Near-Zero-Power Temperature Sensing via Tunneling Currents Through Complementary Metal-Oxide-Semiconductor Transistors.

Temperature sensors are routinely found in devices used to monitor the environment, the human body, industrial equipment, and beyond. In many such applications, the energy available from batteries or the power available from energy harvesters is extremely limited due to limited available volume, and thus the power consumption of sensing should be minimized in order to maximize operational lifetime. Here we present a new method to transduce and digitize temperature at very low power levels. Specifically, two pA current references are generated via small tunneling-current metal-oxide-semiconductor field effect transistors (MOSFETs) that are independent and proportional to temperature, respectively, which are then used to charge digitally-controllable banks of metal-insulator-metal (MIM) capacitors that, via a discrete-time feedback loop that equalizes charging time, digitize temperature directly. The proposed temperature sensor was integrated into a silicon microchip and occupied 0.15 mm2 of area. Four tested microchips were measured to consume only 113 pW with a resolution of 0.21 °C and an inaccuracy of ±1.65 °C, which represents a 628× reduction in power compared to prior-art without a significant reduction in performance

Low energy digital circuits in advanced nanometer technologies

The demand for portable devices and the continuing trend towards the Internet ofThings (IoT) have made of energy consumption one of the main concerns in the industry and researchers. The most efficient way of reducing the energy consump-tion of digital circuits is decreasing the supply voltage (Vdd) since the dynamicenergy quadratically depends onVdd. Several works have shown that an optimumsupply voltage exists that minimizes the energy consumption of digital circuits. This optimum supply voltage is usually around 200 mV and 400 mV dependingon the circuit and technology used. To obtain these low supply voltages, on-chipdc-dc converters with high efficiency are needed.This thesis focuses on the study of subthreshold digital systems in advancednanometer technologies. These systems usually can be divided into a Power Man-agement Unit (PMU) and a digital circuit operating at the subthreshold regime.In particular, while considering the PMU, one of the key circuits is the dc-dcconverter. This block converts the voltage from the power source (battery, supercapacitor or wireless power transfer link) to a voltage between 200 mV and 400mV in order to power the digital circuit. In this thesis, we developed two chargerecycling techniques in order to improve the efficiency of switched capacitors dc-dcconverters. The first one is based on a technique used in adiabatic circuits calledstepwise charging. This technique was used in circuits and applications wherethe switching consumption of a big capacitance is very important. We analyzedthe possibility of using this technique in switched capacitor dc-dc converters withintegrated capacitors. We showed through measurements that a 29% reductionin the gate drive losses can be obtained with this technique. The second one isa simplification of stepwise charging which can be applied in some architecturesof switched capacitors dc-dc converters. We also fabricated and tested a dc-dcconverter with this technique and obtained a 25% energy reduction in the drivingof the switches that implement the converter.Furthermore, we studied the digital circuit working in the subthreshold regime,in particular, operating at the minimum energy point. We studied different modelsfor circuits working in these conditions and improved them by considering thedifferences between the NMOS and PMOS transistors. We obtained an optimumNMOS/PMOS leakage current imbalance that minimizes the total leakage energy per operation. This optimum depends on the architecture of the digital circuitand the input data. However, we also showed that important energy reductionscan be obtained by operating at a mean optimum imbalance. We proposed two techniques to achieve the optimum imbalance. We used aFully Depleted Silicon on Insulator (FD-SOI) 28 nm technology for most of the simulations, but we also show that these techniques can be applied in traditionalbulk CMOS technologies. The first one consists in using the back plane voltage of the transistors (or bulk voltage in traditional CMOS) to adjust independently theleakage current of the NMOS and PMOS transistor to work under the optimum NMOS/PMOS leakage current imbalance. We called this approach the OptimumBack Plane Biasing (OBB). A second technique consists of using the length of the transistors to adjust this leakage current imbalance. In the subthreshold regimeand in advanced nanometer technologies a moderate increase in the length has little impact in the output capacitance of the gates and thus in the dynamic energy.We called this approach an Asymmetric Length Biasing (ALB). Finally, we use these techniques in some basic circuits such as adders. We show that around 50% energy reduction can be obtained, in a wide range of frequency while working near the minimum energy point and using these techniques. The main contributions of this thesis are: • Analysis of the stepwise charging technique in small capacitances. •Implementation of stepwise charging technique as a charge recycling tech-nique for efficiency improvement in switched capacitor dc-dc converters. • Development of a charge sharing technique for efficiency improvement inswitched capacitor dc-dc converters. • Analysis of minimum operating voltage of digital circuits due to intrinsicnoise and the impact of technology scaling in this minimum. • Improvement in the modeling of the minimum energy point while considering NMOS and PMOS transistors difference. • Demonstration of the existence of an optimum leakage current imbalance be-tween the NMOS and PMOS transistors that minimizes energy consumptionin the subthreshold regiion. • Development of a back plane (bulk) voltage strategy for working in this optimum.