Model-assisted effective large scale matrix computations

Prof.in Valeria Simoncini PhD

Oct. 16, 2012, 1:45 p.m. S2 059

Advanced mathematical models very often require the solution of
(sequences of) large algebraic linear systems, whose
numerical treatment should incorporate problem information in order
to be computationally effective. For instance,
matrices and vectors usually inherit crucial (e.g., spectral) properties
of the underlying continuous operators.
In this talk we will discuss a few examples where the performance
of state-of-the-art iterative linear system solvers
can be dramatically enhanced by exploiting
these properties.
Our presentation will focus on structured linear systems
stemming from the numerical discretization of
systems of partial differential equations,
as well as of optimal control problems constrained by
partial differential equations.