Efficient Preconditioning of hp-FEM Matrices by Hierarchical Low-Rank Approximations

Abstract

We introduce a preconditioner based on a hierarchical low-rank compression scheme of Schur complements. The construction is inspired by standard nested dissection, and relies on the assumption that the Schur complements can be approximated, to high precision, by Hierarchically-Semi-Separable matrices. We build the preconditioner as an approximate $$LDM^t$$LDMt factorization of a given matrix A, and no knowledge of A in assembled form is required by the construction. The $$LDM^t$$LDMt factorization is amenable to fast inversion, and the action of the inverse can be determined fast as well. We investigate the behavior of the preconditioner in the context of DG finite element approximations of elliptic and hyperbolic problems, with respect to both the mesh size and the order of approximation.