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One-Way and Fully-Coupled FE2 Methods for Heterogeneous Elasticity and Plasticity Problems: Parallel Scalability and an Application to Thermo-Elastoplasticity of Dual-Phase Steels.

D. Balzani, A. Gandhi, A. Klawonn, M. Lanser, O. Rheinbach, and J. Schröder. Software for Exascale Computing, volume 113 of Lecture Notes in Computational Science and Engineering, Springer, (2016)

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Martin Baumann

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Nonlinear FETI-DP and BDDC Methods.A. Klawonn, M. Lanser, and O. Rheinbach. SIAM J. Scientific Computing, (2014)Scalability of Classical Algebraic Multigrid for Elasticity to Half a Million Parallel Tasks.A. Baker, A. Klawonn, T. Kolev, M. Lanser, O. Rheinbach, and U. Yang. Software for Exascale Computing, volume 113 of Lecture Notes in Computational Science and Engineering, Springer, (2016)Nonlinear FETI-DP and BDDC Methods: A Unified Framework and Parallel Results.A. Klawonn, M. Lanser, O. Rheinbach, and M. Uran. SIAM J. Scientific Computing, (2017)A Highly Scalable Implementation of Inexact Nonlinear FETI-DP Without Sparse Direct Solvers.A. Klawonn, M. Lanser, and O. Rheinbach. ENUMATH, volume 112 of Lecture Notes in Computational Science and Engineering, page 255-264. Springer, (2015)Toward Extremely Scalable Nonlinear Domain Decomposition Methods for Elliptic Partial Differential Equations.A. Klawonn, M. Lanser, and O. Rheinbach. SIAM J. Scientific Computing, (2015)FE2TI: Computational Scale Bridging for Dual-Phase Steels.A. Klawonn, M. Lanser, and O. Rheinbach. PARCO, volume 27 of Advances in Parallel Computing, page 797-806. IOS Press, (2015)Multicore Performance Engineering of Sparse Triangular Solves Using a Modified Roofline Model.M. Wittmann, G. Hager, R. Janalík, M. Lanser, A. Klawonn, O. Rheinbach, O. Schenk, and G. Wellein. SBAC-PAD, page 233-241. IEEE, (2018)One-Way and Fully-Coupled FE2 Methods for Heterogeneous Elasticity and Plasticity Problems: Parallel Scalability and an Application to Thermo-Elastoplasticity of Dual-Phase Steels.D. Balzani, A. Gandhi, A. Klawonn, M. Lanser, O. Rheinbach, and J. Schröder. Software for Exascale Computing, volume 113 of Lecture Notes in Computational Science and Engineering, Springer, (2016)Machine Learning in Adaptive Domain Decomposition Methods - Predicting the Geometric Location of Constraints.A. Heinlein, A. Klawonn, M. Lanser, and J. Weber. SIAM J. Scientific Computing, 41 (6): A3887-A3912 (2019)