Logic synthesis and testing techniques for switching nano-crossbar arrays

Beyond CMOS, new technologies are emerging to extend electronic systems with features unavailable to silicon-based devices. Emerging technologies provide new logic and interconnection structures for computation, storage and communication that may require new design paradigms, and therefore trigger the development of a new generation of design automation tools. In the last decade, several emerging technologies have been proposed and the time has come for studying new ad-hoc techniques and tools for logic synthesis, physical design and testing. The main goal of this project is developing a complete synthesis and optimization methodology for switching nano-crossbar arrays that leads to the design and construction of an emerging nanocomputer. New models for diode, FET, and four-terminal switch based nanoarrays are developed. The proposed methodology implements logic, arithmetic, and memory elements by considering performance parameters such as area, delay, power dissipation, and reliability. With combination of logic, arithmetic, and memory elements a synchronous state machine (SSM), representation of a computer, is realized. The proposed methodology targets variety of emerging technologies including nanowire/nanotube crossbar arrays, magnetic switch-based structures, and crossbar memories. The results of this project will be a foundation of nano-crossbar based circuit design techniques and greatly contribute to the construction of emerging computers beyond CMOS. The topic of this project can be considered under the research area of â\u80\u9cEmerging Computing Modelsâ\u80\u9d or â\u80\u9cComputational Nanoelectronicsâ\u80\u9d, more specifically the design, modeling, and simulation of new nanoscale switches beyond CMOS

Wafer-scale integration of semiconductor memory.

This work is directed towards a study of full-slice or "wafer-scale integrated" - semiconductor memory. Previous approaches to full slice technology are studied and critically compared. It is shown that a fault-tolerant, fixed-interconnection approach offers many advantages; such a technique forms the basis of the experimental work. The disadvantages of the conventional technology are reviewed to illustrate the potential improvements in cost, packing density and reliability obtainable with wafer-scale integration (W.S.l). Iterative chip arrays are modelled by a pseudorandom fault distribution; algorithms to control the linking of adjacent good - chips into linear chains are proposed and investigated by computer simulation. It is demonstrated that long chains may be produced at practicable yield levels. The on-chip control circuitry and the external control electronics required to implement one particular algorithm are described in relation to a TTL simulation of an array of 4 X 4 integrated circuit chips. A layout of the on-chip control logic is shown to require (in 40 dynamic MOS circuitry) an area equivalent to ~250 shift register stages -a reasonable overhead on large memories. Structures are proposed to extend the fixed-interconnection, fault-tolerant concept to parallel/serial organised memory - covering RAM, ROM and Associative Memory applications requiring up to~ 2M bits of storage. Potential problem areas in implementing W.S.I are discussed and it is concluded that current technology is capable of manufacturing such devices. A detailed cost comparison of the conventional and W.S.I approaches to large serial memories illustrates the potential savings available with wafer-scale integration. The problem of gaining industrial acceptance for W.S.I is discussed in relation to known and anticipated views- of new technology. The thesis concludes with suggestions for further work in the general field of wafer-scale integration

Charge Trap Transistors (CTT): Turning Logic Transistors into Embedded Non-Volatile Memory for Advanced High-k/Metal Gate CMOS Technologies

While need for embedded non-volatile memory (eNVM) in modern computing systems continues to grow rapidly, the options have been limited due to integration and scaling challenges as well as operational voltage incompatibilities. Introduced in this work is a unique multi-time programmable memory (MTPM) solution for advanced high-k/metal-gate (HKMG) CMOS technologies which turns as-fabricated standard logic transistors into eNVM elements, without the need for any process adders or additional masks. These logic transistors, when employed as eNVM elements, are dubbed “Charge Trap Transistors” (CTTs). The fundamental device physics, principles of operation, and technological breakthroughs required for employing logic transistors as eNVM are presented. Implementation of CTT eNVM in 32 nm, 22 nm, 14 nm, and 7 nm production technologies has been realized and demonstrated in this work. The emerging memory technology landscape and the space that the CTT technology occupies therein are examined.The motivation behind this work is to develop an eNVM technology that is completely process/mask-free, multi-time programmable, operable at low/logic-compatible voltages, scalable, and secure. The CTT technology satisfies all of the aforementioned criteria. CTTs offer a data retention lifetime of > 10 years at 125 �C and an operation temperature range of -55�-125� C. Hardware results demonstrate an endurance of > 10^4 program/erase cycles which is more than adequate for most embedded applications. Hardware security enhancement, on-chip reconfigurable encryption, firmware, BIOS, chip ID, redundancy, repair at wafer and module test and in the field, performance tailoring, and chip configuration are a few of the applications of CTT eNVM. Moreover, the CTT array in its native (unprogrammed) state measures very well as an entropy source for potential PUF (Physically Unclonable Function) applications such as identification, authentication, anti-counterfeiting, secure boot, and cryptographic IP. In addition to the numerous digital applications, CTTs can also be utilized as an analog memory for applications like neuromorphic computing for machine learning (ML) and artificial intelligence (AI)

Investigation into yield and reliability enhancement of TSV-based three-dimensional integration circuits

