Design of Low-Voltage Digital Building Blocks and ADCs for Energy-Efficient Systems

Increasing number of energy-limited applications continue to drive the demand for designing systems with high energy efficiency. This tutorial covers the main building blocks of a system implementation including digital logic, embedded memories, and analog-to-digital converters and describes the challenges and solutions to designing these blocks for low-voltage operation

Oxygen-insertion Technology for CMOS Performance Enhancement

Until 2003, the semiconductor industry followed Dennard scaling rules to improve complementary metal-oxide-semiconductor (CMOS) transistor performance. However, performance gains with further reductions in transistor gate length are limited by physical effects that do not scale commensurately with device dimensions: short-channel effects (SCE) due to gate-leakage-limited gate-oxide thickness scaling, channel mobility degradation due to enhanced vertical electric fields, increased parasitic resistances due to reductions in source/drain (S/D) contact area, and increased variability in transistor performance due to random dopant fluctuation (RDF) effects and gate work function variations (WFV). These emerging scaling issues, together with increased process complexity and cost, pose severe challenges to maintaining the exponential scaling of transistor dimensions. This dissertation discusses the benefits of oxygen-insertion (OI) technology, a CMOS performance booster, for overcoming these challenges. The benefit of OI technology to mitigate the increase in sheet resistance ($R_{sh}$) with decreasing junction depth ($X_J$) for ultra-shallow-junctions (USJs) relevant for deep-sub-micron planar CMOS transistors is assessed through the fabrication of $R_{sh}$ test structures, electrical characterization, and technology computer-aided design (TCAD) simulations. Experimental and secondary ion mass spectroscopy (SIMS) analyses indicate that OI technology can facilitate low-resistivity USJ formation by reducing $R_{sh}$ and $X_J$ due to retarded transient-enhanced-diffusion (TED) effects and enhanced dopant retention during post-implantation thermal annealing. It is also shown that a low-temperature-oxide (LTO) capping can increase $R_{sh}$ unfavorably due to lower dopant activation levels, which can be alleviated by OI technology. This dissertation extends the evaluation of OI technology to advanced FinFET technology, targeting 7/8-nm low power technology node. A bulk-Si FinFET design comprising a super-steep retrograde (SSR) fin channel doping profile achievable with OI technology is studied by three-dimensional (3-D) TCAD simulations. As compared with the conventional bulk-Si (control) FinFET design with a heavily-doped fin channel doping profile, SSR FinFETs can achieve higher $I_{on}/I_{off}$ ratios and reduce the sensitivity of device performance to variations due to the lightly doped fin channel. As compared with the SOI FinFET design, SSR FinFETs can achieve similarly low $V_{DD,min}$ for 6T-SRAM cell yield estimation. Both SSR and SOI design can provide for as much as 100 mV reduction in $V_{DD,min}$ compared with the control FinFET design. Overall, the SSR FinFET design that can be achieved with OI technology is demonstrated to be a cheaper alternative to the SOI FinFET technology for extending CMOS scaling beyond the 10-nm node. Finally, this dissertation investigates the benefits of OI technology for reducing the Schottky barrier height ($\Phi_{Bp}$) of a Pt/Ti/p-type Si metal-semiconductor (M/S) contact, which can be expected to help reduce the specific contact resistivity for a p-type silicon contact. Electrical measurements of back-to-back Schottky diodes, SIMS, and X-ray photoelectron spectroscopy (XPS) show that the reduction in $\Phi_{Bp}$ is associated with enhanced Ti 2p and Si 2p core energy level shifts. OI technology is shown to favor low-$\Phi_{Bp}$ Pt monosilicide formation during forming gas anneal (FGA) by suppressing the grain boundary diffusion of Pt atoms into the crystalline Si substrate

Design and Analysis of Robust Low Voltage Static Random Access Memories.

Static Random Access Memory (SRAM) is an indispensable part of most modern VLSI designs and dominates silicon area in many applications. In scaled technologies, maintaining high SRAM yield becomes more challenging since they are particularly vulnerable to process variations due to 1) the minimum sized devices used in SRAM bitcells and 2) the large array sizes. At the same time, low power design is a key focus throughout the semiconductor industry. Since low voltage operation is one of the most effective ways to reduce power consumption due to its quadratic relationship to energy savings, lowering the minimum operating voltage (Vmin) of SRAM has gained significant interest. This thesis presents four different approaches to design and analyze robust low voltage SRAM: SRAM analysis method improvement, SRAM bitcell development, SRAM peripheral optimization, and advance device selection. We first describe a novel yield estimation method for bit-interleaved voltage-scaled 8-T SRAMs. Instead of the traditional trade-off between write and read, the trade-off between write and half select disturb is analyzed. In addition, this analysis proposes a method to find an appropriate Write Word-Line (WWL) pulse width to maximize yield. Second, low leakage 10-T SRAM with speed compensation scheme is proposed. During sleep mode of a sensor application, SRAM retaining data cannot be shut down so it is important to minimize leakage in SRAM. This work adopts several leakage reduction techniques while compensating performance. Third, adaptive write architecture for low voltage 8-T SRAMs is proposed. By adaptively modulating WWL width and voltage level, it is possible to achieve low power consumption while maintaining high yield without excessive performance degradation. Finally, low power circuit design based on heterojunction tunneling transistors (HETTs) is discussed. HETTs have a steep subthreshold swing beneficial for low voltage operation. Device modeling and design of logic and SRAM are proposed.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91569/1/daeyeonk_1.pd