• Development of a sizing strategy for working in the aforementioned optimum. • Analysis of the impact of architecture and input data on the optimum im-balance. The thesis is based on the publications [1–8]. During the Ph.D. program, other publications were generated [9–16] that are partially related with the thesis butwere not included in it.La constante demanda de dispositivos portables y los avances hacia la Internet de las Cosas han hecho del consumo de energía uno de los mayores desafíos y preocupación en la industria y la academia. La forma más eficiente de reducir el consumo de energía de los circuitos digitales es reduciendo su voltaje de alimentación ya que la energía dinámica depende de manera cuadrática con dicho voltaje. Varios trabajos demostraron que existe un voltaje de alimentación óptimo, que minimiza la energía consumida para realizar cierta operación en un circuito digital, llamado punto de mínima energía. Este óptimo voltaje se encuentra usualmente entre 200 mV y 400 mV dependiendo del circuito y de la tecnología utilizada. Para obtener estos voltajes de alimentación de la fuente de energía, se necesitan conversores dc-dc integrados con alta eficiencia. Esta tesis se concentra en el estudio de sistemas digitales trabajando en la región sub umbral diseñados en tecnologías nanométricas avanzadas (28 nm). Estos sistemas se pueden dividir usualmente en dos bloques, uno llamado bloque de manejo de potencia, y el segundo, el circuito digital operando en la region sub umbral. En particular, en lo que corresponde al bloque de manejo de potencia, el circuito más crítico es en general el conversor dc-dc. Este circuito convierte el voltaje de una batería (o super capacitor o enlace de transferencia inalámbrica de energía o unidad de cosechado de energía) en un voltaje entre 200 mV y 400 mV para alimentar el circuito digital en su voltaje óptimo. En esta tesis desarrollamos dos técnicas que, mediante el reciclado de carga, mejoran la eficiencia de los conversores dc-dc a capacitores conmutados. La primera es basada en una técnica utilizada en circuitos adiabáticos que se llama carga gradual o a pasos. Esta técnica se ha utilizado en circuitos y aplicaciones en donde el consumo por la carga y descarga de una capacidad grande es dominante. Nosotros analizamos la posibilidad de utilizar esta técnica en conversores dc-dc a capacitores conmutados con capacitores integrados. Se demostró a través de medidas que se puede reducir en un 29% el consumo debido al encendido y apagado de las llaves que implementan el conversor dc-dc. La segunda técnica, es una simplificación de la primera, la cual puede ser aplicada en ciertas arquitecturas de conversores dc-dc a capacitores conmutados. También se fabricó y midió un conversor con esta técnica y se obtuvo una reducción del 25% en la energía consumida por el manejo de las llaves del conversor. Por otro lado, estudiamos los circuitos digitales operando en la región sub umbral y en particular cerca del punto de mínima energía. Estudiamos diferentes modelos para circuitos operando en estas condiciones y los mejoramos considerando las diferencias entre los transistores NMOS y PMOS. Mediante este modelo demostramos que existe un óptimo en la relación entre las corrientes de fuga de ambos transistores que minimiza la energía de fuga consumida por operación. Este óptimo depende de la arquitectura del circuito digital y ademas de los datos de entrada del circuito. Sin embargo, demostramos que se puede reducir el consumo de manera considerable al operar en un óptimo promedio. Propusimos dos técnicas para alcanzar la relación óptima. Utilizamos una tecnología FD-SOI de 28nm para la mayoría de las simulaciones, pero también mostramos que estas técnicas pueden ser utilizadas en tecnologías bulk convencionales. La primer técnica, consiste en utilizar el voltaje de la puerta trasera (o sustrato en CMOS convencional) para ajustar de manera independiente las corrientes del NMOS y PMOS para que el circuito trabaje en el óptimo de la relación de corrientes. Esta técnica la llamamos polarización de voltaje de puerta trasera óptimo. La segunda técnica, consiste en utilizar los largos de los transistores para ajustar las corrientes de fugas de cada transistor y obtener la relación óptima. Trabajando en la región sub umbral y en tecnologías avanzadas, incrementar moderadamente el largo del transistor tiene poco impacto en la energía dinámica y es por eso que se puede utilizar. Finalmente, utilizamos estas técnicas en circuitos básicos como sumadores y mostramos que se puede obtener una reducción de la energía consumida de aproximadamente 50%, en un amplio rango de frecuencias, mientras estos circuitos trabajan cerca del punto de energía mínima. Las principales contribuciones de la tesis son: • Análisis de la técnica de carga gradual o a pasos en capacidades pequeñas. • Implementación de la técnica de carga gradual para la mejora de eficiencia de conversores dc-dc a capacitores conmutados. • Simplificación de la técnica de carga gradual para mejora de la eficiencia en algunas arquitecturas de conversores dc-dc de capacitores conmutados. • Análisis del mínimo voltaje de operación en circuitos digitales debido al ruido intrínseco del dispositivo y el impacto del escalado de las tecnologías en el mismo. • Mejoras en el modelado del punto de energía mínima de operación de un circuito digital en el cual se consideran las diferencias entre el transistor PMOS y NMOS. • Demostración de la existencia de un óptimo en la relación entre las corrientes de fuga entre el NMOS y PMOS que minimiza la energía de fugas consumida en la región sub umbral. • Desarrollo de una estrategia de polarización del voltaje de puerta trasera para que el circuito digital trabaje en el óptimo antes mencionado. • Desarrollo de una estrategia para el dimensionado de los transistores que componen las compuertas digitales que permite al circuito digital operar en el óptimo antes mencionado. • Análisis del impacto de la arquitectura del circuito y de los datos de entrada del mismo en el óptimo antes mencionado

