Library Compatible Variational Delay Computation

  • Luis Guerra e Silva
  • Zhenhai Zhu
  • Joel R. Phillips
  • L. Miguel Silveira
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 249)

With technology steadily progressing into nanometer dimensions, precise control over all aspects of the fabrication process becomes an area of increasing concern. Process variations have immediate impact on circuit performance and behavior and standard design and signoff methodologies have to account for such variability. In this context, timing verification, already a challenging task due to the sheer complexity of todays designs, becomes an increasingly difficult problem. Statistical static timing analysis has been proposed as a solution to this problem, but most of the work has focused in the development of timing engines for computing delay propagation. Such tools rely on the availability of delay formulas accounting for both cell and interconnect delay that take into account unpredictable variability effects. In this paper, we concentrate on the impact of interconnect on delay and propose an extension to the standard modeling strategies that is variation-aware and compatible with such statistical engines. Our approach, based on a specific type of perturbation analysis, allows for the analytical computation of the quantities needed for statistical delay propagation. We also show how perturbation analysis can be performed when only the standard delay table lookup models are available for the standard cells. This makes the proposed approach compatible with existing timing analysis frameworks. Results from applying our proposed modeling strategy to computing delays and slews in several instances accurately match similar results obtained using electrical level simulation.


Perturbation Analysis Research Trend Cell Delay Delay Computation Timing Characterization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© International Federation for Information Processin 2008

Authors and Affiliations

  • Luis Guerra e Silva
    • 1
  • Zhenhai Zhu
    • 2
  • Joel R. Phillips
    • 2
  • L. Miguel Silveira
    • 1
  1. 1.Cadence Laboratories / INESC-ID ISTTech. U. LisbonPortugal
  2. 2.Cadence Berkeley LaboratoriesCadence Design SystemsSan JoseUSA

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