GPU-Accelerated Finite-Element Matrix Generation for Lossless, Lossy, and Tensor Media [EM Programmer´s Notebook]

This paper presents an optimization approach for limiting memory requirements and enhancing the performance of GPU-accelerated finite-element matrix generation applied in the implementation of the higher-order finite-element method (FEM). It emphasizes the details of the implementation of the matrix-generation algorithm for the simulation of electromagnetic wave propagation in lossless, lossy, and tensor media. Moreover, the impact of GPU RAM memory requirements on the performance of the finite-element matrix-generation process is discussed. The numerical results were obtained using a workstation equipped with a Tesla K40 GPU and two Intel Xeon Sandy Bridge E5-2687W CPUs. The results obtained for the high-end test platform indicated that the utilization of a GPU in the finite-element matrix-generation process allowed significant time reduction. With double-precision arithmetic, the GPU-accelerated matrix generation of over 5 million unknowns could be carried out in a matter of tens of seconds, as opposed to a CPU that required several minutes.