Circuit failure prediction predicts the occurrence of a circuit failure before errors actually appear in system data and states. This is in contrast to classical error detection where a failure is detected after errors appear in system data and states. Circuit failure prediction is performed during system operation by analyzing the data collected by sensors inserted at various locations inside a chip. We demonstrate this concept of circuit failure prediction for a dominant PMOS aging mechanism induced by negative bias temperature instability (NBTI). NBTI-induced PMOS aging slows down PMOS transistors over time. As a result, the speed of a chip can significantly degrade over time and can result in delay faults. The traditional practice is to incorporate worst-case speed margins to prevent delay faults during system operation due to NBTI aging. A new sensor design integrated inside a flip-flop enables efficient circuit failure prediction at a low cost. Simulation results using 90nm and 65nm technologies demonstrate that this technique can significantly improve system performance by enabling close to best-case design instead of traditional worst-case design.

Circuit Failure Prediction and Its Application to Transistor Aging

Negative bias temperature instability (NBTI) has become the dominant reliability concern for nanoscale PMOS transistors. In this paper, a predictive model is developed for the degradation of NBTI in both static and dynamic operations. Model scalability and generality are comprehensively verified with experimental data over a wide range of process and bias conditions. By implementing the new model into SPICE for an industrial 90nm technology, key insights are obtained for the development of robust design solutions: (1) the most effective techniques to mitigate the NBTI degradation are V/sub DD/ tuning, PMOS sizing, and reducing the duty cycle; (2) an optimal V/sub DD/ exists to minimize the degradation of circuit performance; (3) tuning gate length or the switching frequency has little impact on the NBTI effect; (4) a new switching scenario is identified for worst case timing analysis during NBTI stress.

Modeling and minimization of PMOS NBTI effect for robust nanometer design

https://www.iue.tuwien.ac.at/pdf/ib_2011/JB2011_Grasser_5.pdf

Stochastic charge trapping in oxides: From random telegraph noise to bias temperature instabilities

This paper presents a predictive model for the negative bias temperature instability (NBTI) of PMOS under both short term and long term operation. Based on the reaction-diffusion (R-D) mechanism, this model accurately captures the dependence of NBTI on the oxide thickness (tox), the diffusing species (H or H2) and other key transistor and design parameters. In addition, a closed form expression was derived for the threshold voltage change (DeltaVth ) under multiple cycle dynamic operation. Model accuracy and efficiency were verified with 90-nm experimental and simulation data. The impact of NBTI was further investigated on representative digital circuits

Predictive Modeling of the NBTI Effect for Reliable Design

One of the most important degradation modes in CMOS technologies, the bias temperature instability (BTI) has been known since the 1960s. Already in early interpretations, charge trapping in the oxide was considered an important aspect of the degradation. In their 1977 paper, Jeppson and Svensson suggested a hydrogen-diffusion controlled mechanism for the creation of interface states. Their reaction-diffusion model subsequently became the dominant explanation of the phenomenon. While Jeppson and Svensson gave a preliminary study of the recovery of the degradation, this issue received only limited attention for many years. In the last decade, however, a large number of detailed recovery studies have been published, showing clearly that the reaction-diffusion mechanism is inconsistent with the data. As a consequence, the research focus shifted back toward charge trapping. Currently available advanced charge-trapping theories based on switching oxide traps are now able to explain the bulk of the experimental data. We give a review of our perspective on some selected developments in this area.

The Paradigm Shift in Understanding the Bias Temperature Instability: From Reaction–Diffusion to Switching Oxide Traps

Negative bias temperature instability (NBTI) has become one of the major causes for reliability degradation of nanoscale circuits. In this letter, we propose a simple analytical model to predict the delay degradation of a wide class of digital logic gate based on both worst case and activity dependent threshold voltage change under NBTI. We show that by knowing the threshold voltage degradation of a single transistor due to NBTI, one can predict the performance degradation of a circuit with a reasonable degree of accuracy. We find that digital circuits are much less sensitive (approximately 9.2% performance degradation in ten years for 70 nm technology) to NBTI degradation than previously anticipated.

