Volume 53, pp. 562-591, 2020.

A frugal FETI-DP and BDDC coarse space for heterogeneous problems

Alexander Heinlein, Axel Klawonn, Martin Lanser, and Janine Weber

Abstract

The convergence rate of domain decomposition methods is generally determined by the eigenvalues of the preconditioned system. For second-order elliptic partial differential equations, coefficient discontinuities with a large contrast can lead to a deterioration of the convergence rate. Only by implementing an appropriate coarse space, or second level, a robust domain decomposition method can be obtained. In this article, a new frugal coarse space for FETI-DP (Finite Element Tearing and Interconnecting-Dual Primal) and BDDC (Balancing Domain Decomposition by Constraints) methods is presented, which has a lower set-up cost than competing adaptive coarse spaces. In particular, in contrast to adaptive coarse spaces, it does not require the solution of any local generalized eigenvalue problems. The approach considered here aims at a low-dimensional approximation of the adaptive coarse space by using appropriate weighted averages, and it is robust for a broad range of coefficient distributions for diffusion and elasticity problems. However, in general, for completely arbitrary coefficient distributions with high contrast, some additional, adaptively chosen constraints are necessary in order to guarantee robustness. In this article, the robustness is heuristically justified as well as numerically shown for several coefficient distributions. The new coarse space is compared to adaptive coarse spaces, and parallel scalability up to 262144 parallel cores for a parallel BDDC implementation with the new coarse space is shown. The superiority of the new coarse space over classic coarse spaces with respect to parallel weak scalability and time-to-solution is confirmed by numerical experiments. Since the new frugal coarse space is computationally inexpensive, it could serve as a new default coarse space, which, for very challenging coefficient distributions, could then still be enhanced by adaptively chosen constraints.

Full Text (PDF) [12.6 MB], BibTeX

Key words

FETI-DP, BDDC, robust coarse spaces, adaptive domain decomposition methods

AMS subject classifications

68W10, 65N22, 65N55, 65F08, 65F10, 65Y05

Links to the cited ETNA articles

[9]	Vol. 45 (2016), pp. 524-544 Juan G. Calvo and Olof B. Widlund: An adaptive choice of primal constraints for BDDC domain decomposition algorithms
[24]	Vol. 48 (2018), pp. 156-182 Alexander Heinlein, Axel Klawonn, Jascha Knepper, and Oliver Rheinbach: Multiscale coarse spaces for overlapping Schwarz methods based on the ACMS space in 2D
[33]	Vol. 49 (2018), pp. 1-27 Axel Klawonn, Martin Kühn, and Oliver Rheinbach: Adaptive FETI-DP and BDDC methods with a generalized transformation of basis for heterogeneous problems
[36]	Vol. 49 (2018), pp. 244-273 Axel Klawonn, Martin Lanser, and Oliver Rheinbach: Nonlinear BDDC Methods with approximate solvers
[38]	Vol. 51 (2019), pp. 432-450 Axel Klawonn, Martin Lanser, Oliver Rheinbach, and Janine Weber: Preconditioning the coarse problem of BDDC methods ‐ three-level, algebraic multigrid, and vertex-based preconditioners
[40]	Vol. 45 (2016), pp. 75-106 Axel Klawonn, Patrick Radtke, and Oliver Rheinbach: A comparison of adaptive coarse spaces for iterative substructuring in two dimensions
[58]	Vol. 46 (2017), pp. 273-336 Clemens Pechstein and Clark R. Dohrmann: A unified framework for adaptive BDDC

< Back