NEGATIVE BIAS TEMPERATURE INSTABILITY STUDIES FOR ANALOG SOC CIRCUITS

Negative Bias Temperature Instability (NBTI) is one of the recent reliability issues in sub threshold CMOS circuits. NBTI effect on analog circuits, which require matched device pairs and mismatches, will cause circuit failure. This work is to assess the NBTI effect considering the voltage and the temperature variations. It also provides a working knowledge of NBTI awareness to the circuit design community for reliable design of the SOC analog circuit. There have been numerous studies to date on the NBTI effect to analog circuits. However, other researchers did not study the implication of NBTI stress on analog circuits utilizing bandgap reference circuit. The reliability performance of all matched pair circuits, particularly the bandgap reference, is at the mercy of aging differential. Reliability simulation is mandatory to obtain realistic risk evaluation for circuit design reliability qualification. It is applicable to all circuit aging problems covering both analog and digital. Failure rate varies as a function of voltage and temperature. It is shown that PMOS is the reliabilitysusceptible device and NBTI is the most vital failure mechanism for analog circuit in sub-micrometer CMOS technology. This study provides a complete reliability simulation analysis of the on-die Thermal Sensor and the Digital Analog Converter (DAC) circuits and analyzes the effect of NBTI using reliability simulation tool. In order to check out the robustness of the NBTI-induced SOC circuit design, a bum-in experiment was conducted on the DAC circuits. The NBTI degradation observed in the reliability simulation analysis has given a clue that under a severe stress condition, a massive voltage threshold mismatch of beyond the 2mV limit was recorded. Bum-in experimental result on DAC proves the reliability sensitivity of NBTI to the DAC circuitry

A novel deep submicron bulk planar sizing strategy for low energy subthreshold standard cell libraries

Engineering andPhysical Science ResearchCouncil (EPSRC) and Arm Ltd for providing funding in the form of grants and studentshipsThis work investigates bulk planar deep submicron semiconductor physics in an attempt to improve standard cell libraries aimed at operation in the subthreshold regime and in Ultra Wide Dynamic Voltage Scaling schemes. The current state of research in the field is examined, with particular emphasis on how subthreshold physical effects degrade robustness, variability and performance. How prevalent these physical effects are in a commercial 65nm library is then investigated by extensive modeling of a BSIM4.5 compact model. Three distinct sizing strategies emerge, cells of each strategy are laid out and post-layout parasitically extracted models simulated to determine the advantages/disadvantages of each. Full custom ring oscillators are designed and manufactured. Measured results reveal a close correlation with the simulated results, with frequency improvements of up to 2.75X/2.43X obs erved for RVT/LVT devices respectively. The experiment provides the first silicon evidence of the improvement capability of the Inverse Narrow Width Effect over a wide supply voltage range, as well as a mechanism of additional temperature stability in the subthreshold regime. A novel sizing strategy is proposed and pursued to determine whether it is able to produce a superior complex circuit design using a commercial digital synthesis flow. Two 128 bit AES cores are synthesized from the novel sizing strategy and compared against a third AES core synthesized from a state-of-the-art subthreshold standard cell library used by ARM. Results show improvements in energy-per-cycle of up to 27.3% and frequency improvements of up to 10.25X. The novel subthreshold sizing strategy proves superior over a temperature range of 0 °C to 85 °C with a nominal (20 °C) improvement in energy-per-cycle of 24% and frequency improvement of 8.65X. A comparison to prior art is then performed. Valid cases are presented where the proposed sizing strategy would be a candidate to produce superior subthreshold circuits

Cmos Rf Cituits Sic] Variability And Reliability Resilient Design, Modeling, And Simulation

The work presents a novel voltage biasing design that helps the CMOS RF circuits resilient to variability and reliability. The biasing scheme provides resilience through the threshold voltage (VT) adjustment, and at the mean time it does not degrade the PA performance. Analytical equations are established for sensitivity of the resilient biasing under various scenarios. Power Amplifier (PA) and Low Noise Amplifier (LNA) are investigated case by case through modeling and experiment. PTM 65nm technology is adopted in modeling the transistors within these RF blocks. A traditional class-AB PA with resilient design is compared the same PA without such design in PTM 65nm technology. Analytical equations are established for sensitivity of the resilient biasing under various scenarios. A traditional class-AB PA with resilient design is compared the same PA without such design in PTM 65nm technology. The results show that the biasing design helps improve the robustness of the PA in terms of linear gain, P1dB, Psat, and power added efficiency (PAE). Except for post-fabrication calibration capability, the design reduces the majority performance sensitivity of PA by 50% when subjected to threshold voltage (VT) shift and 25% to electron mobility (μn) degradation. The impact of degradation mismatches is also investigated. It is observed that the accelerated aging of MOS transistor in the biasing circuit will further reduce the sensitivity of PA. In the study of LNA, a 24 GHz narrow band cascade LNA with adaptive biasing scheme under various aging rate is compared to LNA without such biasing scheme. The modeling and simulation results show that the adaptive substrate biasing reduces the sensitivity of noise figure and minimum noise figure subject to process variation and iii device aging such as threshold voltage shift and electron mobility degradation. Simulation of different aging rate also shows that the sensitivity of LNA is further reduced with the accelerated aging of the biasing circuit. Thus, for majority RF transceiver circuits, the adaptive body biasing scheme provides overall performance resilience to the device reliability induced degradation. Also the tuning ability designed in RF PA and LNA provides the circuit post-process calibration capability

IC design for reliability

textAs the feature size of integrated circuits goes down to the nanometer scale, transient and permanent reliability issues are becoming a significant concern for circuit designers. Traditionally, the reliability issues were mostly handled at the device level as a device engineering problem. However, the increasing severity of reliability challenges and higher error rates due to transient upsets favor higher-level design for reliability (DFR). In this work, we develop several methods for DFR at the circuit level. A major source of transient errors is the single event upset (SEU). SEUs are caused by high-energy particles present in the cosmic rays or emitted by radioactive contaminants in the chip packaging materials. When these particles hit a N+/P+ depletion region of an MOS transistor, they may generate a temporary logic fault. Depending on where the MOS transistor is located and what state the circuit is at, an SEU may result in a circuit-level error. We analyze SEUs both in combinational logic and memories (SRAM). For combinational logic circuit, we propose FASER, a Fast Analysis tool of Soft ERror susceptibility for cell-based designs. The efficiency of FASER is achieved through its static and vector-less nature. In order to evaluate the impact of SEU on SRAM, a theory for estimating dynamic noise margins is developed analytically. The results allow predicting the transient error susceptibility of an SRAM cell using a closedform expression. Among the many permanent failure mechanisms that include time-dependent oxide breakdown (TDDB), electro-migration (EM), hot carrier effect (HCE), and negative bias temperature instability (NBTI), NBTI has recently become important. Therefore, the main focus of our work is NBTI. NBTI occurs when the gate of PMOS is negatively biased. The voltage stress across the gate generates interface traps, which degrade the threshold voltage of PMOS. The degraded PMOS may eventually fail to meet timing requirement and cause functional errors. NBTI becomes severe at elevated temperatures. In this dissertation, we propose a NBTI degradation model that takes into account the temperature variation on the chip and gives the accurate estimation of the degraded threshold voltage. In order to account for the degradation of devices, traditional design methods add guard-bands to ensure that the circuit will function properly during its lifetime. However, the worst-case based guard-bands lead to significant penalty in performance. In this dissertation, we propose an effective macromodel-based reliability tracking and management framework, based on a hybrid network of on-chip sensors, consisting of temperature sensors and ring oscillators. The model is concerned specifically with NBTIinduced transistor aging. The key feature of our work, in contrast to the traditional tracking techniques that rely solely on direct measurement of the increase of threshold voltage or circuit delay, is an explicit macromodel which maps operating temperature to circuit degradation (the increase of circuit delay). The macromodel allows for costeffective tracking of reliability using temperature sensors and is also essential for enabling the control loop of the reliability management system. The developed methods improve the over-conservatism of the device-level, worstcase reliability estimation techniques. As the severity of reliability challenges continue to grow with technology scaling, it will become more important for circuit designers/CAD tools to be equipped with the developed methods.Electrical and Computer Engineerin

Dynamic Lifetime Reliability and Energy Management for Network-on-Chip based Chip Multiprocessors

In this dissertation, we study dynamic reliability management (DRM) and dynamic energy management (DEM) techniques for network-on-chip (NoC) based chip multiprocessors (CMPs). In the first part, the proposed DRM algorithm takes both the computational and the communication components of the CMP into consideration and combines thread migration and dynamic voltage and frequency scaling (DVFS) as the two primary techniques to change the CMP operation. The goal is to increase the lifetime reliability of the overall system to the desired target with minimal performance degradation. The simulation results on a variety of benchmarks on 16 and 64 core NoC based CMP architectures demonstrate that lifetime reliability can be improved by 100% for an average performance penalty of 7.7% and 8.7% for the two CMP architectures. In the second part of this dissertation, we first propose novel algorithms that employ Kalman filtering and long short term memory (LSTM) for workload prediction. These predictions are then used as the basis on which voltage/frequency (V/F) pairs are selected for each core by an effective dynamic voltage and frequency scaling algorithm whose objective is to reduce energy consumption but without degrading performance beyond the user set threshold. Secondly, we investigate the use of deep neural network (DNN) models for energy optimization under performance constraints in CMPs. The proposed algorithm is implemented in three phases. The first phase collects the training data by employing Kalman filtering for workload prediction and an efficient heuristic algorithm based on DVFS. The second phase represents the training process of the DNN model and in the last phase, the DNN model is used to directly identify V/F pairs that can achieve lower energy consumption without performance degradation beyond the acceptable threshold set by the user. Simulation results on 16 and 64 core NoC based architectures demonstrate that the proposed approach can achieve up to 55% energy reduction for 10% performance degradation constraints. Simulation experiments compare the proposed algorithm against existing approaches based on reinforcement learning and Kalman filtering and show that the proposed DNN technique provides average improvements in energy-delay-product (EDP) of 6.3% and 6% for the 16 core architecture and of 7.4% and 5.5% for the 64 core architecture

Thermal Management for Dependable On-Chip Systems

This thesis addresses the dependability issues in on-chip systems from a thermal perspective. This includes an explanation and analysis of models to show the relationship between dependability and tempature. Additionally, multiple novel methods for on-chip thermal management are introduced aiming to optimize thermal properties. Analysis of the methods is done through simulation and through infrared thermal camera measurements

Degradation in FPGAs: Monitoring, Modeling and Mitigation

This dissertation targets the transistor aging degradation as well as the associated thermal challenges in FPGAs (since there is an exponential relation between aging and chip temperature). The main objectives are to perform experimentation, analysis and device-level model abstraction for modeling the degradation in FPGAs, then to monitor the FPGA to keep track of aging rates and ultimately to propose an aging-aware FPGA design flow to mitigate the aging