DTMOS-Based 0.4V Ultra Low-Voltage Low-Power VDTA Design and Its Application to EEG Data Processing

In this paper, an ultra low-voltage, ultra low-power voltage differencing transconductance amplifier (VDTA) is proposed. DTMOS (Dynamic Threshold Voltage MOS) transistors are employed in the design to effectively use the ultra low supply voltage. The proposed VDTA is composed of two operational transconductance amplifiers operating in the subthreshold region. Using TSMC 0.18µm process technology parameters with symmetric ±0.2V sup¬ply voltage, the total power consumption of the VDTA block is found as just 5.96 nW when the transconductances have 3.3 kHz, 3 dB bandwidth. The proposed VDTA circuit is then used in a fourth-order double-tuned band-pass filter for processing real EEG data measurements. The filter achieves close to 64 dB dynamic range at 2% THD with a total power consumption of 12.7 nW

High-performance subthreshold standard cell design and cell placement optimization

Please see PDF for exact formulas

FEEDFORWARD ARTIFICIAL NEURAL NETWORK DESIGN UTILISING SUBTHRESHOLD MODE CMOS DEVICES

This thesis reviews various previously reported techniques for simulating artificial neural networks and investigates the design of fully-connected feedforward networks based on MOS transistors operating in the subthreshold mode of conduction as they are suitable for performing compact, low power, implantable pattern recognition systems. The principal objective is to demonstrate that the transfer characteristic of the devices can be fully exploited to design basic processing modules which overcome the linearity range, weight resolution, processing speed, noise and mismatch of components problems associated with weak inversion conduction, and so be used to implement networks which can be trained to perform practical tasks. A new four-quadrant analogue multiplier, one of the most important cells in the design of artificial neural networks, is developed. Analytical as well as simulation results suggest that the new scheme can efficiently be used to emulate both the synaptic and thresholding functions. To complement this thresholding-synapse, a novel current-to-voltage converter is also introduced. The characteristics of the well known sample-and-hold circuit as a weight memory scheme are analytically derived and simulation results suggest that a dummy compensated technique is required to obtain the required minimum of 8 bits weight resolution. Performance of the combined load and thresholding-synapse arrangement as well as an on-chip update/refresh mechanism are analytically evaluated and simulation studies on the Exclusive OR network as a benchmark problem are provided and indicate a useful level of functionality. Experimental results on the Exclusive OR network and a 'QRS' complex detector based on a 10:6:3 multilayer perceptron are also presented and demonstrate the potential of the proposed design techniques in emulating feedforward neural networks

Ultra-low-voltage self-body biasing scheme and its application to basic arithmetic circuits

The gate level body biasing (GLBB) is assessed in the context of ultra-low-voltage logic designs. To this purpose, a GLBB mirror full adder is implemented by using a commercial 45 nm bulk CMOS triple-well technology and compared to equivalent conventional zero body-biased CMOS and dynamic threshold voltage MOSFET (DTMOS) circuits under different running conditions. Postlayout simulations demonstrate that, at the parity of leakage power consumption, the GLBB technique exhibits a significant concurrent reduction of the energy per operation and the delay in comparison to the conventional CMOS and DTMOS approaches. The silicon area required by the GLBB full adder is halved with respect to the equivalent DTMOS implementation, but it is higher in comparison to conventional CMOS design. Performed analysis also proves that the GLBB solution exhibits a high level of robustness against temperature fluctuations and process variations

