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.
@article{arxiv.2007.01948,
title = {Exploiting Extended Krylov Subspace for the Reduction of Regular and Singular Circuit Models},
author = {Chrysostomos Chatzigeorgiou and Dimitrios Garyfallou and George Floros and Nestor Evmorfopoulos and George Stamoulis},
journal= {arXiv preprint arXiv:2007.01948},
year = {2020}
}