Paper Info
Title
Variational capacitance modeling using orthogonal polynomial method
Abstract
In this paper, we propose a novel statistical capacitance extraction method for interconnects considering process variations. The new method, called statCap, is based on the spectral stochastic method where orthogonal polynomials are used to represent the statistical processes in a deterministic way. We first show how the variational potential coefficient matrix is represented in a first-order form using Taylor expansion and orthogonal decomposition. Then an augmented potential coefficient matrix, which consists of the coefficients of the polynomials, is derived. After that, corresponding augmented system is solved to obtain the variational capacitance values in the orthogonal polynomial form. Experimental results show that our method is two orders of magnitude faster than the recently proposed statistical capacitance extraction method based on the spectral stochastic collocation approach and many orders of magnitude faster than the Monte Carlo method for several practical interconnect structures.
Year
DOI
Venue
2008
10.1145/1366110.1366119
ACM Great Lakes Symposium on VLSI
Keywords
Field
DocType
variational capacitance value,orthogonal polynomial,variational capacitance modeling,orthogonal decomposition,statistical process,novel statistical capacitance extraction,new method,monte carlo method,orthogonal polynomial form,spectral stochastic method,orthogonal polynomial method,statistical capacitance extraction method,random variable,process variation,first order,taylor expansion
Monte Carlo method,Coefficient matrix,Capacitance,Orthogonal polynomials,Polynomial,Mathematical analysis,Orthogonal collocation,Mathematics,Taylor series,Collocation
Conference
Citations 
PageRank 
References 
6
0.56
14
Authors
6
Name
Order
Citations
PageRank
Jian Cui160.56
Gengsheng Chen2265.13
Ruijing Shen3686.75
Sheldon Tan470.91
Wenjian Yu522547.76
Jiarong Tong66811.74