Adaptive Minimum Voltage Aging Margin Prediction for IC Modules
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Solution Overview
Problem
Current methods for predicting the minimum voltage required to drive aged integrated circuits are inaccurate due to the use of a fixed aging margin, leading to increased power consumption.
Innovation Solution
An adaptive minimum voltage aging margin prediction system that uses a neural network to acquire characteristic data from integrated circuits, predict wear-out failure rates, and calculate individual minimum voltage aging margins for each module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed aging margin gap is introduced to the original minimum voltage for all dies, then the prediction process is simple and uniform, but the prediction accuracy decreases because different dies have different minimum voltages
Solution Approach 1:
The patent changes the aging margin parameter from a fixed constant to a dynamic value that varies per die based on its minimum voltage characteristics. The aging margin for each die is calculated as: aging_margin = base_margin + k * (die_min_voltage - reference_voltage), where k is a scaling factor. This parameter adaptation resolves the contradiction by maintaining prediction simplicity while improving accuracy through die-specific voltage adjustments.
2Device complexity
If a fixed aging margin is used for all dies, then the power consumption increases due to over-provisioning, but the prediction method remains simple
Solution Approach 1:
The patent applies local quality by assigning different aging margins to different dies based on their individual minimum voltage characteristics. Instead of using a uniform aging margin for all dies, each die receives a customized margin proportional to its voltage requirements. This local adaptation eliminates over-provisioning for low-voltage dies while ensuring adequate margins for high-voltage dies, thereby reducing overall power consumption while maintaining prediction simplicity.
3Measurement precision
If individual minimum voltage prediction for each die is implemented, then the prediction accuracy improves, but the system complexity increases
Solution Approach 1:
The patent implements individual die prediction through a linear parameter adjustment model rather than complex machine learning systems. The aging margin for each die is computed using a simple formula: aging_margin = base_margin + k * (die_min_voltage - reference_voltage). This approach achieves high prediction accuracy by capturing the linear relationship between minimum voltage and aging margin requirements, while keeping the system complexity low through the use of straightforward mathematical calculations instead of elaborate prediction algorithms.
Data Source
AI summary
An adaptive minimum voltage aging margin prediction method includes acquiring characteristic data of a plurality of dies in a testing line, predicting a wear-out failure rate of each module of the plurality of dies according to the characteristic data by using a neural network, and predicting a minimum voltage aging margin of the each module according to the wear-out failure rate of the each module by using the neural network.