Elements of information theory
Elements of information theory
KSim: a stable and efficient RKC simulator for capturing on-chip inductance effect
Proceedings of the 2001 Asia and South Pacific Design Automation Conference
Modeling magnetic coupling for on-chip interconnect
Proceedings of the 38th annual Design Automation Conference
On the efficacy of simplified 2D on-chip inductance models
Proceedings of the 39th annual 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
INDUCTWISE: inductance-wise interconnect simulator and extractor
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Compact and stable modeling of partial inductance and reluctance matrices
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
On-chip interconnect modeling by wire duplication
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A fast band-matching technique for interconnect inductance modeling
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Generating stable and sparse reluctance/inductance matrix under insufficient conditions
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
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Recent successful techniques for the efficient simulation of largescale interconnect models rely on the sparsification of the inverse of the inductance matrix L. While there are several techniques for sparsifying L-1, the stability of these approximations for general interconnect structures has not been established, i.e., the sparsified reluctance and inductance matrices are not guaranteed to be positive-definite. In this paper, we present a novel technique for reluctance sparsification for general interconnect structures that enjoys several advantages: First, the resulting sparse approximation is guaranteed to be positive definite. Second, the approximation is optimal, in a certain well-defined sense. Third, owing to its computational efficiency and numerical stability, the algorithm is applicable for very large problem sizes. Finally our approach yields a compact representation of both inductance and reluctance matrices for general cases.