Criticality computation in parameterized statistical timing

  • Authors:
  • Jinjun Xiong;Vladimir Zolotov;Natesan Venkateswaran;Chandu Visweswariah

  • Affiliations:
  • Univ. of California, Los Angeles, CA;IBM Research, Yorktown Heights, NY;IBM Sys. & Tech. Group, Fishkill, NY;IBM Research, Yorktown Heights, NY

  • Venue:
  • Proceedings of the 43rd annual Design Automation Conference
  • Year:
  • 2006

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Abstract

Chips manufactured in 90 nm technology have shown large parametric variations, and a worsening trend is predicted. These parametric variations make circuit optimization difficult since different paths are frequency-limiting in different parts of the multi-dimensional process space. Therefore, it is desirable to have a new diagnostic metric for robust circuit optimization. This paper presents a novel algorithm to compute the criticality probability of every edge in the timing graph of a design with linear complexity in the circuit size. Using industrial benchmarks, we verify the correctness of our criticality computation via Monte Carlo simulation. We also show that for large industrial designs with 442,000 gates, our algorithm computes all edge criticalities in less than 160 seconds.