Hybrid importance sampling Monte Carlo approach for yield estimation in circuit design View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Anuj K. Tyagi, Xavier Jonsson, Theo G. J. Beelen, Wil H. A. Schilders

ABSTRACT

The dimension of transistors shrinks with each new technology developed in the semiconductor industry. The extreme scaling of transistors introduces important statistical variations in their process parameters. A large digital integrated circuit consists of a very large number (in millions or billions) of transistors, and therefore the number of statistical parameters may become very large if mismatch variations are modeled. The parametric variations often cause to the circuit performance degradation. Such degradation can lead to a circuit failure that directly affects the yield of the producing company and its fame for reliable products. As a consequence, the failure probability of a circuit must be estimated accurately enough. In this paper, we consider the Importance Sampling Monte Carlo method as a reference probability estimator for estimating tail probabilities. We propose a Hybrid ISMC approach for dealing with circuits having a large number of input parameters and provide a fast estimation of the probability. In the Hybrid approach, we replace the expensive to use circuit model by its cheap surrogate for most of the simulations. The expensive circuit model is used only for getting the training sets (to fit the surrogates) and near to the failure threshold for reducing the bias introduced by the replacement. More... »

PAGES

11

References to SciGraph publications

  • 2006. Overview and Recent Advances in Partial Least Squares in SUBSPACE, LATENT STRUCTURE AND FEATURE SELECTION
  • 2006-09. The Cross-Entropy Method for Continuous Multi-Extremal Optimization in METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY
  • 2003. The Design and Analysis of Computer Experiments in NONE
  • 1983-12. Cross validation of kriging in a unique neighborhood in MATHEMATICAL GEOSCIENCES
  • Journal

    TITLE

    Journal of Mathematics in Industry

    ISSUE

    1

    VOLUME

    8

    From Grant

  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13362-018-0053-4

    DOI

    http://dx.doi.org/10.1186/s13362-018-0053-4

    DIMENSIONS

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