519 research outputs found

    Low Power Memory/Memristor Devices and Systems

    Get PDF
    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

    Product assurance technology for procuring reliable, radiation-hard, custom LSI/VLSI electronics

    Get PDF
    Advanced measurement methods using microelectronic test chips are described. These chips are intended to be used in acquiring the data needed to qualify Application Specific Integrated Circuits (ASIC's) for space use. Efforts were focused on developing the technology for obtaining custom IC's from CMOS/bulk silicon foundries. A series of test chips were developed: a parametric test strip, a fault chip, a set of reliability chips, and the CRRES (Combined Release and Radiation Effects Satellite) chip, a test circuit for monitoring space radiation effects. The technical accomplishments of the effort include: (1) development of a fault chip that contains a set of test structures used to evaluate the density of various process-induced defects; (2) development of new test structures and testing techniques for measuring gate-oxide capacitance, gate-overlap capacitance, and propagation delay; (3) development of a set of reliability chips that are used to evaluate failure mechanisms in CMOS/bulk: interconnect and contact electromigration and time-dependent dielectric breakdown; (4) development of MOSFET parameter extraction procedures for evaluating subthreshold characteristics; (5) evaluation of test chips and test strips on the second CRRES wafer run; (6) two dedicated fabrication runs for the CRRES chip flight parts; and (7) publication of two papers: one on the split-cross bridge resistor and another on asymmetrical SRAM (static random access memory) cells for single-event upset analysis

    Nano-intrinsic security primitives for internet of everything

    Get PDF
    With the advent of Internet-enabled electronic devices and mobile computer systems, maintaining data security is one of the most important challenges in modern civilization. The innovation of physically unclonable functions (PUFs) shows great potential for enabling low-cost low-power authentication, anti-counterfeiting and beyond on the semiconductor chips. This is because secrets in a PUF are hidden in the randomness of the physical properties of desirably identical devices, making it extremely difficult, if not impossible, to extract them. Hence, the basic idea of PUF is to take advantage of inevitable non-idealities in the physical domain to create a system that can provide an innovative way to secure device identities, sensitive information, and their communications. While the physical variation exists everywhere, various materials, systems, and technologies have been considered as the source of unpredictable physical device variation in large scales for generating security primitives. The purpose of this project is to develop emerging solid-state memory-based security primitives and examine their robustness as well as feasibility. Firstly, the author gives an extensive overview of PUFs. The rationality, classification, and application of PUF are discussed. To objectively compare the quality of PUFs, the author formulates important PUF properties and evaluation metrics. By reviewing previously proposed constructions ranging from conventional standard complementary metal-oxide-semiconductor (CMOS) components to emerging non-volatile memories, the quality of different PUFs classes are discussed and summarized. Through a comparative analysis, emerging non-volatile redox-based resistor memories (ReRAMs) have shown the potential as promising candidates for the next generation of low-cost, low-power, compact in size, and secure PUF. Next, the author presents novel approaches to build a PUF by utilizing concatenated two layers of ReRAM crossbar arrays. Upon concatenate two layers, the nonlinear structure is introduced, and this results in the improved uniformity and the avalanche characteristic of the proposed PUF. A group of cell readout method is employed, and it supports a massive pool of challenge-response pairs of the nonlinear ReRAM-based PUF. The non-linear PUF construction is experimentally assessed using the evaluation metrics, and the quality of randomness is verified using predictive analysis. Last but not least, random telegraph noise (RTN) is studied as a source of entropy for a true random number generation (TRNG). RTN is usually considered a disadvantageous feature in the conventional CMOS designs. However, in combination with appropriate readout scheme, RTN in ReRAM can be used as a novel technique to generate quality random numbers. The proposed differential readout-based design can maintain the quality of output by reducing the effect of the undesired noise from the whole system, while the controlling difficulty of the conventional readout method can be significantly reduced. This is advantageous as the differential readout circuit can embrace the resistance variation features of ReRAMs without extensive pre-calibration. The study in this thesis has the potential to enable the development of cost-efficient and lightweight security primitives that can be integrated into modern computer mobile systems and devices for providing a high level of security

    Stochastic Memory Devices for Security and Computing

    Get PDF
    With the widespread use of mobile computing and internet of things, secured communication and chip authentication have become extremely important. Hardware-based security concepts generally provide the best performance in terms of a good standard of security, low power consumption, and large-area density. In these concepts, the stochastic properties of nanoscale devices, such as the physical and geometrical variations of the process, are harnessed for true random number generators (TRNGs) and physical unclonable functions (PUFs). Emerging memory devices, such as resistive-switching memory (RRAM), phase-change memory (PCM), and spin-transfer torque magnetic memory (STT-MRAM), rely on a unique combination of physical mechanisms for transport and switching, thus appear to be an ideal source of entropy for TRNGs and PUFs. An overview of stochastic phenomena in memory devices and their use for developing security and computing primitives is provided. First, a broad classification of methods to generate true random numbers via the stochastic properties of nanoscale devices is presented. Then, practical implementations of stochastic TRNGs, such as hardware security and stochastic computing, are shown. Finally, future challenges to stochastic memory development are discussed

