Implementation of numerical integration to high-order elements on the GPUs
Authors:
- Filip Krużel,
- Krzysztof Banaś,
- Mateusz Nytko
Abstract
This article presents ways to implement a resource-consuming algorithm on hardware witha limited amount of memory, which is the GPU. Numerical integration for higher-orderfinite element approximation was chosen as an example algorithm. To perform compu-tational tests, we use a non-linear geometric element and solve the convection-diffusion-reaction problem. For calculations, a Tesla K20m graphics card based on Kepler archi-tecture and Radeon r9 280X based on Tahiti XT architecture were used. The resultsof computational experiments were compared with the theoretical performance of bothGPUs, which allowed an assessment of actual performance. Our research gives sugges-tions for choosing the optimal design of algorithms as well as the right hardware for sucha resource-demanding task.
- Record ID
- CUT68e25e5357574cfcac9d17b6c7c39cb7
- Publication categories
- ;
- Author
- Journal series
- Computer Assisted Methods in Engineering and Science, ISSN 2299-3649
- Issue year
- 2020
- Vol
- 27
- No
- 1
- Pages
- 3-26
- Other elements of collation
- fot.; schem.; tab.; wykr.; Bibliografia (na s.) - 24-26; Bibliografia (liczba pozycji) - 22; Oznaczenie streszczenia - Streszcz. ang.; Numeracja w czasopiśmie - Vol. 27, No. 1
- Keywords in English
- GPU, numerical integration, finite element method, OpenCL, CUDA
- DOI
- DOI:10.24423/cames.264 Opening in a new tab
- URL
- https://cames.ippt.pan.pl/index.php/cames/article/view/264 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 70
- Additional fields
- Indeksowana w: Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT68e25e5357574cfcac9d17b6c7c39cb7/
- URN
urn:pkr-prod:CUT68e25e5357574cfcac9d17b6c7c39cb7
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.