Statistical ordering of correlated timing quantities and its application for path ranking

Correct ordering of timing quantities is essential for both timing analysis and design optimization in the presence of process variation, because timing quantities are no longer a deterministic value, but a distribution. This paper proposes a novel metric, called tiered criticalities, which guarantees to provide a unique order for a set of correlated timing quantities while properly taking into account full process space coverage. Efficient algorithms are developed to compute this metric, and its effectiveness on path ranking for at-speed testing is also demonstrated.