Miller Coefficient Estimation via Reduced Order System Synthesis
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Solution Overview
Problem
Current timing analysis methods for large-scale circuit designs, such as microprocessors, face challenges in accurately estimating the impact of noise on signal paths due to the complexity of interactions between victim and aggressor signal paths, which are not effectively addressed by existing worst-case modeling techniques.
Innovation Solution
A method is introduced to estimate the Miller coefficient by synthesizing reduced order systems from aggressor and victim networks, calculating active areas across coupling capacitors, and shifting noise signals to align mean arrival times, allowing for more accurate estimation of timing delays caused by noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If worst-case modeling techniques are used to account for noise delays, then timing analysis can be performed, but the accuracy of timing delay estimation deteriorates due to inability to effectively address complex interactions between victim and aggressor signal paths
Solution Approach 1:
The patent introduces a coupling capacitor as an intermediary element to model the interaction between aggressor and victim signal paths. By representing the complex coupling effects through this intermediate capacitive element, the patent enables accurate timing delay estimation while simplifying the analysis of complex signal path interactions. The coupling capacitor serves as a mediator that captures the essential noise coupling behavior without requiring direct analysis of the full complexity of the interacting signal paths.
2Measurement precision
If coupling capacitor values are scaled by Miller coefficient to estimate aggressor path noise impact, then timing analysis becomes feasible, but the estimation accuracy deteriorates when using traditional methods that do not account for mean time of arrival alignment
Solution Approach 1:
The patent applies preliminary action by calculating and aligning the mean time of arrival (MTA) of noise signals before performing the Miller coefficient scaling. This preliminary MTA alignment ensures that the timing characteristics of the aggressor noise are properly synchronized with the victim signal timing, thereby improving the accuracy of the noise impact estimation. By performing this timing alignment in advance, the patent enhances estimation accuracy while maintaining the computational efficiency of the Miller coefficient approach.
Data Source
AI summary
A method of estimating a Miller coefficient for an aggressor network and a victim network coupled by a coupling capacitor includes synthesizing a reduced order system from the aggressor network and the victim network, estimating an active area across the coupling capacitor for an aggressor induced noise signal based on the reduced order system, calculating an estimate of the Miller coefficient based on the active area of the aggressor induced noise signal, and outputting the calculated estimate of the Miller coefficient.