  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.
