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arXiv · 2007.01948

Exploiting Extended Krylov Subspace for the Reduction of Regular and Singular Circuit Models

Chrysostomos Chatzigeorgiou·Dimitrios Garyfallou·George Floros·Nestor Evmorfopoulos·George Stamoulis
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Abstract

During the past decade, Model Order Reduction (MOR) has become key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-matching are well established due to their simplicity and computational performance in the reduction process. However, moment-matching methods based on the ordinary Krylov subspace are usually inadequate to accurately approximate the original circuit behavior. In this paper, we present a moment-matching method which is based on the extended Krylov subspace and exploits the superposition property in order to deal with many terminals. The proposed method can handle large-scale regular and singular circuits and generate accurate and efficient reduced-order models for circuit simulation. Experimental results on industrial IBM power grids demonstrate that our method achieves an error reduction up to 83.69% over a standard Krylov subspace method.

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Chrysostomos Chatzigeorgiou, Dimitrios Garyfallou, George Floros, Nestor Evmorfopoulos, George Stamoulis. 2020-07-03. Exploiting Extended Krylov Subspace for the Reduction of Regular and Singular Circuit Models. https://arxiv.org/abs/2007.01948

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