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The rapid growth of circuit complexity has rendered Model Order Reduction(MOR) a key enabler for the efficient simulation of large circuit models. MORtechniques based on moment-matching are well established due to theirsimplicity and computational performance in the reduction process. However,moment-matching methods based on the ordinary Krylov subspace are usuallyinadequate to accurately approximate the original circuit behavior, and at thesame time do not produce reduced-order models as compact as needed. In thispaper, we present a moment-matching method which utilizes the extended and theasymmetric extended Krylov subspace (EKS and AEKS), while it allows theparallel computation of the transfer function in order to deal with circuitsthat have many terminals. The proposed method can handle large-scale regularand singular circuits and generate accurate and efficient reduced-order modelsfor circuit simulation. Experimental results on industrial IBM power gridsdemonstrate that the EKS method can achieve an error reduction up to 85.28%over a standard Krylov subspace method, while the AEKS method greatly reducesthe runtime of EKS, introducing a negligible overhead in the reduction error.

The Extended and Asymmetric Extended Krylov Subspace in Moment-Matching-Based Order Reduction of Large Circuit Models