System‐theoretic model order reduction with pyMOR

pyMOR - Generic Algorithms and Interfaces for Model Order Reduction

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 mai...

Model Checking with the Partial Order Reduction

Symbolic Model Order Reduction

Symbolic Model Order Reduction (SMOR) is the problem of reducing a large circuit that contains symbolic circuit parameters to smaller low order models at its ports. Several methods, including symbol isolation, single frequency point reduction, and multiple frequency point reduction, are described and compared. Test circuits with simulation results are presented to demonstrate the accuracy and e...

Model Order Reduction

This chapter presents an overview of Model Order Reduction – a new paradigm in the field of simulationbased engineering sciences, and one that can tackle the challenges and leverage the opportunities of modern ICT technologies. Despite the impressive progress attained by simulation capabilities and techniques, a number of challenging problems remain intractable. These problems are of different ...

Introduction to Model Order Reduction

In this first section we present a high level discussion on computational science, and the need for compact models of phenomena observed in nature and industry. We argue that much more complex problems can be addressed by making use of current computing technology and advanced algorithms, but that there is a need for model order reduction in order to cope with even more complex problems. We als...