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Comparison of CPML Implementations for the GPU-Accelerated FDTD Solver

J.I. Toivanen, T.P. Stefanski, N. Kuster, N. Chavannes
Department of Mathematical Information Technology, University of JyvAaskylAa, P. O. Box 35, FI-40014 University of JyvAaskylAa, Finland
Progress In Electromagnetics Research M, Vol. 19, 61-75, 2011

@article{toivanen2011comparison,

   title={Comparison of Cpml Implementations for the Gpu-Accelerated FDTD Solver},

   author={Toivanen, J.I. and Stefanski, T.P. and Kuster, N. and Chavannes, N.},

   journal={Progress In Electromagnetics Research},

   volume={19},

   pages={61–75},

   year={2011},

   publisher={EMW Publishing}

}

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Three distinctively different implementations of convolutional perfectly matched layer for the FDTD method on CUDA enabled graphics processing units are presented. All implementations store additional variables only inside the convolutional perfectly matched layers, and the computational speeds scale according to the thickness of these layers. The merits of the different approaches are discussed, and a comparison of computational performance is made using complex real-life benchmarks.
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