Per-Core DVFS with Switched-Capacitor Converters for Energy Efficiency in Manycore Processors

Integrating multiple power converters on-chip improves energy efficiency of manycore architectures. Switched-capacitor (SC) dc-dc converters are compatible with conventional CMOS processes, but traditional implementations suffer from limited conversion efficiency. We propose a dynamic voltage and frequency scaling scheme with SC converters that achieves high converter efficiency by allowing the output voltage to ripple and having the processor core frequency track the ripple. Minimum core energy is achieved by hopping between different converter modes and tuning body-bias voltages. A multicore processor model based on a 28-nm technology shows conversion efficiencies of 90% along with over 25% improvement in the overall chip energy efficiency

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

A Charge-Recycling Scheme and Ultra Low Voltage Self-Startup Charge Pump for Highly Energy Efficient Mixed Signal Systems-On-A-Chip

The advent of battery operated sensor-based electronic systems has provided a pressing need to design energy-efficient, ultra-low power integrated circuits as a means to improve the battery lifetime. This dissertation describes a scheme to lower the power requirement of a digital circuit through the use of charge-recycling and dynamic supply-voltage scaling techniques. The novel charge-recycling scheme proposed in this research demonstrates the feasibility of operating digital circuits using the charge scavenged from the leakage and dynamic load currents inherent to digital design. The proposed scheme efficiently gathers the “ground-bound” charge into storage capacitor banks. This reclaimed charge is then subsequently recycled to power the source digital circuit. The charge-recycling methodology has been implemented on a 12-bit Gray-code counter operating at frequencies of less than 50 MHz. The circuit has been designed in a 90-nm process and measurement results reveal more than 41% reduction in the average energy consumption of the counter. The total energy savings including the power consumed for the generation of control signals aggregates to an average of 23%. The proposed methodology can be applied to an existing digital path without any design change to the circuit but with only small loss to the performance. Potential applications of this scheme are described, specifically in wide-temperature dynamic power reduction and as a source for energy harvesters. The second part of this dissertation deals with the design and development of a self-starting, ultra-low voltage, switched-capacitor (SC) DC-DC converter that is essential to an energy harvesting system. The proposed charge-pump based SC-converter operates from 125-mV input and thus enables battery-less operation in ultra-low voltage energy harvesters. The charge pump does not require any external components or expensive post-fabrication processing to enable low-voltage operation. This design has been implemented in a 130-nm CMOS process. While the proposed charge pump provides significant efficiency enhancement in energy harvesters, it can also be incorporated within charge recycling systems to facilitate adaptable charge-recycling levels. In total, this dissertation provides key components needed for highly energy-efficient mixed signal systems-on-a-chip

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

Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing

The development of computing systems based on the conventional von Neumann architecture has slowed down in the past decade as complementary metal-oxide-semiconductor (CMOS) technology scaling becomes more and more difficult. To satisfy the ever-increasing demands in computing power, neuromorphic computing has emerged as an attractive alternative. This dissertation focuses on developing learning algorithm, hardware architecture, circuit components, and design methodologies for low-power neuromorphic computing that can be employed in various energy-constrained applications. A top-down approach is adopted in this research. Starting from the algorithm-architecture co-design, a hardware-friendly learning algorithm is developed for spiking neural networks (SNNs). The possibility of estimating gradients from spike timings is explored. The learning algorithm is developed for the ease of hardware implementation, as well as the compatibility with many well-established learning techniques developed for classic artificial neural networks (ANNs). An SNN hardware equipped with the proposed on-chip learning algorithm is implemented in CMOS technology. In this design, two unique features of SNNs, the event-driven computation and the inferring with a progressive precision, are leveraged to reduce the energy consumption. In addition to low-power SNN hardware, accelerators for ANNs are also presented to accelerate the adaptive dynamic programing algorithm. An efficient and flexible single-instruction-multiple-data architecture is proposed to exploit the inherent data-level parallelism in the inference and learning of ANNs. In addition, the accelerator is augmented with a virtual update technique, which helps improve the throughput and energy efficiency remarkably. Lastly, two techniques in the architecture-circuit level are introduced to mitigate the degraded reliability of the memory system in a neuromorphic hardware owing to the aggressively-scaled supply voltage and integration density. The first method uses on-chip feedback to compensate for the process variation and the second technique improves the throughput and energy efficiency of a conventional error-correction method.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144149/1/zhengn_1.pd

