Abstract
The Monte Carlo method exhibits generality and insensitivity to the number of stochastic variables, but is expensive for accurate Average Quality Measure (AQI) or Parametric Yield estimation of MOS VLSI circuits. In this contribution a new method of variance reduction technique, viz. the Latin Hypercube Sampling (LHS) method is presented which improves the efficiency of AQI estimation in integrated circuits especially for MOS digital circuits. This method is similar to the Primitive Monte Carlo (PMC) method except in samples generation step where the Latin Hypercube Sampling method is used. This sampling method is very simple and does not involve any further simulations. Moreover, it has a smaller variance with respect to the PMC estimator. Encouraging results have thus far been obtained. A 3-dimensional quadratic function, a high pass filter, and a CMOS delay circuit examples are included to demonstrate the efficiency of this technique.
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Keramat, M., Kielbasa, R. (1997). Latin Hypercube Sampling Monte Carlo Estimation of Average Quality Index for Integrated Circuits. In: Becerra, J.J., Friedman, E.G. (eds) Analog Design Issues in Digital VLSI Circuits and Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-6101-9_11
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DOI: https://doi.org/10.1007/978-1-4615-6101-9_11
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