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GPU-ACCELERATED FUNDAMENTAL ADI-FDTD WITH COMPLEX FREQUENCY SHIFTED CONVOLUTIONAL PERFECTLY MATCHED LAYER

By W. C. Tay, D. Y. Heh, and E. L. Tan

Full Article PDF (247 KB)

Abstract:
This paper presents the graphics processing unit (GPU) accelerated fundamental alternating-direction-implicit finite-difference time-domain (FADI-FDTD) with complex frequency shifted convolutional perfectly matched layer (CFS-CPML). The compact matrix form of the conventional ADI-FDTD method with CFS-CPML is formulated into FADI-FDTD with its right-hand-sides free of matrix operators, resulting in simpler and more concise update equations. Using Compute Unified Device Architecture (CUDA), the FADI-FDTD with CFS-CPML is further incorporated into the GPU to exploit data parallelism. Numerical results show that a much higher efficiency gain of up to 15 times can be achieved.

Citation:
W. C. Tay, D. Y. Heh, and E. L. Tan, "Gpu-accelerated fundamental adi-FDTD with complex frequency shifted convolutional perfectly matched layer," Progress In Electromagnetics Research M, Vol. 14, 177-192, 2010.
doi:10.2528/PIERM10090605
http://www.jpier.org/pierm/pier.php?paper=10090605

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