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

Ultra Low Power Digital Circuit Design for Wireless Sensor Network Applications

Ny forskning innenfor feltet trådløse sensornettverk åpner for nye og innovative produkter og løsninger. Biomedisinske anvendelser er blant områdene med størst potensial og det investeres i dag betydelige beløp for å bruke denne teknologien for å gjøre medisinsk diagnostikk mer effektiv samtidig som man åpner for fjerndiagnostikk basert på trådløse sensornoder integrert i et ”helsenett”. Målet er å forbedre tjenestekvalitet og redusere kostnader samtidig som brukerne skal oppleve forbedret livskvalitet som følge av økt trygghet og mulighet for å tilbringe mest mulig tid i eget hjem og unngå unødvendige sykehusbesøk og innleggelser. For å gjøre dette til en realitet er man avhengige av sensorelektronikk som bruker minst mulig energi slik at man oppnår tilstrekkelig batterilevetid selv med veldig små batterier. I sin avhandling ” Ultra Low power Digital Circuit Design for Wireless Sensor Network Applications” har PhD-kandidat Farshad Moradi fokusert på nye løsninger innenfor konstruksjon av energigjerrig digital kretselektronikk. Avhandlingen presenterer nye løsninger både innenfor aritmetiske og kombinatoriske kretser, samtidig som den studerer nye statiske minneelementer (SRAM) og alternative minnearkitekturer. Den ser også på utfordringene som oppstår når silisiumteknologien nedskaleres i takt med mikroprosessorutviklingen og foreslår løsninger som bidrar til å gjøre kretsløsninger mer robuste og skalerbare i forhold til denne utviklingen. De viktigste konklusjonene av arbeidet er at man ved å introdusere nye konstruksjonsteknikker både er i stand til å redusere energiforbruket samtidig som robusthet og teknologiskalerbarhet øker. Forskningen har vært utført i samarbeid med Purdue University og vært finansiert av Norges Forskningsråd gjennom FRINATprosjektet ”Micropower Sensor Interface in Nanometer CMOS Technology”

Combined Time and Information Redundancy for SEU-Tolerance in Energy-Efficient Real-Time Systems

Recently the trade-off between energy consumption and fault-tolerance in real-time systems has been highlighted. These works have focused on dynamic voltage scaling (DVS) to reduce dynamic energy dissipation and on time redundancy to achieve transient-fault tolerance. While the time redundancy technique exploits the available slack time to increase the fault-tolerance by performing recovery executions, DVS exploits slack time to save energy. Therefore we believe there is a resource conflict between the time-redundancy technique and DVS. The first aim of this paper is to propose the usage of information redundancy to solve this problem. We demonstrate through analytical and experimental studies that it is possible to achieve both higher transient fault-tolerance (tolerance to single event upsets (SEU)) and less energy using a combination of information and time redundancy when compared with using time redundancy alone. The second aim of this paper is to analyze the interplay of transient-fault tolerance (SEU-tolerance) and adaptive body biasing (ABB) used to reduce static leakage energy, which has not been addressed in previous studies. We show that the same technique (i.e. the combination of time and information redundancy) is applicable to ABB-enabled systems and provides more advantages than time redundancy alone

A Construction Kit for Efficient Low Power Neural Network Accelerator Designs

Implementing embedded neural network processing at the edge requires efficient hardware acceleration that couples high computational performance with low power consumption. Driven by the rapid evolution of network architectures and their algorithmic features, accelerator designs are constantly updated and improved. To evaluate and compare hardware design choices, designers can refer to a myriad of accelerator implementations in the literature. Surveys provide an overview of these works but are often limited to system-level and benchmark-specific performance metrics, making it difficult to quantitatively compare the individual effect of each utilized optimization technique. This complicates the evaluation of optimizations for new accelerator designs, slowing-down the research progress. This work provides a survey of neural network accelerator optimization approaches that have been used in recent works and reports their individual effects on edge processing performance. It presents the list of optimizations and their quantitative effects as a construction kit, allowing to assess the design choices for each building block separately. Reported optimizations range from up to 10'000x memory savings to 33x energy reductions, providing chip designers an overview of design choices for implementing efficient low power neural network accelerators