A high-performance parallel implementation of the certified reduced basis method

Abstract The certified reduced basis method (herein RB method) is a popular approach for model reduction of parametrized partial differential equations. In this paper we introduce new techniques that are required to efficiently implement the Offline “Construction stage” of the RB method on high-performance parallel supercomputers. This enables us to generate certified RB models for large-scale three-dimensional problems that can be evaluated on standard workstations and other “thin” computing resources with speedup of many orders of magnitude compared to the corresponding full order model. We use our implementation to perform detailed numerical studies for two computationally expensive model problems: a natural convection fluid flow problem and a “many parameter” heat transfer problem. In the heat transfer problem, we exploit the computational efficiency of the RB method to perform a detailed study of “snapshot” selection in the Greedy algorithm, and we also examine statistics of the output sensitivity derivatives to obtain a “global” view of the relative importance of the parameters.

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