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Accurate timing prediction at placement stage with look-ahead RC network

Xu He, Zhiyong Fu, Yao Wang, Chang Liu, Yang Guo

2022Year
43Citations
4Top-tier citations

Abstract

Timing closure is a critical but effort-taking task in VLSI designs. In placement stage, a fast and accurate net delay estimator is highly desirable to guide the timing optimization prior to routing, and thus reduce the timing pessimism and shorten the design turn-around time. To handle the timing uncertainty at the placement stage, we propose a fast net delay timing predictor based on machine learning, which extract the fully timing features using a look-ahead RC network. Experimental results show that the proposed timing predictor has achieved average correlation over 0.99 with the post-routing sign-off timing results obtained in Synopsys PrimeTime.

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