Parallel Model Order Reducation for Sparse Electromagnetic/Circuit Models

Authors

  • Giovanni De Luca Dipartimento di Ingegneria Industriale e dell’Informazione e di Economia Università degli Studi dell’Aquila, L’Aquila, 67100, Italy
  • Giulio Antonini Dipartimento di Ingegneria Industriale e dell’Informazione e di Economia Università degli Studi dell’Aquila, L’Aquila, 67100, Italy
  • Peter Benner 2Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany

Keywords:

Model order reduction, parallel computing, sparse electromagnetic/circuit systems

Abstract

This paper describes a parallel Model Order Reduction (MOR) technique for Linear Time Invariant (LTI) electromagnetic/circuit systems with sparse structure. The multi-point Krylovsubspace projection method is adopted as framework for the model order reduction and a parallelization strategy is proposed. More specifically, a multi-point version of the wellknown PRIMA algorithm is proposed, which is parallelized with respect to the computation of the error between the original model and the reduced one. The number of moments to be matched for any expansion point is chosen adaptively as well. The numerical results show that the proposed parallelized MOR algorithm is able to preserve the accuracy of the reduced models while providing a significant compression and a satisfactory speedup with respect to the sequential one.

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Published

2021-08-24

How to Cite

[1]
G. D. . Luca, G. . Antonini, and P. . Benner, “Parallel Model Order Reducation for Sparse Electromagnetic/Circuit Models”, ACES Journal, vol. 30, no. 01, pp. 1–21, Aug. 2021.

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General Submission