Parametric yield estimation considering leakage variability

  • Authors:
  • Rajeev R. Rao;Anirudh Devgan;David Blaauw;Dennis Sylvester

  • Affiliations:
  • University of Michigan, Ann Arbor, MI;IBM Corporation, Austin, TX;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI

  • Venue:
  • Proceedings of the 41st annual Design Automation Conference
  • Year:
  • 2004

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Abstract

Leakage current has become a stringent constraint in modern processor designs in addition to traditional constraints on frequency. Since leakage current exhibits a strong inverse correlation with circuit delay, effective parametric yield prediction must consider the dependence of leakage current on frequency. In this paper, we present a new chip-level statistical method to estimate the total leakage current in the presence of within-die and die-to-die variability. We develop a closed-form expression for total chip leakage that models the dependence of the leakage current distribution on a number of process parameters. The model is based on the concept of scaling factors to capture the effects of within-die variability. Using this model, we then present an integrated approach to accurately estimate the yield loss when both frequency and power limits are imposed on a design. Our method demonstrates the importance of considering both these limiters in calculating the yield of a lot.