Friday, 16:15 - 16:40 h, Room: H 0111


Ekkehard Sachs
Reduced order models in preconditioning techniques

Coauthor: Xuancan Ye


The main effort of solving a PDE constrained optimization problem is devoted to solving the corresponding large scale linear system, which is usually sparse and ill conditioned. As a result, a suitable Krylov subspace solver is favourable, if a proper preconditioner is embedded. Other than the commonly used block preconditioners, we exploit knowledge of proper orthogonal decomposition (POD) for preconditioning and achieve some interesting features. Numerical results on nonlinear test problems are presented.


Talk 3 of the invited session Fri.3.H 0111
"Preconditioning in PDE constrained optimization" [...]
Cluster 19
"PDE-constrained optimization & multi-level/multi-grid methods" [...]


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