SAMSON: A Generalized Second-order Arnoldi Method for Reducing Multiple Source Network

Power integrity analysis of in-package and on-chip power supply needs to consider a large number of ports and handle magnetic coupling that is better represented by susceptance. The existing moment matching methods are not able to accurately model both large number of ports and susceptance. In this paper, we propose a generalized Second-order Arnoldi method for reducing Multiple SOurce Network (SAMSON) for linear circuits considering susceptance (S). We employ a right-hand-side excitation current vector to replace the port incident matrix such that an MIMO system is transformed into an equivalent superposed SISO system to avoid accuracy loss in block moment matching, and develop a generalized second-order Arnoldi method based orthonormalization to simultaneously accurately handle susceptance and all kinds of non-impulse current sources. Compared with existing EKS and IEKS approaches able to consider non-impulse sources but not susceptance, SAMSON is slightly faster and is more accurate in high frequency range and at dc. With same model order, SAMSON reduces time domain waveform error by 33X compared to EKS/IEKS and by 47X compared with the best block moment matching method applicable to susceptance.