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GPU computing for accelerating the numerical Path Integration approach

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journal contribution
posted on 04.01.2018, 10:57 by Panagiotis 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.

Publisher

© Elsevier

Version

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

05/05/2016

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.

ISSN

0045-7949

Language

en

Exports