Impact of NBTI on the temporal performance degradation of digital circuits

A comprehensive model for PMOS NBTI degradation: Recent progress.

Recent advances in experimental techniques (on-the- fly and ultrafast techniques) allow measurement of threshold voltage degradation due to negative-bias temperature instability (NBTI) over many decades in timescale Such measurements over wider temperature range (-25degC to 145degC), film thicknesses (12-22 nm of effective oxide thickness), and processing conditions (variation of nitrogen within gate dielectric) provide an excellent framework for a theoretical analysis of NBTI degradation In this paper, we analyze these experiments to refine the existing theory of NBTI to 1) explore the mechanics of time transients of NBTI over many orders of magnitude in time; 2) establish field dependence of interface trap generation to resolve questions regarding the appropriateness of power law versus exponential projection of lifetimes; 3) ascertain the relative contributions to NBTI from interface traps versus hole trapping as a function of processing conditions; and 4) briefly discuss relaxation dynamics for fast-transient NBTI recovery that involves interface traps and trapped holes

/pdf/recent-issues-in-negative-bias-temperature-instability-516v1ys8p8.pdf

Recent Issues in Negative-Bias Temperature Instability: Initial Degradation, Field Dependence of Interface Trap Generation, Hole Trapping Effects, and Relaxation

Negative Bias Temperature Instability (NBTI) has become one of the major causes for temporal reliability degradation of nanoscale circuits. In this paper, we analyze the temporal delay degradation of logic circuits due to NBTI. We show that knowing the threshold voltage degradation of a single transistor due to NBTI, one can predict the performance degradation of a circuit with a reasonable degree of accuracy. We also propose a sizing algorithm taking NBTI-affected performance degradation into account to ensure the reliability of nanoscale circuits for a given period of time. Experimental results on several benchmark circuits show that with an average of 8.7% increase in area one can ensure reliable performance of circuits for 10 years.

/pdf/temporal-performance-degradation-under-nbti-estimation-and-q0dwdjunv3.pdf

Temporal Performance Degradation under NBTI: Estimation and Design for Improved Reliability of Nanoscale Circuits

One of the major reliability concerns in nanoscale very large-scale integration design is the time-dependent negative- bias-temperature-instability (NBTI) degradation. Due to the higher operating temperature and increasing vertical oxide field, threshold voltage (Vt) of PMOS transistors can increase with time under NBTI. In this paper, we examine the impact of NBTI degradation in memory elements of digital circuits, focusing on the conventional 6T-SRAM-array topology. An analytical expression for the time-dependent Vt degradation in PMOS transistors based on the empirical reaction-diffusion (RD) framework was employed for our analysis. Using the RD-based Vt model, we analytically examine the impact of NBTI degradation in critical performance parameters of SRAM array. These parameters include the following: (1) static noise margin; (2) statistical READ and WRITE stability; (3) parametric yield; and (4) standby leakage current (IDDQ). We show that due to NBTI, READ stability of SRAM cell degrades, while write stability and standby leakage improve with time. Furthermore, by carefully examining the degradation in leakage current due to NBTI, it is possible to characterize and predict the lifetime behavior of NBTI degradation in real circuit operation.

H. Kufluoglu

Papers

Impact of NBTI on the temporal performance degradation of digital circuits

A comprehensive model for PMOS NBTI degradation: Recent progress.

Recent Issues in Negative-Bias Temperature Instability: Initial Degradation, Field Dependence of Interface Trap Generation, Hole Trapping Effects, and Relaxation

Temporal Performance Degradation under NBTI: Estimation and Design for Improved Reliability of Nanoscale Circuits

Impact of Negative-Bias Temperature Instability in Nanoscale SRAM Array: Modeling and Analysis