BTI-Induced Aging under Random Stress Waveforms

Abstract

The BTI effect, which consists of both stress and recovery phases, poses a unique challenge to long-term aging prediction, because the degradation rate strongly depends on the stress pattern. Previous approaches usually resort to an average, constant stress waveform to simplify the situation. They are efficient, but fail to capture the reality, especially under dynamic voltage scaling (DVS) or in analog/mixed signal designs where the stress waveform is much more random. This paper presents a suite of solutions that enable aging simulation under all possible stress conditions. Key contributions include: (1) Compact modeling of BTI when the stress voltage is varying. The results to both reaction-diffusion (RD) and trapping/detrapping (TD) mechanisms are derived.(2) Efficient simulation under DVS, leveraging the new BTI models; (3) Silicon validation at 45nm and 65nm, at both device and circuit levels. As the results illustrate, it is necessary to combine both RD and TD mechanisms to accurately predict aging under changing stress voltages. Our proposed work provides a general and comprehensive solution to aging analysis under random stress patterns.

Predictive Reliability and Fault Management in Exascale Systems

“…Aging and Reliability. Bias Temperature Instability (namely, BTI), is a degradation effect that changes the threshold voltage of CMOS transistors, and has been regarded as one of the most relevant aging effects in CMOS technology [ 163 ]. From a technological perspective, the BTI occurs when, under a constant gate voltage, a stress in temperature (i.e., increasing temperature from ambient to 200 • C) results in charges being trapped in the transistor gate oxide and reduces the voltage threshold of transistors [ 67 ].…”