Statistical Timing Analysis Under Spatial Correlations (2005)
| Venue: | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
| Citations: | 27 - 3 self |
BibTeX
@ARTICLE{Chang05statisticaltiming,
author = {Hongliang Chang and Sachin S. Sapatnekar},
title = {Statistical Timing Analysis Under Spatial Correlations},
journal = {IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems},
year = {2005},
volume = {24},
pages = {1467--1482}
}
Years of Citing Articles
OpenURL
Abstract
Abstract — Process variations are of increasing concern in today’s technologies, and can significantly affect circuit performance. We present an efficient statistical timing analysis algorithm that predicts the probability distribution of the circuit delay considering both inter-die and intra-die variations, while accounting for the effects of spatial correlations of intra-die parameter variations. The procedure uses a first-order Taylor series expansion to approximate the gate and interconnect delays. Next, principal component analysis techniques are��and ��� are employed to transform the set of correlated parameters into an uncorrelated set. The statistical timing computation is then easily performed with a PERT-like circuit graph traversal. The run-time of our algorithm is linear in the number of gates and interconnects, as well as the number of varying parameters and grid partitions that are used to model spatial correlations. The accuracy of the method is verified with Monte Carlo simulation. On average, for 100nm technology, the errors of mean and standard deviation values computed by the proposed method respectively, and the errors of predicting the��and confidence point are ���and ���respectively. A testcase with about 17,800 gates was solved in about�seconds, with high accuracy as compared to a Monte Carlo simulation that required more than�hours.







