Digital design at a crossroads: how to make statistical design methodologies industrially relevant

  • Authors:
  • Ulf Schlichtmann;Manuel Schmidt;Michael Pronath;Volker Glöckel;Harald Kinzelbach;Manfred Dietrich;Uwe Eichler;Joachim Haase

  • Affiliations:
  • Technische Universität München, Munich, Germany;Technische Universität München, Munich, Germany;MunEDA GmbH, Munich, Germany;MunEDA GmbH, Munich, Germany;Infineon Technologies AG, Munich, Germany;Fraunhofer IIS/EAS Dresden, Dresden, Germany;Fraunhofer IIS/EAS Dresden, Dresden, Germany;Fraunhofer IIS/EAS Dresden, Dresden, Germany

  • Venue:
  • Proceedings of the Conference on Design, Automation and Test in Europe
  • Year:
  • 2009

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Abstract

Statistical analysis is generally seen as the next EDA technology for timing and power sign-off. Research into this field has seen significant activity started about five years ago. Recently, interest appears to have fallen off somewhat. Also, while a lot of focus has been put on research fundamentals, extremely few applications in industry have been reported so far. Therefore, a group including Infineon Technologies as a leading semiconductor IDM and various universities and research institutes, as well as an EDA provider has tackled key challenges to enable statistical design in industry in a publicly funded project called "Sigma65". Sigma65 strives to provide key foundations to allow a change from traditional deterministic design methods to future design methods driven by statistical considerations. The project starts with statistical modeling and optimization of library components and ranges to statistical techniques for designing ICs on gate level and higher levels. In this paper, we present some results of this project, demonstrating how the interaction between industrial perspective, research institutions and EDA provider enables solutions which are applicable already in the near future. After an overview of the industrial perspective of the current situation in dealing with variations recent results on both statistical timing and power analysis will be given. In addition, recent research advances on fast yield estimation concerning parametric timing yield will be given.