Volume 63, 2018CEMRACS 2016 - Numerical challenges in parallel scientific computing
|Page(s)||1 - 43|
|Published online||19 October 2018|
Krylov Subspace Solvers and Preconditioners
Delft University of Technology, Delft Institute of Applied Mathematics, Delft, Netherlands
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. After a discretization of partial differential equations large, sparse systems of linear equations have to be solved. Fast solution of these systems is very urgent nowadays. The size of the problems can be 1013 unknowns and 1013 equations. Iterative solution methods are the methods of choice for these large linear systems. We start with a short introduction of Basic Iterative Methods. Thereafter preconditioned Krylov subspace methods, which are state of the art, are describeed. A distinction is made between various classes of matrices.
At the end of the lecture notes many references are given to state of the art Scientific Computing methods. Here, we will discuss a number of books which are nice to use for an overview of background material. First of all the books of Golub and Van Loan  and Horn and Johnson  are classical works on all aspects of numerical linear algebra. These books also contain most of the material, which is used for direct solvers. Varga  is a good starting point to study the theory of basic iterative methods. Krylov subspace methods and multigrid are discussed in Saad  and Trottenberg, Oosterlee and Schüller . Other books on Krylov subspace methods are [1, 6, 21, 34, 39].
© EDP Sciences, SMAI 2018
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