Early prediction of NBTI effects using RTL source code analysis

Jayanand Asok Kumar, Kenneth M. Butler, Heesoo Kim, Shobha Vasudevan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In present day technology, the design of reliable systems must factor in temporal degradation due to aging effects such as Negative Bias Temperature Instability (NBTI). In this paper, we present a methodology to estimate delay degradation early at the Register Transfer Level (RTL). We statically analyze the RTL source code to determine signal correlations. We then determine probability distributions of RTL signals formally by using probabilistic model checking. Finally, we propagate these signal probabilities through delay macromodels and estimate the delay degradation. We demonstrate our methodology on several benchmarks RTL designs. We estimate the degradation with <10% error and up to 18.2x speedup in runtime as compared to estimation using gate-level simulations.

Original languageEnglish (US)
Title of host publicationProceedings of the 49th Annual Design Automation Conference, DAC '12
Pages808-813
Number of pages6
DOIs
StatePublished - Jul 11 2012
Event49th Annual Design Automation Conference, DAC '12 - San Francisco, CA, United States
Duration: Jun 3 2012Jun 7 2012

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Other

Other49th Annual Design Automation Conference, DAC '12
CountryUnited States
CitySan Francisco, CA
Period6/3/126/7/12

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Keywords

  • NBTI
  • RTL
  • aging
  • static analysis
  • statistical analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

Cite this

Kumar, J. A., Butler, K. M., Kim, H., & Vasudevan, S. (2012). Early prediction of NBTI effects using RTL source code analysis. In Proceedings of the 49th Annual Design Automation Conference, DAC '12 (pp. 808-813). (Proceedings - Design Automation Conference). https://doi.org/10.1145/2228360.2228506