MIC (Many Integrated Core) architecture. For this purpose, the modeling of an electromagnetic problem is carried out using the SIE-MoM (Surface Integral Equation-Method of Moments) methodology, and new algorithms are developed for their execution on Intel Xeon Phi coprocessor cards. The results obtained after evaluating computation time compared between Intel Xeon Phi cards and Intel Xeon CPUs, indicate that the Intel MIC architecture could be suitable in electromagnetic simulations as a complement to CPUs

Investigation of general-purpose computing on graphics processing units and its application to the finite element analysis of electromagnetic problems

In this dissertation, the hardware and API architectures of GPUs are investigated, and the corresponding acceleration techniques are applied on the traditional frequency domain finite element method (FEM), the element-level time-domain methods, and the nonlinear discontinuous Galerkin method. First, the assembly and the solution phases of the FEM are parallelized and mapped onto the granular GPU processors. Efficient parallelization strategies for the finite element matrix assembly on a single GPU and on multiple GPUs are proposed. The parallelization strategies for the finite element matrix solution, in conjunction with parallelizable preconditioners are investigated to reduce the total solution time. Second, the element-level dual-field domain decomposition (DFDD-ELD) method is parallelized on GPU. The element-level algorithms treat each finite element as a subdomain, where the elements march the fields in time by exchanging fields and fluxes on the element boundary interfaces with the neighboring elements. The proposed parallelization framework is readily applicable to similar element-level algorithms, where the application to the discontinuous Galerkin time-domain (DGTD) methods show good acceleration results. Third, the element-level parallelization framework is further adapted to the acceleration of nonlinear DGTD algorithm, which has potential applications in the field of optics. The proposed nonlinear DGTD algorithm describes the third-order instantaneous nonlinear effect between the electromagnetic field and the medium permittivity. The Newton-Raphson method is incorporated to reduce the number of nonlinear iterations through its quadratic convergence. Various nonlinear examples are presented to show the different Kerr effects observed through the third-order nonlinearity. With the acceleration using MPI+GPU under large cluster environments, the solution times for the various linear and nonlinear examples are significantly reduced

Parallel algorithms for microstrip antennas modeling by the method of moments

Microstrip antény (MA) jsou široce používány jako součást různých zařízení pro mobilní komunikační systémy: fázované antény, základnové stanice s odvětvovými radiačními vzory, příjem vesmírné rozmanitosti atd. Pro výpočet charakteristik (MA) jsou vyžadovány silné výpočetní algoritmy. V práci se zabýváme problematikou rovinné elektromagnetické vlnové difrakce tenkou kovovou deskou, což je speciální případ vyzařujícího prvku mikropáskové antény. Je navržena paralelní implementace numerického řešení pomocí technologie CUDA.Microstrip antennas (MA) are widely used as component in various devices for mobile communication systems: phased antenna arrays, base stations with sectorial radiation patterns, space-diversity reception, etc. Powerful computational algorithms are required to calculate the characteristics of (MA). In thesis we consider the problem of plane electromagnetic wave diffraction by a thin metal plate, which is a special case of the radiating element of a microstrip antenna. Parallel implementation of the numerical solving via CUDA technology is proposed

Bio-Inspired Optimization of Ultra-Wideband Patch Antennas Using Graphics Processing Unit Acceleration

Ultra-wideband (UWB) wireless systems have recently gained considerable attention as effective communications platforms with the properties of low power and high data rates. Applications of UWB such as wireless USB put size constraints on the antenna, however, which can be very dicult to meet using typical narrow band antenna designs. The aim of this thesis is to show how bio-inspired evolutionary optimization algorithms, in particular genetic algorithm (GA), particle swarm optimization (PSO) and biogeography-based optimization (BBO) can produce novel UWB planar patch antenna designs that meet a size constraint of a 10 mm 10 mm patch. Each potential antenna design is evaluated with the nite dierence time domain (FDTD) technique, which is accurate but time-consuming. Another aspect of this thesis is the modication of FDTD to run on a graphics processing unit (GPU) to obtain nearly a 20 speedup. With the combination of GA, PSO, BBO and GPU-accelerated FDTD, three novel antenna designs are produced that meet the size and bandwidth requirements applicable to UWB wireless USB system