Abstract
Maxwell's equations play a crucial role in electromagnetic theory and applications. However, it is not always possible to solve these equations analytically. Consequently, we have to use numerical methods in order to get approximate solutions of the Maxwell's equations. The FDTD (Finite-diference Time-Domain) method, proposed by K. Yee, is widely used to solve Maxwell's equations, due to its efficiency and simplicity. However, this method has a high computational cost. In this paper, we propose a parallel implementation of the FDTD method to run on GPUs by using CUDA platform. Our goal is to reduce the processing time required, allowing the use of the FDTD method in the simulation of electromagnetic wave propagation. We evaluate the proposed algorithm considering two different kind of boundary conditions: a Dirichlet type boundary conditions and absorbing boundary conditions. We get a performance gain ranging from 7 to 8 times when comparing the proposed parallel implementation with an optimized sequential version.
Highlights
Implementamos duas versoes do algoritmo, uma usando condicoes de contorno de Dirichlet, e outra usando condicoes de contorno absorventes [3]
Nos referimos a essas condicoes de contorno como condicoes de contorno de tipo Dirichlet
Assim como nas versoes sequenciais, implementamos duas versoes do algoritmo paralelo, uma usando condicoes de contorno especıficas e outra usando PML
Summary
A energia gerada por fontes eletromagneticas e suas interacoes com o entorno possuem muitas aplicacoes, entre as quais podemos citar as tecnologias de comunicacao sem fio e alguns tratamentos e diagnosticos usados na area medica [7, 8, 16]. O desenvolvimento e aprimoramento dessas aplicacoes requerem um estudo detalhado sobre a interacao do campo eletromagnetico e a propagacao de ondas eletromagneticas na regiao de interesse. Esse estudo toma como base as equacoes de Maxwell, um sistema de equacoes em derivadas parciais que descreve a evolucao no tempo do campo eletromagnetico
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