Fast Simulation Technique of Plane Circuits via Two-Layer CNN-Based Modeling

Yuichi TANJI  Hideki ASAI  Masayoshi ODA  Yoshifumi NISHIO  Akio USHIDA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E91-A   No.12   pp.3757-3762
Publication Date: 2008/12/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e91-a.12.3757
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Nonlinear Problems
Keyword: 
cellular neural networks,  plane circuits,  signal/power integrity,  leapfrog method,  

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Summary: 
A fast time-domain simulation technique of plane circuits via two-layer Cellular Neural Network (CNN)-based modeling, which is necessary for power/signal integrity evaluation in VLSIs, printed circuit boards, and packages, is presented. Using the new notation expressed by the two-layer CNN, 1,553 times faster simulation is achieved, compared with Berkeley SPICE (ngspice). In CNN community, CNNs are generally simulated by explicit numerical integration such as the forward Euler and Runge-Kutta methods. However, since the two-layer CNN is a stiff circuit, we cannot analyze it by using an explicit numerical integration method. Hence, to analyze the two-layer CNN and reduce the computational cost, the leapfrog method is introduced. This procedure would open an application of CNN to electronic design automation area.