Statistical static timing analysis: how simple can we get?

  • Authors:
  • Chirayu S. Amin;Noel Menezes;Kip Killpack;Florentin Dartu;Umakanta Choudhury;Nagib Hakim;Yehea I. Ismail

  • Affiliations:
  • Northwestern University, Evanston, IL;Intel Corporation, Hillsboro, OR;Intel Corporation, Hillsboro, OR;Intel Corporation, Hillsboro, OR;Intel Corporation, Hillsboro, OR;Intel Corporation, Hillsboro, OR;Northwestern University, Evanston, IL

  • Venue:
  • Proceedings of the 42nd annual Design Automation Conference
  • Year:
  • 2005

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Abstract

With an increasing trend in the variation of the primary parameters affecting circuit performance, the need for statistical static timing analysis (SSTA) has been firmly established in the last few years. While it is generally accepted that a timing analysis tool should handle parameter variations, the benefits of advanced SSTA algorithms are still questioned by the designer community because of their significant impact on complexity of STA flows. In this paper, we present convincing evidence that a path-based SSTA approach implemented as a post-processing step captures the effect of parameter variations on circuit performance fairly accurately. On a microprocessor block implemented in 90nm technology, the error in estimating the standard deviation of the timing margin at the inputs of sequential elements is at most 0.066 FO4 delays, which translates in to only 0.31% of worst case path delay.