In-situ and In-field temperature and transistor BTI sensing techniques with microprocessor level implementation

In modern deep-scaled CMOS technologies, various silicon-related pitfalls present challenges to the long-term performance of microprocessors. Such challenges include (1) local hot spots, which breach the thermal limitations of a microprocessor, and (2) transistor aging, especially NBTI, which degrades transistor threshold voltage, ultimately threatening the reliability of the entire memory block. In previous systems, the dummy circuit was placed next to the subject, where the dummy was frequently analyzed, and the readout was used to infer the condition of the target. Due to rapidly changing ambient conditions (e.g., temperature and voltage) and the potential scale of the target dimensions, such metrics may not accurately represent the condition of the target. Moreover, such temperature sensors and canary circuits occupy a significant area. Therefore, it would be highly preferable to monitor the target circuit in-situ, i.e., to sense the precise transistor at operation. It is also important to achieve an accurate sensing metric. When the temperature is analyzed, the readout should account for voltage and process variations. While sensing the aging degradation, the readout should account for voltage and temperature fluctuations. This would allow testing during in-field operation, while the circuits achieve area-efficiency. This research had two stages. One result of the first stage was a silicon test chip that was a compact temperature sensor. It involved a family of PTAT+CTAT sensor front-ends that unitized only 6 to 8 conventional CMOS logic devices, yielding a smaller sized chip. The sensor demonstrates accuracy within the target and achieves a 14.3x smaller foot print than preceding published designs. The second product of the first stage was a PMOS aging sensor used in 6T SRAM circuits. The test chip has a real SRAM array, integrated with the proposed PMOS NBTI sensor. It can sense real PMOS NBTI effects in any bit cell (in-situ) and provide robust readings of temperature and voltage (in-field). Intensive aging tests validated the proposed sensing technique. The second stage was focused on implementing the in-situ and in-field sensing techniques in a real processor. The MIPS microprocessor had a modified instruction cache (I$) and instruction set architecture. With the addition of new instruction aging sensing and minor modification of the circuits, the processor can execute aging sensing opportunistically to evaluate the aging level of its instruction cache. A software framework was developed and verified to estimate the retention voltage of the instruction cache over the lifetime of the chip. An area-efficient SoC was developed that could transform the instruction cache into an ambient temperature sensor. It had a physically unclonable function (PUF), and it was built with an area-saving technique similar to the earlier work. This thesis has four chapters. They are presented in chronological and they are aligned with the research described above

Probabilistic Compute-in-Memory Design For Efficient Markov Chain Monte Carlo Sampling

Markov chain Monte Carlo (MCMC) is a widely used sampling method in modern artificial intelligence and probabilistic computing systems. It involves repetitive random number generations and thus often dominates the latency of probabilistic model computing. Hence, we propose a compute-in-memory (CIM) based MCMC design as a hardware acceleration solution. This work investigates SRAM bitcell stochasticity and proposes a novel ``pseudo-read'' operation, based on which we offer a block-wise random number generation circuit scheme for fast random number generation. Moreover, this work proposes a novel multi-stage exclusive-OR gate (MSXOR) design method to generate strictly uniformly distributed random numbers. The probability error deviating from a uniform distribution is suppressed under $10^{-5}$. Also, this work presents a novel in-memory copy circuit scheme to realize data copy inside a CIM sub-array, significantly reducing the use of R/W circuits for power saving. Evaluated in a commercial 28-nm process development kit, this CIM-based MCMC design generates 4-bit$\sim$32-bit samples with an energy efficiency of $0.53$~pJ/sample and high throughput of up to $166.7$M~samples/s. Compared to conventional processors, the overall energy efficiency improves $5.41\times10^{11}$ to $2.33\times10^{12}$ times

Solid State Circuits Technologies

The evolution of solid-state circuit technology has a long history within a relatively short period of time. This technology has lead to the modern information society that connects us and tools, a large market, and many types of products and applications. The solid-state circuit technology continuously evolves via breakthroughs and improvements every year. This book is devoted to review and present novel approaches for some of the main issues involved in this exciting and vigorous technology. The book is composed of 22 chapters, written by authors coming from 30 different institutions located in 12 different countries throughout the Americas, Asia and Europe. Thus, reflecting the wide international contribution to the book. The broad range of subjects presented in the book offers a general overview of the main issues in modern solid-state circuit technology. Furthermore, the book offers an in depth analysis on specific subjects for specialists. We believe the book is of great scientific and educational value for many readers. I am profoundly indebted to the support provided by all of those involved in the work. First and foremost I would like to acknowledge and thank the authors who worked hard and generously agreed to share their results and knowledge. Second I would like to express my gratitude to the Intech team that invited me to edit the book and give me their full support and a fruitful experience while working together to combine this book

