Affiliations: Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX, USA. E-mail: [email protected] | Sandia National Laboratories, Livermore, CA, USA. E-mail: [email protected] | Sandia National Laboratories, Albuquerque, NM, USA. E-mail: [email protected]
Note: [] Corresponding author: Kevin Long, Department of Mathematics and Statistics, Texas Tech University, Broadway and Boston, Lubbock, TX 79049-1042, USA. E-mail: [email protected].
Abstract: Sundance is a package in the Trilinos suite designed to provide high-level components for the development of high-performance PDE simulators with built-in capabilities for PDE-constrained optimization. We review the implications of PDE-constrained optimization on simulator design requirements, then survey the architecture of the Sundance problem specification components. These components allow immediate extension of a forward simulator for use in an optimization context. We show examples of the use of these components to develop full-space and reduced-space codes for linear and nonlinear PDE-constrained inverse problems.
