Layout-accurate Ultra-fast System-level Design Exploration Through Verilog-ams

This research addresses problems in designing analog and mixed-signal (AMS) systems by bridging the gap between system-level and circuit-level simulation by making simulations fast like system-level and accurate like circuit-level. The tools proposed include metamodel integrated Verilog-AMS based design exploration flows. The research involves design centering, metamodel generation flows for creating efficient behavioral models, and Verilog-AMS integration techniques for model realization. The core of the proposed solution is transistor-level and layout-level metamodeling and their incorporation in Verilog-AMS. Metamodeling is used to construct efficient and layout-accurate surrogate models for AMS system building blocks. Verilog-AMS, an AMS hardware description language, is employed to build surrogate model implementations that can be simulated with industrial standard simulators. The case-study circuits and systems include an operational amplifier (OP-AMP), a voltage-controlled oscillator (VCO), a charge-pump phase-locked loop (PLL), and a continuous-time delta-sigma modulator (DSM). The minimum and maximum error rates of the proposed OP-AMP model are 0.11 % and 2.86 %, respectively. The error rates for the PLL lock time and power estimation are 0.7 % and 3.0 %, respectively. The OP-AMP optimization using the proposed approach is ~17000× faster than the transistor-level model based approach. The optimization achieves a ~4× power reduction for the OP-AMP design. The PLL parasitic-aware optimization achieves a 10× speedup and a 147 µW power reduction. Thus the experimental results validate the effectiveness of the proposed solution

A Holistic Approach to Functional Safety for Networked Cyber-Physical Systems

Functional safety is a significant concern in today's networked cyber-physical systems such as connected machines, autonomous vehicles, and intelligent environments. Simulation is a well-known methodology for the assessment of functional safety. Simulation models of networked cyber-physical systems are very heterogeneous relying on digital hardware, analog hardware, and network domains. Current functional safety assessment is mainly focused on digital hardware failures while minor attention is devoted to analog hardware and not at all to the interconnecting network. In this work we believe that in networked cyber-physical systems, the dependability must be verified not only for the nodes in isolation but also by taking into account their interaction through the communication channel. For this reason, this work proposes a holistic methodology for simulation-based safety assessment in which safety mechanisms are tested in a simulation environment reproducing the high-level behavior of digital hardware, analog hardware, and network communication. The methodology relies on three main automatic processes: 1) abstraction of analog models to transform them into system-level descriptions, 2) synthesis of network infrastructures to combine multiple cyber-physical systems, and 3) multi-domain fault injection in digital, analog, and network. Ultimately, the flow produces a homogeneous optimized description written in C++ for fast and reliable simulation which can have many applications. The focus of this thesis is performing extensive fault simulation and evaluating different functional safety metrics, \eg, fault and diagnostic coverage of all the safety mechanisms

System level performance and yield optimisation for analogue integrated circuits

Advances in silicon technology over the last decade have led to increased integration of analogue and digital functional blocks onto the same single chip. In such a mixed signal environment, the analogue circuits must use the same process technology as their digital neighbours. With reducing transistor sizes, the impact of process variations on analogue design has become prominent and can lead to circuit performance falling below specification and hence reducing the yield.This thesis explores the methodology and algorithms for an analogue integrated circuit automation tool that optimizes performance and yield. The trade-offs between performance and yield are analysed using a combination of an evolutionary algorithm and Monte Carlo simulation. Through the integration of yield parameter into the optimisation process, the trade off between the performance functions can be better treated that able to produce a higher yield. The results obtained from the performance and variation exploration are modelled behaviourally using a Verilog-A language. The model has been verified with transistor level simulation and a silicon prototype.For a large analogue system, the circuit is commonly broken down into its constituent sub-blocks, a process known as hierarchical design. The use of hierarchical-based design and optimisation simplifies the design task and accelerates the design flow by encouraging design reuse.A new approach for system level yield optimisation using a hierarchical-based design is proposed and developed. The approach combines Multi-Objective Bottom Up (MUBU) modelling technique to model the circuit performance and variation and Top Down Constraint Design (TDCD) technique for the complete system level design. The proposed method has been used to design a 7th order low pass filter and a charge pump phase locked loop system. The results have been verified with transistor level simulations and suggest that an accurate system level performance and yield prediction can be achieved with the proposed methodology