Circuits and Systems Advances in Near Threshold Computing

Modern society is witnessing a sea change in ubiquitous computing, in which people have embraced computing systems as an indispensable part of day-to-day existence. Computation, storage, and communication abilities of smartphones, for example, have undergone monumental changes over the past decade. However, global emphasis on creating and sustaining green environments is leading to a rapid and ongoing proliferation of edge computing systems and applications. As a broad spectrum of healthcare, home, and transport applications shift to the edge of the network, near-threshold computing (NTC) is emerging as one of the promising low-power computing platforms. An NTC device sets its supply voltage close to its threshold voltage, dramatically reducing the energy consumption. Despite showing substantial promise in terms of energy efficiency, NTC is yet to see widescale commercial adoption. This is because circuits and systems operating with NTC suffer from several problems, including increased sensitivity to process variation, reliability problems, performance degradation, and security vulnerabilities, to name a few. To realize its potential, we need designs, techniques, and solutions to overcome these challenges associated with NTC circuits and systems. The readers of this book will be able to familiarize themselves with recent advances in electronics systems, focusing on near-threshold computing

Nano-scale TG-FinFET: Simulation and Analysis

Transistor has been designed and fabricated in the same way since its invention more than four decades ago enabling exponential shrinking in the channel length. However, hitting fundamental limits imposed the need for introducing disruptive technology to take over. FinFET - 3-D transistor - has been emerged as the first successor to MOSFET to continue the technology scaling roadmap. In this thesis, scaling of nano-meter FinFET has been investigated on both the device and circuit levels. The studies, primarily, consider FinFET in its tri-gate (TG) structure. On the device level, first, the main TCAD models used in simulating electron transport are benchmarked against the most accurate results on the semi-classical level using Monte Carlo techniques. Different models and modifications are investigated in a trial to extend one of the conventional models to the nano-scale simulations. Second, a numerical study for scaling TG-FinFET according to the most recent International Technology Roadmap of Semiconductors is carried out by means of quantum corrected 3-D Monte Carlo simulations in the ballistic and quasi-ballistic regimes, to assess its ultimate performance and scaling behavior for the next generations. Ballisticity ratio (BR) is extracted and discussed over different channel lengths. The electron velocity along the channel is analyzed showing the physical significance of the off-equilibrium transport with scaling the channel length. On the circuit level, first, the impact of FinFET scaling on basic circuit blocks is investigated based on the PTM models. 256-bit (6T) SRAM is evaluated for channel lengths of 20nm down to 7nm showing the scaling trends of basic performance metrics. In addition, the impact of VT variations on the delay, power, and stability is reported considering die-to-die variations. Second, we move to another peer-technology which is 28nm FD-SOI as a comparative study, keeping the SRAM cell as the test block, more advanced study is carried out considering the cell‘s stability and the evolution from dynamic to static metrics

Low-Power and Error-Resilient VLSI Circuits and Systems.

Efficient low-power operation is critically important for the success of the next-generation signal processing applications. Device and supply voltage have been continuously scaled to meet a more constrained power envelope, but scaling has created resiliency challenges, including increasing timing faults and soft errors. Our research aims at designing low-power and robust circuits and systems for signal processing by drawing circuit, architecture, and algorithm approaches. To gain an insight into the system faults due to supply voltage reduction, we researched the two primary effects that determine the minimum supply voltage (VMIN) in Intel’s tri-gate CMOS technology, namely process variations and gate-dielectric soft breakdown. We determined that voltage scaling increases the timing window that sequential circuits are vulnerable. Thus, we proposed a new hold-time violation metric to define hold-time VMIN, which has been adopted as a new design standard. Device scaling increases soft errors which affect circuit reliability. Through extensive soft error characterization using two 65nm CMOS test chips, we studied the soft error mechanisms and its dependence on supply voltage and clock frequency. This study laid the foundation of the first 65nm DSP chip design for a NASA spaceflight project. To mitigate such random errors, we proposed a new confidence-driven architecture that effectively enhances the error resiliency of deeply scaled CMOS and post-CMOS circuits. Designing low-power resilient systems can effectively leverage application-specific algorithmic approaches. To explore design opportunities in the algorithmic domain, we demonstrate an application-specific detection and decoding processor for multiple-input multiple-output (MIMO) wireless communication. To enhance the receive error rate for a robust wireless communication, we designed a joint detection and decoding technique by enclosing detection and decoding in an iterative loop to enhance both interference cancellation and error reduction. A proof-of-concept chip design was fabricated for the next-generation 4x4 256QAM MIMO systems. Through algorithm-architecture optimizations and low-power circuit techniques, our design achieves significant improvements in throughput, energy efficiency and error rate, paving the way for future developments in this area.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110323/1/uchchen_1.pd

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within