@inproceedings{d94b2c5fff244408a4ed22ca05f164f5,
title = "Acceleration of the finite element method using hybrid OpenMP-CUDA",
abstract = "Graphics processing units (GPUs) are efficient in accelerating algorithms that are highly parallelizable. This paper discusses various aspects of parallelizing the traditional finite element algorithm, whose communication-intensive nature makes it difficult to be parallelized in a straightforward manner, and proposes solutions to alleviate the acceleration bottlenecks. The examples show that decent speedup can still be achieved over OpenMP-enabled CPUs.",
author = "Meng, {Huan Ting} and Nie, {Bao Lin} and Jin, {Jian Ming} and Steven Wong and Charles Macon",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Antennas and Propagation Society International Symposium, APSURSI 2014 ; Conference date: 06-07-2014 Through 11-07-2014",
year = "2014",
month = sep,
day = "18",
doi = "10.1109/APS.2014.6905015",
language = "English (US)",
series = "IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1379--1380",
booktitle = "2014 IEEE Antennas and Propagation Society International Symposium(APSURSI)",
address = "United States",
}