High-performance digital circuits are facing increasingly severe signal integrity problems due to crosstalk noise and therefore the state-of-the-art static timing analysis (STA) methods consider crosstalk-induced delay variation. Current noise-aware STA methods compute noise-induced delay uncertainly for each net independently and annotate appropriate delay changes of nets onto data paths and associated clock paths to determine timing violations. Since delay changes in individual nets contribute cumulatively to delay changes of paths, even small amounts of pessimism in noise computation of nets can add up to produce large timing violations for paths, which may be unrealistic. Unlike glitch noise analysis where noise often attenuates during propagation, quality of delay noise analysis is severely affected by any pessimism in noise estimation and can unnecessarily cost valuable silicon and design resources for fixing unreal violations. In this paper, we propose a method to reduce pessimism in noise-aware STA by considering signal correlations of a11 nets associated with an entire timing path simultaneously, in a path-based approach. We first present an exact algorithm based on the branch-and-bound technique and then extend it with several heuristic techniques so that very large industrial designs can be analyzed efficiently. These techniques, which are implemented in an industrial crosstalk noise analysis tool, show as much as 75% reduction in the computed path delay variations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.