A Scalable Auxiliary Space Preconditioner for High-Order Finite Element Methods

TL;DR

This paper enhances an auxiliary space preconditioning method for high-order finite element systems, providing new convergence estimates, parallel implementation, and demonstrating improved efficiency and scalability on complex PDEs.

Contribution

It introduces a new convergence rate estimate and parallel implementation for an auxiliary space preconditioner, improving its robustness and scalability for high-order finite element methods.

Findings

Demonstrates improved efficiency and robustness on Poisson and Stokes equations.

Shows good parallel scalability on 3D unstructured grids.

Provides theoretical convergence rate estimates for the preconditioner.

Abstract

In this paper, we revisit an auxiliary space preconditioning method proposed by Xu [Computing 56, 1996], in which low-order finite element spaces are employed as auxiliary spaces for solving linear algebraic systems arising from high-order finite element discretizations. We provide a new convergence rate estimate and parallel implementation of the proposed algorithm. We show that this method is user-friendly and can play an important role in a variety of Poisson-based solvers for more challenging problems such as the Navier--Stokes equation. We investigate the performance of the proposed algorithm using the Poisson equation and the Stokes equation on 3D unstructured grids. Numerical results demonstrate the advantages of the proposed algorithm in terms of efficiency, robustness, and parallel scalability.