ENOR: model order reduction of RLC circuits using nodal equations for efficient factorization
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
How to efficiently capture on-chip inductance effects: introducing a new circuit element K
Proceedings of the 2000 IEEE/ACM international conference on Computer-aided design
Robust and passive model order reduction for circuits containing susceptance elements
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Window-Based Susceptance Models for Large-Scale RLC Circuit Analyses
Proceedings of the conference on Design, automation and test in Europe
PRIMA: passive reduced-order interconnect macromodeling algorithm
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Structure preserving reduction of frequency-dependent interconnect
Proceedings of the 42nd annual Design Automation Conference
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
Proceedings of the 2006 international symposium on Physical design
Empire: an efficient and compact multiple-parameterized model order reduction method
Proceedings of the 2007 international symposium on Physical design
A fast block structure preserving model order reduction for inverse inductance circuits
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
SBPOR: second-order balanced truncation for passive order reduction of RLC circuits
Proceedings of the 44th annual Design Automation Conference
EMPIRE: an efficient and compact multiple-parameterized model-order reduction
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Fast analysis of a large-scale inductive interconnect by block-structure-preserved macromodeling
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Decentralized and passive model order reduction of linear networks with massive ports
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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The recently-introduced susceptance element exhibits many prominent features in modeling the on-chip magnetic couplings. For an RCS circuit, it is better to be formulated as a second-order system. Therefore, corresponding MOR (model-order reduction) techniques for second-order systems are desired to efficiently deal with the ever-increasing circuit scale and to preserve essential model properties. We first review the existing MOR methods for RCS circuits, such as ENOR and SMOR, and discuss several key issues related to numerical stability and accuracy of the methods. Then, a technique, SAPOR (second-order Arnoldi method for passive order reduction), is proposed to effectively address these issues. Based on an implementation of a generalized second-order Arnoldi method, SAPOR is numerically stable and efficient. Meanwhile, the reduced-order system also guarantees passivity.