Diseño de circuitos analógicos y de señal mixta con consideraciones de diseño físico y variabilidad

Advances in microelectronic technology has been based on an increasing capacity to integrate transistors, moving this industry to the nanoelectronics realm in recent years. Moore’s Law [1] has predicted (and somehow governed) the growth of the capacity to integrate transistors in a single IC. Nevertheless, while this capacity has grown steadily, the increasing number of design tasks that are involved in the creation of the integrated circuit and their complexity has led to a phenomenon known as the ``design gap´´. This is the difference between what can theoretically be integrated and what can practically be designed. Since the early 2000s, the International Technology Roadmap of Semiconductors (ITRS) reports, published by the Semiconductor Industry Association (SIA), alert about the necessity to limit the growth of the design cost by increasing the productivity of the designer to continue the semiconductor industry’s growth. Design automation arises as a key element to close this ”design gap”. In this sense, electronic design automation (EDA) tools have reached a level of maturity for digital circuits that is far behind the EDA tools that are made for analog circuit design automation. While digital circuits rely, in general, on two stable operation states (which brings inherent robustness against numerous imperfections and interferences, leading to few design constraints like area, speed or power consumption), analog signal processing, on the other hand, demands compliance with lots of constraints (e.g., matching, noise, robustness, ...). The triumph of digital CMOS circuits, thanks to their mentioned robustness, has, ultimately, facilitated the way that circuits can be processed by algorithms, abstraction levels and description languages, as well as how the design information traverse the hierarchical levels of a digital system. The field of analog design automation faces many more difficulties due to the many sources of perturbation, such as the well-know process variability, and the difficulty in treating these systematically, like digital tools can do. In this Thesis, different design flows are proposed, focusing on new design methodologies for analog circuits, thus, trying to close the ”gap” between digital and analog EDA tools. In this chapter, the most important sources for perturbations and their impact on the analog design process are discussed in Section 1.2. The traditional analog design flow is discussed in 1.3. Emerging design methodologies that try to reduce the ”design gap” are presented in Section 1.4 where the key concept of Pareto-Optimal Front (POF) is explained. This concept, brought from the field of economics, models the analog circuit performances into a set of solutions that show the optimal trade-offs among conflicting circuit performances (e.g. DC-gain and unity-gain frequency). Finally, the goals of this thesis are presented in Section 1.5

Advanced analog layout design automation in compliance with density uniformity

To fabricate a reliable integrated circuit chip, foundries follow specific design rules and layout processing techniques. One of the parameters, which affect circuit performance and final electronic product quality, is the variation of thickness for each semiconductor layer within the fabricated chips. The thickness is closely dependent on the density of geometric features on that layer. Therefore, to ensure consistent thickness, foundries normally have to seriously control distribution of the feature density on each layer by using post-processing operations. In this research, the methods of controlling feature density distribution on different layers of an analog layout during the process of layout migration from an old technology to a new one or updated design specifications in the same technology have been investigated. We aim to achieve density-uniformity-aware layout retargeting for facilitating manufacturing process in the advanced technologies. This can offer an advantage right to the design stage for the designers to evaluate the effects of applying density uniformity to their drafted layouts, which are otherwise usually done by the foundries at the final manufacturing stage without considering circuit performance. Layout modification for density uniformity includes component position change and size modification, which may induce crosstalk noise caused by extra parasitic capacitance. To effectively control this effect, we have also investigated and proposed a simple yet accurate analytic method to model the parasitic capacitance on multi-layer VLSI chips. Supported by this capacitance modeling research, a unique methodology to deal with density-uniformity-aware analog layout retargeting with the capability of parasitic capacitance control has been presented. The proposed operations include layout geometry position rearrangement, interconnect size modification, and extra dummy fill insertion for enhancing layout density uniformity. All of these operations are holistically coordinated by a linear programming optimization scheme. The experimental results demonstrate the efficacy of the proposed methodology compared to the popular digital solutions in terms of minimum density variation and acute parasitic capacitance control

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

A Review of Bayesian Methods in Electronic Design Automation

The utilization of Bayesian methods has been widely acknowledged as a viable solution for tackling various challenges in electronic integrated circuit (IC) design under stochastic process variation, including circuit performance modeling, yield/failure rate estimation, and circuit optimization. As the post-Moore era brings about new technologies (such as silicon photonics and quantum circuits), many of the associated issues there are similar to those encountered in electronic IC design and can be addressed using Bayesian methods. Motivated by this observation, we present a comprehensive review of Bayesian methods in electronic design automation (EDA). By doing so, we hope to equip researchers and designers with the ability to apply Bayesian methods in solving stochastic problems in electronic circuits and beyond.Comment: 24 pages, a draft version. We welcome comments and feedback, which can be sent to [email protected]

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

Ultra-low Voltage Digital Circuits and Extreme Temperature Electronics Design

Certain applications require digital electronics to operate under extreme conditions e.g., large swings in ambient temperature, very low supply voltage, high radiation. Such applications include sensor networks, wearable electronics, unmanned aerial vehicles, spacecraft, and energyharvesting systems. This dissertation splits into two projects that study digital electronics supplied by ultra-low voltages and build an electronic system for extreme temperatures. The first project introduces techniques that improve circuit reliability at deep subthreshold voltages as well as determine the minimum required supply voltage. These techniques address digital electronic design at several levels: the physical process, gate design, and system architecture. This dissertation analyzes a silicon-on-insulator process, Schmitt-trigger gate design, and asynchronous logic at supply voltages lower than 100 millivolts. The second project describes construction of a sensor digital controller for the lunar environment. Parts of the digital controller are an asynchronous 8031 microprocessor that is compatible with synchronous logic, memory with error detection and correction, and a robust network interface. The digitial sensor ASIC is fabricated on a silicon-germanium process and built with cells optimized for extreme temperatures

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

Fast and Robust Design of CMOS VCO for Optimal Performance

The exponentially growing design complexity with technological advancement calls for a large scope in the analog and mixed signal integrated circuit design automation. In the automation process, performance optimization under different environmental constraints is of prime importance. The analog integrated circuits design strongly requires addressing multiple competing performance objectives for optimization with ability to find global solutions in a constrained environment. The integrated circuit (IC) performances are significantly affected by the device, interconnect and package parasitics. Inclusion of circuit parasitics in the design phase along with performance optimization has become a bare necessity for faster prototyping. Besides this, the fabrication process variations have a predominant effect on the circuit performance, which is directly linked to the acceptability of manufactured integrated circuit chips. This necessitates a manufacturing process tolerant design. The development of analog IC design methods exploiting the computational intelligence of evolutionary techniques for optimization, integrating the circuit parasitic in the design optimization process in a more meaningful way and developing process fluctuation tolerant optimal design is the central theme of this thesis. Evolutionary computing multi-objective optimization techniques such as Non-dominated Sorting Genetic Algorithm-II and Infeasibility Driven Evolutionary Algorithm are used in this thesis for the development of parasitic aware design techniques for analog ICs. The realistic physical and process constraints are integrated in the proposed design technique. A fast design methodology based on one of the efficient optimization technique is developed and an extensive worst case process variation analysis is performed. This work also presents a novel process corner variation aware analog IC design methodology, which would effectively increase the yield of chips in the acceptable performance window. The performance of all the presented techniques is demonstrated through the application to CMOS ring oscillators, current starved and xi differential voltage controlled oscillators, designed in Cadence Virtuoso Analog Design Environment