Two-level additive Schwarz preconditioners with GDSW coarse spaces for high-order discretizations in 3D

Overlapping Schwarz methods are among the most successful domain decomposition preconditioners for large-scale finite element simulations. In this work, the Generalized Dryja-Smith-Widlund (GDSW), GDSW$^*$, and Reduced GDSW (RGDSW) coarse spaces are studied for three-dimensional high-order finite element method (FEM) and virtual element method (VEM) for the Poisson equation and the equations of linear elasticity. To the best of our knowledge, this is the first study of GDSW-type coarse spaces for polynomial degrees $k\ge 3$ in three dimensions, for either discretization. In 3D VEM, the face degrees of freedom (DOFs) are moments instead of point values. The kernel of the differential operator, which defines the interface values of the GDSW coarse basis functions, must be represented through these moments. The construction is therefore no longer purely algebraic and, without this correction, the coarse level loses its effect for $k\ge 3$. FEM and VEM are tested on hexahedral meshes, and VEM is additionally tested on polyhedral ones. Polynomial degrees up to $k=5$ and runs on up to $4\,096$ subdomains and parallel cores are included in the numerical study. Numerical experiments show scalable iteration counts for all coarse space variants for the Poisson problem, illustrating the expected trade-off between the coarse space size and robustness. Further experiments for linear elasticity confirms that the moment-based construction extends naturally from the scalar to the vector-valued problem.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-02
DOI
https://doi.org/10.48550/arxiv.2611.03447
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Two-level additive Schwarz preconditioners with GDSW coarse spaces for high-order discretizations in 3D

Tommaso Bevilacqua, Martin Lanser, Axel Klawonn, Adam Wasiak
arXiv (Cornell University)
Advanced Numerical Methods in Computational Mathematics
preprint

Two-level additive Schwarz preconditioners with GDSW coarse spaces for high-order discretizations in 3D

Tommaso Bevilacqua, Martin Lanser, Axel Klawonn, Adam Wasiak
preprint en

Abstract

Overlapping Schwarz methods are among the most successful domain decomposition preconditioners for large-scale finite element simulations. In this work, the Generalized Dryja-Smith-Widlund (GDSW), GDSW$^*$, and Reduced GDSW (RGDSW) coarse spaces are studied for three-dimensional high-order finite element method (FEM) and virtual element method (VEM) for the Poisson equation and the equations of linear elasticity. To the best of our knowledge, this is the first study of GDSW-type coarse spaces for polynomial degrees $k\ge 3$ in three dimensions, for either discretization. In 3D VEM, the face degrees of freedom (DOFs) are moments instead of point values. The kernel of the differential operator, which defines the interface values of the GDSW coarse basis functions, must be represented through these moments. The construction is therefore no longer purely algebraic and, without this correction, the coarse level loses its effect for $k\ge 3$. FEM and VEM are tested on hexahedral meshes, and VEM is additionally tested on polyhedral ones. Polynomial degrees up to $k=5$ and runs on up to $4\,096$ subdomains and parallel cores are included in the numerical study. Numerical experiments show scalable iteration counts for all coarse space variants for the Poisson problem, illustrating the expected trade-off between the coarse space size and robustness. Further experiments for linear elasticity confirms that the moment-based construction extends naturally from the scalar to the vector-valued problem.

arXiv (Cornell University)
Advanced Numerical Methods in Computational Mathematics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon