Weighted Principal Factor Analysis in Statistical Interconnect Parasitic Extraction

To cope with the problems of statistical parasitic extraction induced by random process variations, the technique of weighted principal factor analysis (wPFA) based on Hermite Polynomial Collocation method is proposed to reduce the number of random variables and improve the computational efficiency.The parallel computing technique is also applied to further reduce the computational time.Numerical results show that, the wPFA is able to accelerate the statistical extraction using a normal principal factor analysis by several or several tens times.While, the parallel computing experiment on a machine with 8 CPU achieves a speedup of 6.7.