pyMOR - Generic Algorithms and Interfaces for Model Order Reduction

TL;DR

pyMOR is an open-source Python library that provides generic, easily integrable algorithms for model order reduction, especially reduced basis methods, to efficiently solve parametrized PDEs.

Contribution

The paper introduces pyMOR, a flexible Python library implementing model reduction algorithms with a generic interface for seamless integration with PDE solvers.

Findings

pyMOR successfully integrates with existing PDE solvers.

Benchmark results demonstrate significant computational savings.

Numerical examples validate the effectiveness of the reduction methods.

Abstract

Reduced basis methods are projection-based model order reduction techniques for reducing the computational complexity of solving parametrized partial differential equation problems. In this work we discuss the design of pyMOR, a freely available software library of model order reduction algorithms, in particular reduced basis methods, implemented with the Python programming language. As its main design feature, all reduction algorithms in pyMOR are implemented generically via operations on well-defined vector array, operator and discretization interface classes. This allows for an easy integration with existing open-source high-performance partial differential equation solvers without adding any model reduction specific code to these solvers. Besides an in-depth discussion of pyMOR's design philosophy and architecture, we present several benchmark results and numerical examples showing the feasibility of our approach.