Energy efficient implementation of multi-phase quasi-adiabatic Cyclic Redundancy Check in near field communication

Ultra-low power operation in power-limited portable devices (e.g. cell phone and smartcard) is paramount. Existing conventional CMOS consume high energy. The adiabatic logic technique has the potential of rendering energy efficient operation. In this paper, a multi-phase quasi-adiabatic implementation of 16-bit Cyclic Redundancy Check (CRC) is proposed, compliant with the ISO/IEC-14443 standard for contactless smart cards. In terms of a number of CRC bits, the design is scalable and all generator polynomials and initial load values can be accommodated. The CRC design is used as a vehicle to evaluate a range of adiabatic logic styles and power-clock strategies. The effects of voltage scaling and variations in Process-Voltage-Temperature (PVT) are also investigated providing an insight into the robustness of adiabatic logic styles. PFAL and IECRL designs using a 4-phase power-clock are shown to be both the most energy-efficient and robust designs

Adiabatic Approach for Low-Power Passive Near Field Communication Systems

This thesis tackles the need of ultra-low power electronics in the power limited passive Near Field Communication (NFC) systems. One of the techniques that has proven the potential of delivering low power operation is the Adiabatic Logic Technique. However, the low power benefits of the adiabatic circuits come with the challenges due to the absence of single opinion on the most energy efficient adiabatic logic family which constitute appropriate trade-offs between computation time, area and complexity based on the circuit and the power-clocking schemes. Therefore, five energy efficient adiabatic logic families working in single-phase, 2-phase and 4-phase power-clocking schemes were chosen. Since flip-flops are the basic building blocks of any sequential circuit and the existing flip-flops are MUX-based (having more transistors) design, therefore a novel single-phase, 2-phase and 4-phase reset based flip-flops were proposed. The performance of the multi-phase adiabatic families was evaluated and compared based on the design examples such as 2-bit ring counter, 3-bit Up-Down counter and 16-bit Cyclic Redundancy Check (CRC) circuit (benchmark circuit) based on ISO 14443-3A standard. Several trade-offs, design rules, and an appropriate range for the supply voltage scaling for multi-phase adiabatic logic are proposed. Furthermore, based on the NFC standard (ISO 14443-3A), data is frequently encoded using Manchester coding technique before transmitting it to the reader. Therefore, if Manchester encoding can be implemented using adiabatic logic technique, energy benefits are expected. However, adiabatic implementation of Manchester encoding presents a challenge. Therefore, a novel method for implementing Manchester encoding using adiabatic logic is proposed overcoming the challenges arising due to the AC power-clock. Other challenges that come with the dynamic nature of the adiabatic gates and the complexity of the 4-phase power-clocking scheme is in synchronizing the power-clock v phases and the time spent in designing, validation and debugging of errors. This requires a specific modelling approach to describe the adiabatic logic behaviour at the higher level of abstraction. However, describing adiabatic logic behaviour using Hardware Description Languages (HDLs) is a challenging problem due to the requirement of modelling the AC power-clock and the dual-rail inputs and outputs. Therefore, a VHDL-based modelling approach for the 4-phase adiabatic logic technique is developed for functional simulation, precise timing analysis and as an improvement over the previously described approaches

Carbon Nanotube Interconnect Modeling for Very Large Scale Integrated Circuits

In this research, we have studied and analyzed the physical and electrical properties of carbon nanotubes. Based on the reported models for current transport behavior in non-ballistic CNT-FETs, we have built a dynamic model for non-ballistic CNT-FETs. We have also extended the surface potential model of a non-ballistic CNT-FET to a ballistic CNT-FET and developed a current transport model for ballistic CNT-FETs. We have studied the current transport in metallic carbon nanotubes. By considering the electron-electron interactions, we have modified two-dimensional fluid model for electron transport to build a semi-classical one-dimensional fluid model to describe the electron transport in carbon nanotubes, which is regarded as one-dimensional system. Besides its accuracy compared with two-dimensional fluid model and Lüttinger liquid theory, one-dimensional fluid model is simple in mathematical modeling and easier to extend for electronic transport modeling of multi-walled carbon nanotubes and single-walled carbon nanotube bundles as interconnections. Based on our reported one-dimensional fluid model, we have calculated the parameters of the transmission line model for the interconnection wires made of single-walled carbon nanotube, multi-walled carbon nanotube and single-walled carbon nanotube bundle. The parameters calculated from these models show close agreements with experiments and other proposed models. We have also implemented these models to study carbon nanotube for on-chip wire inductors and it application in design of LC voltage-controlled oscillators. By using these CNT-FET models and CNT interconnects models, we have studied the behavior of CNT based integrated circuits, such as the inverter, ring oscillator, energy recovery logic; and faults in CNT based circuits

Research on low power technology by AC power supply circuits

制度:新 ; 報告番号:甲3692号 ; 学位の種類:博士(工学) ; 授与年月日:2012/9/15 ; 早大学位記番号:新6060Waseda Universit

