5351

Acceleration of TM cylinder EFIE with CUDA

Tyler Killian, Daniel L. Faircloth, Sadasiva M. Rao
Dept. of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
IEEE Antennas and Propagation Society International Symposium, 2009. APSURSI ’09
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In this paper, we have shown that exploitation of the GPU’s massively parallel architecture can dramatically increase the speed of MoM calculations. While the code can certainly be improved, matrix fill speed-up factors are already commonly found to be between 150X-260X. The conjugate gradient solver stands to be improved at this writing but still results in performance increases of 1.25X-20X. Continued development of MoM codes with GPU acceleration will undoubtedly bring about a new era of computational electromagnetics.
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