posted on 2018-01-04, 10:57authored byPanagiotis Alevras, Daniil Yurchenko
The 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 & Structures
Volume
171
Pages
46 - 53
Citation
ALEVRAS, P. and YURCHENKO, D., 2016. GPU computing for accelerating the numerical Path Integration approach. Computers & Structures, 171, pp. 46-53.
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
2016-05-05
Publication date
2016
Notes
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.