The numerical simulation of mathematical models described by partial differential equations (PDEs) is nowadays an important tool for research in almost every scientific discipline. Yet, the use of such models is often limited by the available computational resources.
Over the last decade, a variety of algorithms have been developed which compute, for a given numerical PDE model, a mathematically certified surrogate that can be simulated in a small fraction of the time required for the solution of the original model. These techniques, known as model order reduction (MOR), are now becoming an integral part in many simulation workflows which otherwise would be infeasible, even on the largest available supercomputers.
See MOR Wiki for more information.
pyMOR is a free software library for building model order reduction applications with the Python programming language. Implemented algorithms include reduced basis methods as well as system-theoretic methods. Some of the available methods are:
With pyMOR, it is possible to link to partial differential equations (PDE) solver packages. Currently, there is support for deal.II, DUNE, FEniCS, and NGSolve. Custom (domain specific) solvers can be easily integrated with pyMOR.
The pyMOR Online Course is our replacement for this year's pyMOR School. We hope to reach current and future pyMOR users. It will take place online from Monday (September 28th) to Friday (October 2nd) (exact schedule tbd.).
The Course will consist of introductory lectures on MOR methods available in pyMOR and programming exercises where participants will learn to use pyMOR with the help of pyMOR developers.
See our Frequently Asked Questions page for additional information.