Non-enumerative Generation of Path Delay Distributions and Its Application to Critical Path Selection

Abstract

A Monte Carlo-based approach is proposed capable of identifying in a non-enumerative and scalable manner the distributions that describe the delay of every path in a combinational circuit. Furthermore, a scalable approach to select critical paths from a potentially exponential number of path candidates is presented. Paths and their delay distributions are stored in Zero Suppressed Binary Decision Diagrams. Experimental results on some of the largest ISCAS-89 and ITC-99 benchmarks shows that the proposed method is highly scalable and effective.