Analog System-on-a-Chip with Application to Biosensors

This dissertation facilitates the design and fabrication of analog systems-on-a-chip (SoCs). In this work an analog SoC is developed with application to organic fluid analysis. The device contains a built-in self-test method for performing on-chip analysis of analog macros. The analog system-on-a-chip developed in this dissertation can be used to evaluate the properties of fluids for medical diagnoses. The research herein described covers the development of: analog SoC models, an improved set of chemical sensor arrays, a self-contained system-on-a-chip for the determination of fluid properties, and a method of performing on-chip testing of analog SoC sub-blocks

Behavioural simulation of mixed analogue/digital circuits.

Continuing improvements in integrated circuit technology have made possible the implementation of complex electronic systems on a single chip. This often requires both analogue and digital signal processing. It is essential to simulate such IC's during the design process to detect errors at an early stage. Unfortunately, the simulators that are currently available are not well-suited to large mixed-signal circuits. This thesis describes the design and development of a new methodology for simulating analogue and digital components in a single, integrated environment. The methodology represents components as behavioural models that are more efficient than the circuit models used in conventional simulators. The signals that flow between models are all represented as piecewise-linear (PWL) waveforms. Since models representing digital and analogue components use the same format to represent their signals, they can be directly connected together. An object-oriented approach was used to create a class hierarchy to implement the component models. This supports rapid development of new models since all models are derived from a common base class and inherit the methods and attributes defined in their parentc lassesT. he signal objectsa re implementedw ith a similar class hierarchy. The development and validation of models representing various digital, analogue and mixed-signal components are described. Comparisons are made between the accuracy and performance of the proposed methodology and several commercial simulators. The development of a Windows-based demonstrations imulation tool called POISE is also described. This permitted models to be tested independently and multiple models to be connected together to form structural models of complex circuits

Fault-based Analysis of Industrial Cyber-Physical Systems

The fourth industrial revolution called Industry 4.0 tries to bridge the gap between traditional Electronic Design Automation (EDA) technologies and the necessity of innovating in many indus- trial fields, e.g., automotive, avionic, and manufacturing. This complex digitalization process in- volves every industrial facility and comprises the transformation of methodologies, techniques, and tools to improve the efficiency of every industrial process. The enhancement of functional safety in Industry 4.0 applications needs to exploit the studies related to model-based and data-driven anal- yses of the deployed Industrial Cyber-Physical System (ICPS). Modeling an ICPS is possible at different abstraction levels, relying on the physical details included in the model and necessary to describe specific system behaviors. However, it is extremely complicated because an ICPS is com- posed of heterogeneous components related to different physical domains, e.g., digital, electrical, and mechanical. In addition, it is also necessary to consider not only nominal behaviors but even faulty behaviors to perform more specific analyses, e.g., predictive maintenance of specific assets. Nevertheless, these faulty data are usually not present or not available directly from the industrial machinery. To overcome these limitations, constructing a virtual model of an ICPS extended with different classes of faults enables the characterization of faulty behaviors of the system influenced by different faults. In literature, these topics are addressed with non-uniformly approaches and with the absence of standardized and automatic methodologies for describing and simulating faults in the different domains composing an ICPS. This thesis attempts to overcome these state-of-the-art gaps by proposing novel methodologies, techniques, and tools to: model and simulate analog and multi-domain systems; abstract low-level models to higher-level behavioral models; and monitor industrial systems based on the Industrial Internet of Things (IIOT) paradigm. Specifically, the proposed contributions involve the exten- sion of state-of-the-art fault injection practices to improve the ICPSs safety, the development of frameworks for safety operations automatization, and the definition of a monitoring framework for ICPSs. Overall, fault injection in analog and digital models is the state of the practice to en- sure functional safety, as mentioned in the ISO 26262 standard specific for the automotive field. Starting from state-of-the-art defects defined for analog descriptions, new defects are proposed to enhance the IEEE P2427 draft standard for analog defect modeling and coverage. Moreover, dif- ferent techniques to abstract a transistor-level model to a behavioral model are proposed to speed up the simulation of faulty circuits. Therefore, unlike the electrical domain, there is no extensive use of fault injection techniques in the mechanical one. Thus, extending the fault injection to the mechanical and thermal fields allows for supporting the definition and evaluation of more reliable safety mechanisms. Hence, a taxonomy of mechanical faults is derived from the electrical domain by exploiting the physical analogies. Furthermore, specific tools are built for automatically instru- menting different descriptions with multi-domain faults. The entire work is proposed as a basis for supporting the creation of increasingly resilient and secure ICPS that need to preserve functional safety in any operating context

