Simulations of light scattering from nano-structured surface areas require substantial amount of computing time. The emergence of General Purpose Graphics Processing Units (GPGPUs) as affordable PC SIMD arithmetic coprocessors brings the necessary computing power to modern desktop PCs. In this paper we examine how the computation time of the Finite-Difference Time-Domain (FDTD), a classic numerical method for computing a solution to Maxwell's equations, can be reduced by leveraging the massively parallel architecture of GPGPUs cards. 2008 11th IEEE International Conference on Computational Science and Engineering 978-0-7695-3193-9/08 $25.00
Modern massively parallel graphics cards (GPGPUs) offer a promise of dramatically reducing computation times of numerically-intensive dataparallel algorithms. As cards that are easily integrated into desktop PCs, they can bring computational power previously reserved for computer clusters to the office space. High performance rates make GPGPUs a very attractive target platform for scientific simulations. In this paper we present the lessons learned during the parallelization of a finite-difference time-domain method, an inherently data-parallel algorithm frequently used for numerical computations, on the state of the art graphics hardware.
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