An Analog VLSI Deep Machine Learning Implementation

Machine learning systems provide automated data processing and see a wide range of applications. Direct processing of raw high-dimensional data such as images and video by machine learning systems is impractical both due to prohibitive power consumption and the “curse of dimensionality,” which makes learning tasks exponentially more difficult as dimension increases. Deep machine learning (DML) mimics the hierarchical presentation of information in the human brain to achieve robust automated feature extraction, reducing the dimension of such data. However, the computational complexity of DML systems limits large-scale implementations in standard digital computers. Custom analog signal processing (ASP) can yield much higher energy efficiency than digital signal processing (DSP), presenting means of overcoming these limitations. The purpose of this work is to develop an analog implementation of DML system. First, an analog memory is proposed as an essential component of the learning systems. It uses the charge trapped on the floating gate to store analog value in a non-volatile way. The memory is compatible with standard digital CMOS process and allows random-accessible bi-directional updates without the need for on-chip charge pump or high voltage switch. Second, architecture and circuits are developed to realize an online k-means clustering algorithm in analog signal processing. It achieves automatic recognition of underlying data pattern and online extraction of data statistical parameters. This unsupervised learning system constitutes the computation node in the deep machine learning hierarchy. Third, a 3-layer, 7-node analog deep machine learning engine is designed featuring online unsupervised trainability and non-volatile floating-gate analog storage. It utilizes massively parallel reconfigurable current-mode analog architecture to realize efficient computation. And algorithm-level feedback is leveraged to provide robustness to circuit imperfections in analog signal processing. At a processing speed of 8300 input vectors per second, it achieves 1×1012 operation per second per Watt of peak energy efficiency. In addition, an ultra-low-power tunable bump circuit is presented to provide similarity measures in analog signal processing. It incorporates a novel wide-input-range tunable pseudo-differential transconductor. The circuit demonstrates tunability of bump center, width and height with a power consumption significantly lower than previous works

Low-power spatial computing using dynamic threshold devices

Asynchronous spatial computing systems exhibit only localized communication, their overall data-flow being controlled by handshaking. It is therefore straightforward to determine when a particular part of such a system is active. We show that using thin-body double-gate fully depleted SOI transistors, the shift in threshold voltage that can be produced by modulating the back-gate bias is sufficient to reduce subthreshold leakage power by a factor of more than 104 in typical circuits. Using TBFDSOI devices in spatial computing architectures will allow overall power to be greatly reduced while maintaining high performance

Methodology for Standby Leakage Power Reduction in Nanometer-Scale CMOS Circuits

In nanometer-scale CMOS technology, leakage power has become a major component of the total power dissipation due to the downscaling of threshold voltage and gate oxide thickness. The leakage power consumption has received even more attention by increasing demand for mobile devices. Since mobile devices spend a majority of their time in a standby mode, the leakage power savings in standby state is critical to extend battery lifetime. For this reason, low power has become a major factor in designing CMOS circuits. In this dissertation, we propose a novel transistor reordering methodology for leakage reduction. Unlike previous technique, the proposed method provides exact reordering rules for minimum leakage formation by considering all leakage components. Thus, this method formulates an optimized structure for leakage reduction even in complex CMOS logic gate, and can be used in combination with other leakage reduction techniques to achieve further improvement. We also propose a new standby leakage reduction methodology, leakage-aware body biasing, to overcome the shortcomings of a conventional Reverse Body Biasing (RBB) technique. The RBB technique has been used to reduce subthreshold leakage current. Therefore, this technique works well under subthreshold dominant region even though it has intrinsic structural drawbacks. However, such drawbacks cannot be overlooked anymore since gate leakage has become comparable to subthreshold leakage in nanometer-scale region. In addition, BTBT leakage also increases with technology scaling due to the higher doping concentration applied in each process technology. In these circumstances, the objective of leakage minimization is not a single leakage source but the overall leakage sources. The proposed leakage-aware body biasing technique, unlike conventional RBB technique, considers all major leakage sources to minimize the negative effects of existing body biasing approach. This can be achieved by intelligently applying body bias to appropriate CMOS network based on its status (on-/off-state) with the aid of a pin/transistor reordering technique