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This brief presents a fast energy-efficient level converter capable of converting an input signal from subthreshold voltages up to the nominal supply voltage. Measured results from a 130-nm test chip show robust conversion from 188 mV to 1.2 V with no intermediate supplies required. A combination of circuit methods makes the converter robust to the large variations in the current characteristics of subthreshold circuits. To support dynamic voltage scaling, the level converter can upconvert an input at any voltage within this range to 1.2 V.

On-chip circuit aging sources, like negative bias temperature instability (NBTI), hot-carrier injection (HCI), electromigration, and oxide breakdown, are reducing expected chip lifetimes. Being able to track the actual aging process is one way to avoid unnecessarily large design margins. This work proposes a sensing scheme that uses sets of reliability sensors capable of accurately tracking NBTI PMOS current degradations across process, temperature, and varying activity factors. We show that a set of 1000 such small sensors can predict chip lifetime to an uncertainty of 7% to 10%. We also show that, once the total area dedicated to sensing is chosen, the lifetime prediction uncertainty is almost insensitive to the tradeoff between the number of sensors and the area of each individual sensor.

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Recent works show bias temperature instability (BTI) is a detrimental hard-aging mechanism in CMOS circuit design. Negative BTI (NBTI) alone degrades circuit speed upwards of 20% over a 10 year life-span. Having the ability to track the actual aging process provides one method to reduce large design margins that are otherwise required to offset circuit aging. This work extends previous research by contributing a sensing scheme that employs on-chip sensors capable of accurately tracking NBTI pMOS current degradations across process, temperature, and varying activity factors. Results show that a 7600 m sensing area achieves an overall system accuracy of 90% at a voltage threshold precision of 2 mV. We thoroughly describe the sensor design and the underlying statistics used to determine overall accuracy and precision. Furthermore, a novel sensor distribution method is presented that uses an existing scan-chain methodology to mask the overhead of adding the on-chip sensors.

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