Three dimensional integrated circuits (3D ICs) have been acknowledged as a promising technology to overcome the interconnect delay bottleneck brought by continuous CMOS scaling. Recent research shows that through-silicon-vias (TSVs), which act as vertical links between layers, pose yield and reliability challenges for 3D design. This thesis presents three original contributions.The first contribution presents a grouping-based technique to improve the yield of 3D ICs under manufacturing TSV defects, where regular and redundant TSVs are partitioned into groups. In each group, signals can select good TSVs using rerouting multiplexers avoiding defective TSVs. Grouping ratio (regular to redundant TSVs in one group) has an impact on yield and hardware overhead. Mathematical probabilistic models are presented for yield analysis under the influence of independent and clustering defect distributions. Simulation results using MATLAB show that for a given number of TSVs and TSV failure rate, careful selection of grouping ratio results in achieving 100% yield at minimal hardware cost (number of multiplexers and redundant TSVs) in comparison to a design that does not exploit TSV grouping ratios. The second contribution presents an efficient online fault tolerance technique based on redundant TSVs, to detect TSV manufacturing defects and address thermal-induced reliability issue. The proposed technique accounts for both fault detection and recovery in the presence of three TSV defects: voids, delamination between TSV and landing pad, and TSV short-to-substrate. Simulations using HSPICE and ModelSim are carried out to validate fault detection and recovery. Results show that regular and redundant TSVs can be divided into groups to minimise area overhead without affecting the fault tolerance capability of the technique. Synthesis results using 130-nm design library show that 100% repair capability can be achieved with low area overhead (4% for the best case). The last contribution proposes a technique with joint consideration of temperature mitigation and fault tolerance without introducing additional redundant TSVs. This is achieved by reusing spare TSVs that are frequently deployed for improving yield and reliability in 3D ICs. The proposed technique consists of two steps: TSV determination step, which is for achieving optimal partition between regular and spare TSVs into groups; The second step is TSV placement, where temperature mitigation is targeted while optimizing total wirelength and routing difference. Simulation results show that using the proposed technique, 100% repair capability is achieved across all (five) benchmarks with an average temperature reduction of 75.2? (34.1%) (best case is 99.8? (58.5%)), while increasing wirelength by a small amount

A Holistic Solution for Reliability of 3D Parallel Systems

As device scaling slows down, emerging technologies such as 3D integration and carbon nanotube field-effect transistors are among the most promising solutions to increase device density and performance. These emerging technologies offer shorter interconnects, higher performance, and lower power. However, higher levels of operating temperatures and current densities project significantly higher failure rates. Moreover, due to the infancy of the manufacturing process, high variation, and defect densities, chip designers are not encouraged to consider these emerging technologies as a stand-alone replacement for Silicon-based transistors. The goal of this dissertation is to introduce new architectural and circuit techniques that can work around high-fault rates in the emerging 3D technologies, improving performance and reliability comparable to Silicon. We propose a new holistic approach to the reliability problem that addresses the necessary aspects of an effective solution such as detection, diagnosis, repair, and prevention synergically for a practical solution. By leveraging 3D fabric layouts, it proposes the underlying architecture to efficiently repair the system in the presence of faults. This thesis presents a fault detection scheme by re-executing instructions on idle identical units that distinguishes between transient and permanent faults while localizing it to the granularity of a pipeline stage. Furthermore, with the use of a dynamic and adaptive reconfiguration policy based on activity factors and temperature variation, we propose a framework that delivers a significant improvement in lifetime management to prevent faults due to aging. Finally, a design framework that can be used for large-scale chip production while mitigating yield and variation failures to bring up Carbon Nano Tube-based technology is presented. The proposed framework is capable of efficiently supporting high-variation technologies by providing protection against manufacturing defects at different granularities: module and pipeline-stage levels.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168118/1/javadb_1.pd

Complete Modeling of the Chondrogenic Environment under Continuous Low-Intensity Ultrasound

Articular cartilage is an avascular tissue that requires therapeutic intervention methods. This work answers the following: determine transducer operation to optimize the bioeffects; calculate the magnitude of pressure exerted on chondrocytes at an injury site; and confirm the theoretical findings by an animal model. Earlier work has shown that cellular response to US is maximized at the resonance frequency of the cells. Resonance frequencies were calculated for chondrocytes in various layers. The latter configuration closest resembles in vivo conditions and the resonance occurred at 3.8±0.3 . The 3D model of US propagation in a rabbit knee was constructed from MRIs to produce anatomically correct domains. US attenuates in cartilage and 3D results showed that pressure is maximized at an injury site when the transducer is placed in line with the site. Transducer positions that causes US waves to traverse cartilage before reaching the injury site must be avoided. The 3D model is time-consuming, and impractical for routine clinical usage. The average pressure delivered is lower in pulsed low-intensity US compared to cLIUS. A 1D model, which captured all the key results of the 3D model, was used to calculate the temperature rise due to US dissipation – the cLIUS protocol produces negligible increases in temperature. US attenuation can be overcome if the injury site lies in the near-field of the transducer, where constructive interference tends to not only cancel attenuation but delivers pressures higher than the transducer value – confirmed by both 3D and 1D models. Rabbit studies confirmed that cLIUS treatment significantly improved healing of damaged cartilages, and defect sites filled, in contrast to fibrous filling in untreated defects. Finally, a model that involves three intracellular pathways was used to investigate mechanochemical response of a mesenchymal stem cell (MSC). Results showed that MSCs could be prompted towards the condensation step by mechanical stimulation at the resonance frequencies without any exogeneous chemical prompting, and the key proteins formed much earlier than in in vitro experiments. Adviser: Hendrik J. Viljoe

