Trident: Comprehensive Choke Error Mitigation in NTC Systems

Bal, Aatreyi; Roy, Sanghamitra; Chakraborty, Koushik

doi:10.1109/tvlsi.2018.2863954

Cited by 2 publications

(1 citation statement)

References 39 publications

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“…Tests start by measuring a pulse Id ~ Vg with Vd=0.1 V and a pulse edge time of 3 μs. The Vg is then stepped from zero to 0.5 V and Id is monitored against time under Vd=0.1 V. The average threshold voltage of the nMOSFETs used here is 0.45 V and Vg is chosen to be Vth+0.05 V, as the requirement of low power is driving Vdd towards Vth and the near threshold computing acutely suffers from RTN [28]. The temperature is between 28 o C and 125 o C.…”

Section: B Devices and Measurementmentioning

confidence: 99%

An Assessment of the Statistical Distribution of Random Telegraph Noise Time Constants

et al. 2020

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As transistor sizes are downscaled, a single trapped charge has a larger impact on smaller devices and the Random Telegraph Noise (RTN) becomes increasingly important. To optimize circuit design, one needs assessing the impact of RTN on the circuit and this can only be accomplished if there is an accurate statistical model of RTN. The dynamic Monte Carlo modelling requires the statistical distribution functions of both the amplitude and the capture/emission time (CET) of traps. Early works were focused on the amplitude distribution and the experimental data of CETs were typically too limited to establish their statistical distribution reliably. In particular, the time window used has been often small, e.g. 10 sec or less, so that there are few data on slow traps. It is not known whether the CET distribution extracted from such a limited time window can be used to predict the RTN beyond the test time window. The objectives of this work are three fold: to provide the long term RTN data and use them to test the CET distributions proposed by early works; to propose a methodology for characterizing the CET distribution for a fabrication process efficiently; and, for the first time, to verify the long term prediction capability of a CET distribution beyond the time window used for its extraction.

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Section: B Devices and Measurementmentioning

confidence: 99%

An Assessment of the Statistical Distribution of Random Telegraph Noise Time Constants

et al. 2020

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On the Accuracy in Modeling the Statistical Distribution of Random Telegraph Noise Amplitude

Mehedi

Tok

et al. 2021

IEEE Access

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The power consumption of digital circuits is proportional to the square of operation voltage and the demand for low power circuits reduces the operation voltage towards the threshold of MOSFETs. A weak voltage signal makes circuits vulnerable to noise and the optimization of circuit design requires modelling noise. Random Telegraph Noise (RTN) is the dominant noise for modern CMOS technologies and Monte Carlo modelling has been used to assess its impact on circuits. This requires statistical distributions of RTN amplitude and three different distributions were proposed by early works: Lognormal, Exponential, and Gumbel distributions. They give substantially different RTN predictions and agreement has not been reached on which distribution should be used, calling the modelling accuracy into questions. The objective of this work is to assess the accuracy of these three distributions and to explore other distributions for better accuracy. A novel criterion has been proposed for selecting distributions, which requires a monotonic reduction of modelling errors with increasing number of traps. The three existing distributions do not meet this criterion and thirteen other distributions are explored. It is found that the Generalized Extreme Value (GEV) distribution has the lowest error and meet the new criterion. Moreover, to reduce modelling errors, early works used bimodal Lognormal and Exponential distributions, which have more fitting parameters. Their errors, however, are still higher than those of the monomodal GEV distribution. GEV has a long distribution tail and predicts substantially worse RTN impact. The work highlights the uncertainty in predicting the RTN distribution tail by different statistical models.

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Trident: Comprehensive Choke Error Mitigation in NTC Systems

Cited by 2 publications

References 39 publications

An Assessment of the Statistical Distribution of Random Telegraph Noise Time Constants

An Assessment of the Statistical Distribution of Random Telegraph Noise Time Constants

On the Accuracy in Modeling the Statistical Distribution of Random Telegraph Noise Amplitude

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