On sparse and compact preconditioned conjugate gradient methods for partial differential equations

Abstract

This paper generalises the preconditioning techniques, introduced by Evans [2], and defines sparse and compact preconditioned iterative methods for the numerical solution of the linear system Au = b.The difference between the methods is shown to depend on whether a conditioning matrix R consists of components derived from a splitting or factorization of A. Some theoretical results for the iterative schemes are given when A has particular properties such as consistent ordering, irreducibility, diagonal dominance, positive definiteness, etc., when derived from the finite difference discretisation of a 2nd order self-adjoint elliptic partial differential equation. Finally, the application of both forms of preconditioning to the Conjugate Gradient method is presented and computational results compared.

†Unit of Applied Mathematics. University of Athens. Greece.

†Unit of Applied Mathematics. University of Athens. Greece.

Notes

†Unit of Applied Mathematics. University of Athens. Greece.