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pyMOR - GENERIC ALGORITHMS AND INTERFACES FOR MODEL ORDER REDUCTION

delete2016-01-01
delete41
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OA
AI
R
René Milk *
S
Stephan Rave
F
Felix Schindler
DOI:10.1137/15M1026614delete
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Abstract

Abstract

En 中文
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.
Keywords:
model order reduction
reduced basis method
empirical interpolation
scientific computing
software
Python
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Journal

SIAM Journal on Scientific Computing cover
SIAM Journal on Scientific Computing
IF:
2.6
Papers:
5.1K
Citations:
1.8W

Organization

U
university of munster
Scholars:
2.8W
Papers: 2.2W
Citations: 45