Parameters for modeling digital circuit reliability a statistical perspective

Azam Beg, Faheem Ahmed, Amr Elchouemi, Ajmal Beg

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

    Abstract

    This paper presents a statistical perspective on the relationship of the reliability of a nano-circuit (measured by its probability of failure) and the circuit parameters. The study was motivated by our observation that the reliability estimates using (a commonly used set of) mathematical equations deviated appreciably from the results of a Bayesian Network based reliability calculation software, especially as the circuit size increased. (For comparative purposes, we had utilized the data from thousands of randomly generated circuits.) In this research, we have investigated circuit reliability's sensitivity to circuit parameters besides the ones used in the mathematical equations. For this purpose, we formulated several hypotheses regarding circuit parameters and the reliability, and then used statistical metrics to test them. The findings from this analysis are expected to help create higher accuracy mathematical models for predicting circuit reliability.

    Original languageEnglish
    Title of host publicationProceedings of the IASTED International Conference on Modelling and Simulation, MS 2012
    Pages116-121
    Number of pages6
    DOIs
    Publication statusPublished - Oct 1 2012
    EventIASTED International Conference on Modelling and Simulation, MS 2012 - Banff, AB, Canada
    Duration: Jul 3 2012Jul 5 2012

    Publication series

    NameProceedings of the IASTED International Conference on Modelling and Simulation
    ISSN (Print)1021-8181

    Other

    OtherIASTED International Conference on Modelling and Simulation, MS 2012
    Country/TerritoryCanada
    CityBanff, AB
    Period7/3/127/5/12

    Keywords

    • And nanoelectronics
    • Circuit reliability
    • Computer aided design
    • Digital circuit
    • Monte carlo simulation
    • Probability of failure
    • Statistical and probabilistic modeling

    ASJC Scopus subject areas

    • Software
    • Modelling and Simulation
    • Computer Science Applications

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