    Robust Design With Increasing Device Variability In Sub-Micron Cmos And Beyond: A Bottom-Up Framework

    Full text link
    My Ph.D. research develops a tiered systematic framework for designing process-independent and variability-tolerant integrated circuits. This bottom-up approach starts from designing self-compensated circuits as accurate building blocks, and moves up to sub-systems with negative feedback loop and full system-level calibration. a. Design methodology for self-compensated circuits My collaborators and I proposed a novel design methodology that offers designers intuitive insights to create new topologies that are self-compensated and intrinsically process-independent without external reference. It is the first systematic approaches to create "correct-by-design" low variation circuits, and can scale beyond sub-micron CMOS nodes and extend to emerging non-silicon nano-devices. We demonstrated this methodology with an addition-based current source in both 180nm and 90nm CMOS that has 2.5x improved process variation and 6.7x improved temperature sensitivity, and a GHz ring oscillator (RO) in 90nm CMOS with 65% reduction in frequency variation and 85ppm/oC temperature sensitivity. Compared to previous designs, our RO exhibits the lowest temperature sensitivity and process variation, while consuming the least amount of power in the GHz range. Another self-compensated low noise amplifiers (LNA) we designed also exhibits 3.5x improvement in both process and temperature variation and enhanced supply voltage regulation. As part of the efforts to improve the accuracy of the building blocks, I also demonstrated experimentally that due to "diversification effect", the upper bound of circuit accuracy can be better than the minimum tolerance of on-chip devices (MOSFET, R, C, and L), which allows circuit designers to achieve better accuracy with less chip area and power consumption. b. Negative feedback loop based sub-system I explored the feasibility of using high-accuracy DC blocks as low-variation "rulers-on-chip" to regulate high-speed high-variation blocks (e.g. GHz oscillators). In this way, the trade-off between speed (which can be translated to power) and variation can be effectively de-coupled. I demonstrated this proposed structure in an integrated GHz ring oscillators that achieve 2.6% frequency accuracy and 5x improved temperature sensitivity in 90nm CMOS. c. Power-efficient system-level calibration To enable full system-level calibration and further reduce power consumption in active feedback loops, I implemented a successive-approximation-based calibration scheme in a tunable GHz VCO for low power impulse radio in 65nm CMOS. Events such as power-up and temperature drifts are monitored by the circuits and used to trigger the need-based frequency calibration. With my proposed scheme and circuitry, the calibration can be performed under 135pJ and the oscillator can operate between 0.8 and 2GHz at merely 40[MICRO SIGN]W, which is ideal for extremely power-and-cost constraint applications such as implantable biomedical device and wireless sensor networks

    Energy Efficient Computing with Time-Based Digital Circuits

    Get PDF
    University of Minnesota Ph.D. dissertation. May 2019. Major: Electrical Engineering. Advisor: Chris Kim. 1 computer file (PDF); xv, 150 pages.Advancements in semiconductor technology have given the world economical, abundant, and reliable computing resources which have enabled countless breakthroughs in science, medicine, and agriculture which have improved the lives of many. Due to physics, the rate of these advancements is slowing, while the demand for the increasing computing horsepower ever grows. Novel computer architectures that leverage the foundation of conventional systems must become mainstream to continue providing the improved hardware required by engineers, scientists, and governments to innovate. This thesis provides a path forward by introducing multiple time-based computing architectures for a diverse range of applications. Simply put, time-based computing encodes the output of the computation in the time it takes to generate the result. Conventional systems encode this information in voltages across multiple signals; the performance of these systems is tightly coupled to improvements in semiconductor technology. Time-based computing elegantly uses the simplest of components from conventional systems to efficiently compute complex results. Two time-based neuromorphic computing platforms, based on a ring oscillator and a digital delay line, are described. An analog-to-digital converter is designed in the time domain using a beat frequency circuit which is used to record brain activity. A novel path planning architecture, with designs for 2D and 3D routes, is implemented in the time domain. Finally, a machine learning application using time domain inputs enables improved performance of heart rate prediction, biometric identification, and introduces a new method for using machine learning to predict temporal signal sequences. As these innovative architectures are presented, it will become clear the way forward will be increasingly enabled with time-based designs
    • …
    corecore