9, IO]. However, unlike the case with static timing, it is not so easy We show how recent advances in the handling of correlated interval representations of range uncertainty can be used to predict the impact of statistical manufacturing variations on linear interconnect. We represent correlated statistical variations in RLC parameters as sets of correlated intervals, and show how classical model order reduction methods -AWE and PRIMA -can be re-targeted to compute interval-valued, rather than scalar-valued reductions. By apto see how to represent the essential statistics. For example, it is easy to add two normal distributions; it is not easy to extract the dominant eigenvalues from a matrix whose entries are themselves correlated normal distributions, and represent this as yet another normal distribution. Historically, there have been three different avenues of attack on the statistical interconnect modeling problem: plying a statistical interpretation and samplingto the resulting co...
James D. Ma, Rob A. Rutenbar