000202422 001__ 202422
000202422 005__ 20180913062741.0
000202422 0247_ $$2doi$$a10.1016/j.cma.2014.05.006
000202422 022__ $$a0045-7825
000202422 02470 $$2ISI$$a000340301200010
000202422 037__ $$aARTICLE
000202422 245__ $$aGPU accelerated computational homogenization based on a variational approach in a reduced basis framework
000202422 260__ $$aLausanne$$bElsevier$$c2014
000202422 269__ $$a2014
000202422 300__ $$a32
000202422 336__ $$aJournal Articles
000202422 520__ $$aComputational multiscale methods such as the FE2 technique (Feyel, 1999) come along with large demands in both CPU time and memory. In order to significantly reduce the computational cost of multiscale methods the authors recently proposed a hybrid computational homogenization method for visco-plastic materials using a reduced basis approach in a mixed variational formulation (Fritzen and Leuschner, 2013). In the present contribution two extensions of the method are introduced: First, the previous proposal is extended by allowing for heterogeneous hardening variables instead of piecewise constant fields. This leads to an improved accuracy of the method. Second, a massively parallel GPU implementation of the algorithm using Nvidia's CUDA framework is presented. The GPU subroutines for the batched linear algebraic operations are integrated into a specialized library in order to facilitate its use. The impact of the heterogeneous hardening states on the accuracy and the performance gains obtained from the dedicated GPU implementation are illustrated by means of numerical examples. An overall speedup in the order of 10(4) with respect to a high performance finite element implementation is achieved while preserving good accuracy of the predicted nonlinear material response. (C) 2014 Elsevier B.V. All rights reserved.
000202422 6531_ $$aNvidia CUDA
000202422 6531_ $$aGraphics processing unit (GPU)
000202422 6531_ $$aGPU accelerated batched BLAS
000202422 6531_ $$aReduced basis model order reduction
000202422 6531_ $$aGeneralized Standard Material (GSM)
000202422 6531_ $$aMixed incremental variational approach
000202422 700__ $$aFritzen, Felix$$uKarlsruhe Inst Technol KIT, Inst Engn Mech, Young Investigator Grp Comp Aided Mat Modeling, D-76131 Karlsruhe, Germany
000202422 700__ $$aHodapp, Max
000202422 700__ $$aLeuschner, Matthias$$uKarlsruhe Inst Technol KIT, Inst Engn Mech, Young Investigator Grp Comp Aided Mat Modeling, D-76131 Karlsruhe, Germany
000202422 773__ $$j278$$q186-217$$tComputer Methods In Applied Mechanics And Engineering
000202422 909C0 $$0252513$$pLAMMM$$xU12614
000202422 909CO $$ooai:infoscience.tind.io:202422$$pSTI$$particle
000202422 917Z8 $$x222139
000202422 937__ $$aEPFL-ARTICLE-202422
000202422 973__ $$aOTHER$$rREVIEWED$$sPUBLISHED
000202422 980__ $$aARTICLE