PI_GPU_v_accepted.pdf (1.65 MB)
GPU computing for accelerating the numerical Path Integration approach
journal contribution
posted on 2018-01-04, 10:57 authored by Panagiotis Alevras, Daniil YurchenkoThe paper discusses a novel approach of accelerating the numerical Path Integration method, used for generating a stationary joint response probability density function of a dynamic system subjected to a random excitation, by the GPU computing. The paper proposes the parallelization of nested loops technique and demonstrates the advantages of GPU computing. Two, three and four dimensional in space problems are investigated as a part of the pilot project and the achieved maximum accelerations are reported. Three degree-of-freedom system (6D) is approached by the Path Integration technique for the first time. The application of the proposed GPU methodology for problems of stochastic dynamics and reliability are discussed.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
Computers & StructuresVolume
171Pages
46 - 53Citation
ALEVRAS, P. and YURCHENKO, D., 2016. GPU computing for accelerating the numerical Path Integration approach. Computers & Structures, 171, pp. 46-53.Publisher
© ElsevierVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2016-05-05Publication date
2016Notes
This paper was published in the journal Computers & Structures and the definitive published version is available at https://doi.org/10.1016/j.compstruc.2016.05.002.ISSN
0045-7949Publisher version
Language
- en