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GPU-Accelerated Finite-Element Matrix Generation for Lossless, Lossy, and Tensor Media [EM Programmer's Notebook]
Abstract
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.
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
IEEE ANTENNAS AND PROPAGATION MAGAZINE
no. 56,
pages 186 - 197,
ISSN: 1045-9243 - Language:
- English
- Publication year:
- 2014
- Bibliographic description:
- Dziekoński A., Sypek P., Lamęcki A., Mrozowski M.: GPU-Accelerated Finite-Element Matrix Generation for Lossless, Lossy, and Tensor Media [EM Programmer's Notebook]// IEEE ANTENNAS AND PROPAGATION MAGAZINE. -Vol. 56, nr. 5 (2014), s.186-197
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/map.2014.6971943
- Verified by:
- Gdańsk University of Technology
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