2 papers
math.NA2019
Compression challenges in large scale PDE solvers
Sebastian Götschel, Martin Weiser
Solvers for partial differential equations (PDE) are one of the cornerstones of computational science. For large problems, they involve huge amounts of data that needs to be stored…
math.OC2019
An Efficient Parallel-in-Time Method for Optimization with Parabolic PDEs
Sebastian Götschel, Michael L. Minion
To solve optimization problems with parabolic PDE constraints, often methods working on the reduced objective functional are used. They are computationally expensive due to the nec…