Invited Session Wed.3.H 1058

Wednesday, 15:15 - 16:45 h, Room: H 1058

Cluster 10: Implementations & software [...]

Software for large-scale optimization


Chair: Denis Ridzal



Wednesday, 15:45 - 16:10 h, Room: H 1058, Talk 2

Stefan Richter
FiOrdOs: A Matlab toolbox for C-code generation for first-order methods

Coauthors: Jones Neil Jones, Manfred Morari, Fabian Ullmann


FiOrdOs is the first toolbox for automated C-code generation for first-order methods. It considers the class of multi-parametric convex programs with a quadratic cost and a feasible set given as the intersection of an affine set and a `simple' convex set for which a projection can be evaluated at low cost; this class comprises important embedded optimization problems, for example, model predictive control. The toolbox implements both polyhedral and non-polyhedral simple sets, e.g. the simplex and 1-norm ball and the 2-norm ball and second-order cone respectively. Thus, solver code for problems beyond quadratic programming can be generated. If required, the
solution approach is based on Lagrange relaxation which uses the gradient or the fast gradient method at a lower level. Additional toolbox features include optimal preconditioning and the automatic certification of the iteration count for a restricted set of problems. The generated C-code can be compiled for any platform and can be made library-free. FiOrdOs also provides a tailored MEX-interface for calling the generated solvers inside Matlab and a Simulink library for rapid prototyping.



Wednesday, 16:15 - 16:40 h, Room: H 1058, Talk 3

Eric Phipps
Support embedded algorithms through template-based generic programming

Coauthors: Roger Pawlowski, Andy Salinger


We describe a framework for incorporating embedded analysis algorithms, such as derivative-based optimization and uncertainty quantification, in large-scale simulation codes using template-based generic programming. The framework is based on standard C++ language constructs such as templating, operator overloading, expression templates, and template metaprogramming, and enables the incorporation of advanced algorithms with a minimum of programmer effort. In this talk we describe the overall approach, several software tools implementing the approach in the Trilinos solver framework, and examples demonstrating the usefulness of the approach applied to optimization and uncertainty quantification of large-scale PDE-based simulations.


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