Publication | Closed Access
Parametric yield estimation considering leakage variability
151
Citations
12
References
2004
Year
Unknown Venue
Precision AgricultureEngineeringVlsi DesignComputer ArchitectureYield PredictionLeakage DetectionHardware SecurityPhysical Design (Electronics)Reliability EngineeringUncertainty QuantificationYield OptimizationStatisticsPower-aware DesignParametric Yield EstimationElectrical EngineeringHardware ReliabilityComputer EngineeringTotal Chip LeakageMicroelectronicsCircuit ReliabilityLeakage Current DistributionYield Loss
Leakage current has become a stringent constraint in modern processor designs in addition to traditional constraints on frequency. Since leakage current exhibits a strong inverse correlation with circuit delay, effective parametric yield prediction must consider the dependence of leakage current on frequency. In this paper, we present a new chip-level statistical method to estimate the total leakage current in the presence of within-die and die-to-die variability. We develop a closed-form expression for total chip leakage that models the dependence of the leakage current distribution on a number of process parameters. The model is based on the concept of scaling factors to capture the effects of within-die variability. Using this model, we then present an integrated approach to accurately estimate the yield loss when both frequency and power limits are imposed on a design. Our method demonstrates the importance of considering both these limiters in calculating the yield of a lot.
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