For-loop equivalents and massive parallelization in CasADi
Joris Gillis
KU Leuven, Belgien
Tuesday, July 19, 2016, 11:45
Room 01-012, Georges-Köhler-Allee 102, Freiburg 79110, Germany
In system identification, long horizons may degrade performance of CasADi when solving an optimal control method using a direct approach.
This talk describes how the 'map' and 'mapaccum' nodes can be used to avoid costly for-loops and memory overhead for this application.
Further, the map abstraction is shown to lead to easy parallelization capabilities.
A second application, optimization in image processing, is used to show massive speed-ups with the GPU within the CasADi framework.