000280436 001__ 280436 000280436 005__ 20210129221320.0 000280436 0247_ $$2doi$$a10.4203/ccp.107.5 000280436 037__ $$aFZJ-2016-00213 000280436 1001_ $$0P:(DE-HGF)0$$aTegeler, M.$$b0 000280436 1112_ $$aThe Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering$$cDubrovnik$$d2015-03-24 - 2015-03-27$$wCroatia 000280436 245__ $$aMassively Parallel Multiphase Field Simulations 000280436 260__ $$aStirlingshire, UK$$bCivil-Comp Press$$c2015 000280436 300__ $$aPaper 5 000280436 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1452521165_915 000280436 3367_ $$033$$2EndNote$$aConference Paper 000280436 3367_ $$2ORCID$$aCONFERENCE_PAPER 000280436 3367_ $$2DataCite$$aOutput Types/Conference Paper 000280436 3367_ $$2DRIVER$$aconferenceObject 000280436 3367_ $$2BibTeX$$aINPROCEEDINGS 000280436 520__ $$aThe phase field method is an established technique for investigation of microstructure evolution during materials processing. Large scale three-dimensional simulations including multiple phase fields and multiple components have high requirements for memory and computational power. In this paper we present a distributed-memory parallelization of the phase field library OpenPhase. We consider load imbalances that arise during phase field calculations and propose techniques to balance the computational load efficiently among the processors. We show benchmarks using thousands of processes and use the parallelized OpenPhase for a three-dimensional simulation, that was previously only viable in two dimensions. 000280436 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0 000280436 588__ $$aDataset connected to CrossRef Conference 000280436 7001_ $$0P:(DE-HGF)0$$aMonas, A.$$b1 000280436 7001_ $$0P:(DE-Juel1)132274$$aSutmann, G.$$b2$$ufzj 000280436 773__ $$a10.4203/ccp.107.5 000280436 909CO $$ooai:juser.fz-juelich.de:280436$$pVDB 000280436 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132274$$aForschungszentrum Jülich GmbH$$b2$$kFZJ 000280436 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x0 000280436 9141_ $$y2015 000280436 915__ $$0StatID:(DE-HGF)0550$$2StatID$$aNo Authors Fulltext 000280436 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0 000280436 980__ $$acontrib 000280436 980__ $$aVDB 000280436 980__ $$aUNRESTRICTED 000280436 980__ $$aI:(DE-Juel1)JSC-20090406