@inproceedings{7dc84219bf7742859cd9693edf52b8bc,
title = "A GPU Acceleration Method for Direct Solutions of Electric Field Integral Equations",
abstract = "The method of moments (MoM) as a traditional numerical method has been widely recognized and used in solving electromagnetic integral equations. As the scale of solved problems increases, the computational costs will rise significantly, often preventing it from a direct use. This necessitates the integration of acceleration techniques by either software or hardware. The hardware acceleration is mainly achieved through the central processing unit (CPU) or graphics processing unit (GPU). This paper proposes a GPU acceleration method for the direct solution of electric field integral equations (EFIEs) by the method of moments (MoM). Numerical examples show that the proposed method can be approximately 10 times faster than the acceleration of a state-of-art multicore CPU with an OpenMP parallelism.",
author = "Lu, {Hao Zheng} and Liu, {Lu Yi} and Amir Boag and Tong, {Mei Song}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Symposium on Antennas and Propagation and INC/USNCURSI Radio Science Meeting, AP-S/INC-USNC-URSI 2024 ; Conference date: 14-07-2024 Through 19-07-2024",
year = "2024",
doi = "https://doi.org/10.1109/AP-S/INC-USNC-URSI52054.2024.10687258",
language = "الإنجليزيّة",
series = "IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2569--2570",
booktitle = "2024 IEEE International Symposium on Antennas and Propagation and INC/USNCURSI Radio Science Meeting, AP-S/INC-USNC-URSI 2024 - Proceedings",
address = "الولايات المتّحدة",
}