A scalable preconditioner for a DPG method
Numerical Analysis
2018-07-10 v1
Abstract
We show how a scalable preconditioner for the primal discontinuous Petrov-Galerkin (DPG) method can be developed using existing algebraic multigrid (AMG) preconditioning techniques. The stability of the DPG method gives a norm equivalence which allows us to exploit existing AMG algorithms and software. We show how these algebraic preconditioners can be applied directly to a Schur complement system of interface unknowns arising from the DPG method. To the best of our knowledge, this is the first massively scalable algebraic preconditioner for DPG problems.
Keywords
Cite
@article{arxiv.1612.00838,
title = {A scalable preconditioner for a DPG method},
author = {Andrew T. Barker and Veselin Dobrev and Jay Gopalakrishnan and Tzanio Kolev},
journal= {arXiv preprint arXiv:1612.00838},
year = {2018}
}