Andrew T. Barker

NA
3papers
25citations
Novelty38%
AI Score19

3 Papers

NADec 2, 2016
A scalable preconditioner for a DPG method

Andrew T. Barker, Veselin Dobrev, Jay Gopalakrishnan et al.

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.

NAAug 30, 2014
A Combined Preconditioning Strategy for Nonsymmetric Systems

Blanca Ayuso de Dios, Andrew T. Barker, Panayot S. Vassilevski

We present and analyze a class of nonsymmetric preconditioners within a normal (weighted least-squares) matrix form for use in GMRES to solve nonsymmetric matrix problems that typically arise in finite element discretizations. An example of the additive Schwarz method applied to nonsymmetric but definite matrices is presented for which the abstract assumptions are verified. A variable preconditioner, combining the original nonsymmetric one and a weighted least-squares version of it, is shown to be convergent and provides a viable strategy for using nonsymmetric preconditioners in practice. Numerical results are included to assess the theory and the performance of the proposed preconditioners.