Microelectromechanical Systems and Devices

The advances of microelectromechanical systems (MEMS) and devices have been instrumental in the demonstration of new devices and applications, and even in the creation of new fields of research and development: bioMEMS, actuators, microfluidic devices, RF and optical MEMS. Experience indicates a need for MEMS book covering these materials as well as the most important process steps in bulk micro-machining and modeling. We are very pleased to present this book that contains 18 chapters, written by the experts in the field of MEMS. These chapters are groups into four broad sections of BioMEMS Devices, MEMS characterization and micromachining, RF and Optical MEMS, and MEMS based Actuators. The book starts with the emerging field of bioMEMS, including MEMS coil for retinal prostheses, DNA extraction by micro/bio-fluidics devices and acoustic biosensors. MEMS characterization, micromachining, macromodels, RF and Optical MEMS switches are discussed in next sections. The book concludes with the emphasis on MEMS based actuators

Secure hardware design against side-channel attacks

Embedded systems such as smart card or IoT devices should be protected from side-channel analysis (SCA) attacks. For the secure hardware implementation, SCA security metrics to quantify robustness of the implementation at the abstraction level from the logic level to the layout level against SCA attacks should be considered. In our design flow, the first security test is executed at the logic level. If the implementation does not satisfy the threshold of the SCA security metric based on Kullback-Leibler divergence, the module can be re-synthesized with secure logic styles such as WDDL or t-private logic circuits. At the final security test, we use the machine learning technique such as LDA, QDA, SVM and naive Bayes to check the distinguishability of the side-channel leakage depending on inputs or outputs. These techniques apply to an ASIC in characterizing the secret data leakage. In this thesis, t-private logic circuits are implemented with the FreePDK45nm. The SCA security metric as well as the delay and power consumption is characterized. All this charac- terization data are stored in the standard liberty format(.lib) in order for general CAD tools to use this file. The t-private logic package including the general digital logics can be exploited for secure VLSI design. Also, various classifiers such as LDA, QDA, SVM or naive Bayes are used to emulate real SCA environment. Based on this SCA simulator, the threshold of the SCA security metric can be estimated and the security can be verified more accurately. The secure logic cell package and SCA simulator support the methodology of the secure hardware implementation

Modeling spintronics devices in Verilog-A for use with industry-standard simulation tools

As the semiconductor industry works to integrate increasingly more "non-CMOS" devices onto CMOS ICs, compact model development has become an important step in the circuit/system verification tool flow. This research focuses on the two- and three-dimensional modeling of the physical phenomena that occur in nanoscale magnetic devices. This includes the continuous time dynamics of the changing magnetization state in magnetic thin film spintronic devices such as GMR spin valves, toggle MRAM bits and magnetic tunnel junctions (MTJs). The various torques responsible for magnetization change are modeled in Verilog-A modules and have been simulated for several static and dynamic cases. Device behavior is verified using current-in-plane Oersted fields and current-perpendicular-to-plane, spin transfer torque (STT) as stimulus. All device compact models have electrical I/O and are being developed to provide accurate device terminal behavior when used in a circuit simulation environment with standard CMOS circuits

Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks