Transistor Degradations in Very Large-Scale-Integrated CMOS Technologies

The historical evolution of hot carrier degradation mechanisms and their physical models are reviewed and an energy-driven hot carrier aging model is verified that can reproduce 62-nm-gate-long hot carrier degradation of transistors through consistent aging-parameter extractions for circuit simulation. A long-term hot carrier-resistant circuit design can be realized via optimal driver strength controls. The central role of the V GS ratio is emphasized during practical case studies on CMOS inverter chains and a dynamic random access memory (DRAM) word-line circuit. Negative bias temperature instability (NBTI) mechanisms are also reviewed and implemented in a hydrogen reaction-diffusion (R-D) framework. The R-D simulation reproduces time-dependent NBTI degradations interpreted into interface trap generation, Δ N it with a proper power-law dependency on time. The experimental evidence of pre-existing hydrogen-induced Si–H bond breakage is also proven by the quantifying R-D simulation. From this analysis, a low-pressure end-of-line (EOL) anneal can reduce the saturation level of NBTI degradation, which is believed to be caused by the outward diffusion of hydrogen from the gate regions and therefore prevents further breakage of Si–H bonds in the silicon-oxide interfaces

On variability and reliability of poly-Si thin-film transistors

In contrast to conventional bulk-silicon technology, polysilicon (poly-Si) thin-film transistors (TFTs) can be implanted in flexible substrate and can have low process temperature. These attributes make poly-Si TFT technology more attractive for new applications, such as flexible displays, biosensors, and smart clothing. However, due to the random nature of grain boundaries (GBs) in poly-Si film and self-heating enhanced negative bias temperature instability (NBTI), the variability and reliability of poly-Si TFTs are the main obstacles that impede the application of poly-Si TFTs in high-performance circuits. The primary focus of this dissertation is to develop new design methodologies and modeling techniques for facilitating new applications of poly-Si TFT technology. In order to do that, a physical model is first presented to characterize the GB-induced transistor threshold voltage (V th)variations considering not only the number but also the position and orientation of each GB in 3-D space. The fast computation time of the proposed model makes it suitable for evaluation of GB-induced transistor Vthvariation in the early design phase. Furthermore, a self-consistent electro-thermal model that considers the effects of device geometry, substrate material, and stress conditions on NBTI is proposed. With the proposed modeling methodology, the significant impacts of device geometry, substrate, and supply voltage on NBTI in poly-Si TFTs are shown. From a circuit design perspective, a voltage programming pixel circuit is developed for active-matrix organic light emitting diode (AMOLED) displays for compensating the shift of Vth and mobility in driver TFTs as well as compensating the supply voltage degradation. In addition, a self-repair design methodology is proposed to compensate the GB-induced variations for liquid crystal displays (LCDs) and AMOLED displays. Based on the simulation results, the proposed circuit can decrease the required supply voltage by 20% without performance and yield degradation. In the final section of this dissertation, an optimization methodology for circuit-level reliability tests is explored. To effectively predict circuit lifetime, accelerated aging (i.e. elevated voltage and temperature) is commonly applied in circuit-level reliability tests, such as constant voltage stress (CVS) and ramp voltage stress (RVS) tests. However, due to the accelerated aging, shifting of dominant degradation mechanism might occur leading to the wrong lifetime prediction. To get around this issue, we proposed a technique to determine the proper stress range for accelerated aging tests

Techniques for Aging, Soft Errors and Temperature to Increase the Reliability of Embedded On-Chip Systems

This thesis investigates the challenge of providing an abstracted, yet sufficiently accurate reliability estimation for embedded on-chip systems. In addition, it also proposes new techniques to increase the reliability of register files within processors against aging effects and soft errors. It also introduces a novel thermal measurement setup that perspicuously captures the infrared images of modern multi-core processors

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

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

Characterisation and mitigation of long-term degradation effects in programmable logic

Reliability has always been an issue in silicon device engineering, but until now it has been managed by the carefully tuned fabrication process. In the future the underlying physical limitations of silicon-based electronics, plus the practical challenges of manufacturing with such complexity at such a small scale, will lead to a crunch point where transistor-level reliability must be forfeited to continue achieving better productivity. Field-programmable gate arrays (FPGAs) are built on state-of-the-art silicon processes, but it has been recognised for some time that their distinctive characteristics put them in a favourable position over application-specific integrated circuits in the face of the reliability challenge. The literature shows how a regular structure, interchangeable resources and an ability to reconfigure can all be exploited to detect, locate, and overcome degradation and keep an FPGA application running. To fully exploit these characteristics, a better understanding is needed of the behavioural changes that are seen in the resources that make up an FPGA under ageing. Modelling is an attractive approach to this and in this thesis the causes and effects are explored of three important degradation mechanisms. All are shown to have an adverse affect on FPGA operation, but their characteristics show novel opportunities for ageing mitigation. Any modelling exercise is built on assumptions and so an empirical method is developed for investigating ageing on hardware with an accelerated-life test. Here, experiments show that timing degradation due to negative-bias temperature instability is the dominant process in the technology considered. Building on simulated and experimental results, this work also demonstrates a variety of methods for increasing the lifetime of FPGA lookup tables. The pre-emptive measure of wear-levelling is investigated in particular detail, and it is shown by experiment how di fferent reconfiguration algorithms can result in a significant reduction to the rate of degradation

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

Simulation study of scaling design, performance characterization, statistical variability and reliability of decananometer MOSFETs

This thesis describes a comprehensive, simulation based scaling study – including device design, performance characterization, and the impact of statistical variability – on deca-nanometer bulk MOSFETs. After careful calibration of fabrication processes and electrical characteristics for n- and p-MOSFETs with 35 nm physical gate length, 1 nm EOT and stress engineering, the simulated devices closely match the performance of contemporary 45 nm CMOS technologies. Scaling to 25 nm, 18 nm and 13 nm gate length n and p devices follows generalized scaling rules, augmented by physically realistic constraints and the introduction of high-k/metal-gate stacks. The scaled devices attain the performance stipulated by the ITRS. Device a.c. performance is analyzed, at device and circuit level. Extrinsic parasitics become critical to nano-CMOS device performance. The thesis describes device capacitance components, analyzes the CMOS inverter, and obtains new insights into the inverter propagation delay in nano-CMOS. The projection of a.c. performance of scaled devices is obtained. The statistical variability of electrical characteristics, due to intrinsic parameter fluctuation sources, in contemporary and scaled decananometer MOSFETs is systematically investigated for the first time. The statistical variability sources: random discrete dopants, gate line edge roughness and poly-silicon granularity are simulated, in combination, in an ensemble of microscopically different devices. An increasing trend in the standard deviation of the threshold voltage as a function of scaling is observed. The introduction of high-k/metal gates improves electrostatic integrity and slows this trend. Statistical evaluations of variability in Ion and Ioff as a function of scaling are also performed. For the first time, the impact of strain on statistical variability is studied. Gate line edge roughness results in areas of local channel shortening, accompanied by locally increased strain, both effects increasing the local current. Variations are observed in both the drive current, and in the drive current enhancement normally expected from the application of strain. In addition, the effects of shallow trench isolation (STI) on MOSFET performance and on its statistical variability are investigated for the first time. The inverse-narrow-width effect of STI enhances the current density adjacent to it. This leads to a local enhancement of the influence of junction shapes adjacent to the STI. There is also a statistical impact on the threshold voltage due to random STI induced traps at the silicon/oxide interface

Strain-Engineered MOSFETs

This book brings together new developments in the area of strain-engineered MOSFETs using high-mibility substrates such as SIGe, strained-Si, germanium-on-insulator and III-V semiconductors into a single text which will cover the materials aspects, principles, and design of advanced devices, their fabrication and applications. The book presents a full TCAD methodology for strain-engineering in Si CMOS technology involving data flow from process simulation to systematic process variability simulation and generation of SPICE process compact models for manufacturing for yield optimization