Statistical critical path analysis considering correlations

Authors:
Yaping Zhan;Andrzej J. Strojwas;Mahesh Sharma;David Newmark
Affiliations:
Department of ECE, Carnegie Mellon University, Pittsburgh, PA;Department of ECE, Carnegie Mellon University, Pittsburgh, PA;Advanced Micro Devices Inc, Austin, TX;Advanced Micro Devices Inc, Austin, TX
Venue:
PATMOS'05 Proceedings of the 15th international conference on Integrated Circuit and System Design: power and Timing Modeling, Optimization and Simulation
Year:
2005

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Abstract

Critical Path Analysis is always an important task in timing verification. For today's nanometer IC technologies, process variations have a significant impact on circuit performance. The variability can change the criticality of long paths [1]. Therefore, statistical approaches should be incorporated in Critical Path Analysis. In this paper, we present two novel techniques that can efficiently evaluate path criticality under statistical non-linear delay models. They are integrated into a block-based Statistical Timing tool with the capability of handling arbitrary correlations from manufacturing process dependence and also path sharing. Experiments on ISCAS85 benchmarks prove both accuracy and efficiency of these techniques.