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Maxwellu0027s 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 Maxwellu0027s equations. The FDTD (Finite-diference Time-Domain) method, proposed by K. Yee, is widely used to solve Maxwellu0027s 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.

Melhorando o desempenho computacional de um esquema de diferenças finitas para as equações de Maxwell