GPU-accelerated computations of FDTD-compatible Green's function

We present results of an acceleration of the discrete Green's function (DGF) computations on a graphics processing unit (GPU). Recently, closed-form expression for the DGF was derived, which facilitates applications of this function in the finite-difference time-domain (FDTD) simulations. Howev...

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Bibliographic Details
Published in2013 7th European Conference on Antennas and Propagation (EuCAP) pp. 2643 - 2646
Main Authors Stefanski, T. P., Krzyzanowska, K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2013
Subjects
Central Processing Unit
Finite difference methods
finite-difference time-domain (FDTD) methods
Graphics processing units
Green's function methods
Libraries
parallel processing
Runtime
Time-domain analysis
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Summary:We present results of an acceleration of the discrete Green's function (DGF) computations on a graphics processing unit (GPU). Recently, closed-form expression for the DGF was derived, which facilitates applications of this function in the finite-difference time-domain (FDTD) simulations. However, the new DGF expression may cause long runtimes and accuracy problems. Therefore, we have proposed the DGF implementation on the GPU employing a multiple precision arithmetic library and the CUDA parallel programming interface. We have obtained six-fold speedup of the GPU implementation over a code executed on a multicore central processing unit. Achieved results indicate that GPUs represent an inexpensive source of computational power for the DGF computations.
ISBN:1467321877
9781467321877