AutoMat: automatic differentiation for generalized standard materials on GPUs

  • We propose a universal method for the evaluation of generalized standard materials that greatly simplifies the material law implementation process. By means of automatic differentiation and a numerical integration scheme, AutoMat reduces the implementation effort to two potential functions. By moving AutoMat to the GPU, we close the performance gap to conventional evaluation routines and demonstrate in detail that the expression level reverse mode of automatic differentiation as well as its extension to second order derivatives can be applied inside CUDA kernels. We underline the effectiveness and the applicability of AutoMat by integrating it into the FFT-based homogenization scheme of Moulinec and Suquet and discuss the benefits of using AutoMat with respect to runtime and solution accuracy for an elasto-viscoplastic example.

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Metadaten
Author:Johannes BlühdornORCiD, Nicolas R. GaugerORCiD, Matthias KabelORCiD
URN:urn:nbn:de:hbz:386-kluedo-78182
DOI:https://doi.org/10.1007/s00466-021-02105-2
ISSN:1432-0924
Parent Title (English):Computational Mechanics
Publisher:Springer Nature - Springer
Document Type:Article
Language of publication:English
Date of Publication (online):2024/03/15
Year of first Publication:2021
Publishing Institution:Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
Date of the Publication (Server):2024/03/15
Issue:69
Page Number:25
First Page:589
Last Page:613
Source:https://link.springer.com/article/10.1007/s00466-021-02105-2
Faculties / Organisational entities:Kaiserslautern - Fachbereich Informatik
DDC-Cassification:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Collections:Open-Access-Publikationsfonds
Licence (German):Zweitveröffentlichung