Yield-Aware Leakage Power Reduction of On-Chip SRAMs

Leakage power dissipation of on-chip static random access memories (SRAMs) constitutes a significant fraction of the total chip power consumption in state-of-the-art microprocessors and system-on-chips (SoCs). Scaling the supply voltage of SRAMs during idle periods is a simple yet effective technique to reduce their leakage power consumption. However, supply voltage scaling also results in the degradation of the cells’ robustness, and thus reduces their capability to retain data reliably. This is particularly resulting in the failure of an increasing number of cells that are already weakened by excessive process parameters variations and/or manufacturing imperfections in nano-meter technologies. Thus, with technology scaling, it is becoming increasingly challenging to maintain the yield while attempting to reduce the leakage power of SRAMs. This research focuses on characterizing the yield-leakage tradeoffs and developing novel techniques for a yield-aware leakage power reduction of SRAMs. We first demonstrate that new fault behaviors emerge with the introduction of a low-leakage standby mode to SRAMs. In particular, it is shown that there are some types of defects in SRAM cells that start to cause failures only when the drowsy mode is activated. These defects are not sensitized in the active operating mode, and thus escape the traditional March tests. Fault models for these newly observed fault behaviors are developed and described in this thesis. Then, a new low-complexity test algorithm, called March RAD, is proposed that is capable of detecting all the drowsy faults as well as the simple traditional faults. Extreme process parameters variations can also result in SRAM cells with very weak data-retention capability. The probability of such cells may be very rare in small memory arrays, however, in large arrays, their probability is magnified by the huge number of bit-cells integrated on a single chip. Hence, it is critical also to account for such extremal events while attempting to scale the supply voltage of SRAMs. To estimate the statistics of such rare events within a reasonable computational time, we have employed concepts from extreme value theory (EVT). This has enabled us to accurately model the tail of the cell failure probability distribution versus the supply voltage. Analytical models are then developed to characterize the yield-leakage tradeoffs in large modern SRAMs. It is shown that even a moderate scaling of the supply voltage of large SRAMs can potentially result in significant yield losses, especially in processes with highly fluctuating parameters. Thus, we have investigated the application of fault-tolerance techniques for a more efficient leakage reduction of SRAMs. These techniques allow for a more aggressive voltage scaling by providing tolerance to the failures that might occur during the sleep mode. The results show that in a 45-nm technology, assuming 10% variation in transistors threshold voltage, repairing a 64KB memory using only 8 redundant rows or incorporating single error correcting codes (ECCs) allows for ~90% leakage reduction while incurring only ~1% yield loss. The combination of redundancy and ECC, however, allows to reach the practical limits of leakage reduction in the analyzed benchmark, i.e., ~95%. Applying an identical standby voltage to all dies, regardless of their specific process parameters variations, can result in too many cell failures in some dies with heavily skewed process parameters, so that they may no longer be salvageable by the employed fault-tolerance techniques. To compensate for the inter-die variations, we have proposed to tune the standby voltage of each individual die to its corresponding minimum level, after manufacturing. A test algorithm is presented that can be used to identify the minimum applicable standby voltage to each individual memory die. A possible implementation of the proposed tuning technique is also demonstrated. Simulation results in a 45-nm predictive technology show that tuning standby voltage of SRAMs can enhance data-retention yield by an additional 10%−50%, depending on the severity of the variations

A review of laser engineered net shaping (LENS) build and process parameters of metallic parts

Purpose: This paper aims to present a comprehensive review of the laser engineered net shaping (LENS) process in an attempt to provide the reader with a deep understanding of the controllable and fixed build parameters of metallic parts. The authors discuss the effect and interplay between process parameters, including: laser power, scan speed and powder feed rate. Further, the authors show the interplay between process parameters is pivotal in achieving the desired microstructure, macrostructure, geometrical accuracy and mechanical properties. Design/methodology/approach: In this manuscript, the authors review current research examining the process inputs and their influences on the final product when manufacturing with the LENS process. The authors also discuss how these parameters relate to important build aspects such as melt-pool dimensions, the volume of porosity and geometry accuracy. Findings: The authors conclude that studies have greatly enriched the understanding of the LENS build process, however, much studies remains to be done. Importantly, the authors reveal that to date there are a number of detailed theoretical models that predict the end properties of deposition, however, much more study is necessary to allow for reasonable prediction of the build process for standard industrial parts, based on the synchronistic behavior of the input parameters. Originality/value: This paper intends to raise questions about the possible research areas that could potentially promote the effectiveness of this LENS technology.</div