Monte Carlo Methods for Reliability Analysis and Power Estimation
Burch, Richard Gene
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https://hdl.handle.net/2142/71997
Description
Title
Monte Carlo Methods for Reliability Analysis and Power Estimation
Author(s)
Burch, Richard Gene
Issue Date
1993
Doctoral Committee Chair(s)
Trick, Timothy N.
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Abstract
Estimating the power dissipated during normal operating conditions is a major concern in the design of integrated circuits. Since excessive power dissipation causes overheating and can lead to soft errors and permanent damage, attempts to achieve first-pass reliability require accurate and efficient power estimation. With today's closer customer interaction, many circuits are being designed for already existing systems or for systems that are being concurrently designed. Accurate and efficient power estimation methods are needed to allow such close interaction.
In this thesis, we investigate a novel approach that combines the accuracy of simulation-based approaches with the weak pattern dependence of probabilistic approaches. The resulting approach is statistical in nature; it consists of applying randomly generated input patterns to the circuit and monitoring, with a simulator, the resulting power value. This is continued until a value of power is obtained with a desired accuracy, at a specified confidence level. Since this method uses a finite number of patterns to estimate the power and the power really depends on the infinite set of possible input patterns, this method belongs to the general class of so-called Monte Carlo methods. We describe the approach and its implementation, and we show that it is accurate and efficient for VLSI circuits.
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