High performance 2D and 3D FDTD solvers on GPUs
John R. Humphrey, Daniel K. Price, James P. Durbano, Eric J. Kelmelis, Richard D. Martin
Abstract
John R. Humphrey, Daniel K. Price, James P. Durbano, Eric J. Kelmelis, Richard D. Martin
Abstract
Abstract:- Our group has employed the use of modern graphics processor units (GPUs) for the acceleration of finite-difference based computational electromagnetics (CEM) codes. In particular, we accelerated the well-known Finite-Difference Time-Domain (FDTD) method, which is commonly used for the analysis of electromagnetic phenomena. This algorithm uses difference-based approximations for Maxwell’s Equations to simulate the propagation of electromagnetic fields through space and materials. The method is very general and is applicable to a wide array of problems, but runtimes are long enough that acceleration is highly desired. In this paper we present GPU-based accelerated solvers for the FDTD method in both its 2D and 3D embodiments.
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Abstract:- Our group has employed the use of modern graphics processor units (GPUs) for the acceleration of finite-difference based computational electromagnetics (CEM) codes. In particular, we accelerated the well-known Finite-Difference Time-Domain (FDTD) method, which is commonly used for the analysis of electromagnetic phenomena. This algorithm uses difference-based approximations for Maxwell’s Equations to simulate the propagation of electromagnetic fields through space and materials. The method is very general and is applicable to a wide array of problems, but runtimes are long enough that acceleration is highly desired. In this paper we present GPU-based accelerated solvers for the FDTD method in both its 2D and 3D embodiments.
Key concepts: Finite-difference time-domain method, Acceleration, Computational electromagnetics, Computational science, Computer science, Finite difference method, Electromagnetics, Graphics