Energy efficiency of 2- Step power-clocks for adiabatic logic

The generation of power-clocks in adiabatic integrated circuits is investigated. Specifically, we consider the energy efficiency of a 2-step charging strategy based on a single tank-capacitor circuit. We have investigated the impact of various parameters such as tank-capacitance to load capacitance ratio, ramping time, transistors sizing and power supply voltage scaling on energy recovery achievable in the 2-step charging circuit. We show that energy recovery achievable in the 2-step charging circuit depends on the tank-capacitor and load capacitor size concluding that tank-capacitance (CT) versus load capacitance (CL) is the significant parameter. We also show that the energy performance depends on the ramping time and improves for higher ramping times (lower frequencies). Energy recovery also improves if the transistors sizes in the step charging circuit are sized at their minimum dimensions. Lastly, we show that energy recovery decreases as the power supply voltage is scaled down. Specifically, the decrease in the energy recovery with decreasing power supply is significant for lower ramping times (higher frequencies). We propose that a Ct/Cl ratio of 10, keeping the width of the transistors in the step charging circuit minimum, can be chosen as a convenient `rule-of-thumb' in practical designs

Energy-efficiency improvements for optical access

This article discusses novel approaches to improve energy efficiency of different optical access technologies, including time division multiplexing passive optical network (TDM-PON), time and wavelength division multiplexing PON (TWDM-PON), point-to-point (PTP) access network, wavelength division multiplexing PON (WDM-PON), and orthogonal frequency division multiple access PON (OFDMA-PON). These approaches include cyclic sleep mode, energy-efficient bit interleaving protocol, power reduction at component level, or frequency band selection. Depending on the target optical access technology, one or a combination of different approaches can be applied

Adiabatic smart card / RFID.

Mok, King Keung.Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.Includes bibliographical references (leaves 77-79).Abstracts in English and Chinese.Abstract --- p.1Contents --- p.5List of Figures --- p.7List of Tables --- p.10Acknowledgments --- p.11Chapter 1. --- Introduction --- p.12Chapter 1.1. --- Low Power Design --- p.12Chapter 1.2. --- Power Consumption in Conventional CMOS Logic --- p.13Chapter 1.2.1. --- Dynamic Power --- p.13Chapter 1.2.2. --- Short-Circuit Power --- p.15Chapter 1.2.3. --- Leakage Power --- p.17Chapter 1.2.4. --- Static Power --- p.19Chapter 1.3. --- Smart Card / RFID --- p.21Chapter 1.3.1. --- Applications --- p.21Chapter 1.3.2. --- Operating Principle --- p.22Chapter 1.3.3. --- Conventional Architecture --- p.23Chapter 2. --- Adiabatic Logic --- p.25Chapter 2.1. --- Adiabatic Switching --- p.25Chapter 2.2. --- Energy Recovery --- p.27Chapter 2.3. --- Adiabatic Quasi-Static CMOS Logic --- p.29Chapter 2.3.1. --- Logic Structure --- p.29Chapter 2.3.2. --- Clocking Scheme --- p.31Chapter 2.3.3. --- Flip-flop --- p.33Chapter 2.3.4. --- Layout Techniques --- p.38Chapter 3. --- Adiabatic RFID --- p.41Chapter 3.1. --- System Architecture --- p.41Chapter 3.2. --- Circuit Design --- p.42Chapter 3.2.1. --- Voltage Limiter --- p.43Chapter 3.2.2. --- Substrate Bias Generation Circuit --- p.45Chapter 3.2.3. --- Ring Oscillator --- p.46Chapter 3.2.4. --- ROM and Control Logic --- p.48Chapter 3.2.5. --- Load Modulator --- p.52Chapter 3.2.6. --- Experimental Results --- p.53Chapter 4. --- Adiabatic Smart Card --- p.59Chapter 4.1. --- System Architecture --- p.59Chapter 4.2. --- Circuit Design --- p.61Chapter 4.2.1. --- ASK Demodulator --- p.61Chapter 4.2.2. --- Clock Recovery Circuit --- p.63Chapter 4.3. --- Experimental Results --- p.67Chapter 5. --- Conclusion --- p.74Chapter 6. --- Future Works --- p.76Reference --- p.77Appendix --- p.8

Energy-Efficient Neural Network Architectures

Emerging systems for artificial intelligence (AI) are expected to rely on deep neural networks (DNNs) to achieve high accuracy for a broad variety of applications, including computer vision, robotics, and speech recognition. Due to the rapid growth of network size and depth, however, DNNs typically result in high computational costs and introduce considerable power and performance overheads. Dedicated chip architectures that implement DNNs with high energy efficiency are essential for adding intelligence to interactive edge devices, enabling them to complete increasingly sophisticated tasks by extending battery lie. They are also vital for improving performance in cloud servers that support demanding AI computations. This dissertation focuses on architectures and circuit technologies for designing energy-efficient neural network accelerators. First, a deep-learning processor is presented for achieving ultra-low power operation. Using a heterogeneous architecture that includes a low-power always-on front-end and a selectively-enabled high-performance back-end, the processor dynamically adjusts computational resources at runtime to support conditional execution in neural networks and meet performance targets with increased energy efficiency. Featuring a reconfigurable datapath and a memory architecture optimized for energy efficiency, the processor supports multilevel dynamic activation of neural network segments, performing object detection tasks with 5.3x lower energy consumption in comparison with a static execution baseline. Fabricated in 40nm CMOS, the processor test-chip dissipates 0.23mW at 5.3 fps. It demonstrates energy scalability up to 28.6 TOPS/W and can be configured to run a variety of workloads, including severely power-constrained ones such as always-on monitoring in mobile applications. To further improve the energy efficiency of the proposed heterogeneous architecture, a new charge-recovery logic family, called zero-short-circuit current (ZSCC) logic, is proposed to decrease the power consumption of the always-on front-end. By relying on dedicated circuit topologies and a four-phase clocking scheme, ZSCC operates with significantly reduced short-circuit currents, realizing order-of-magnitude power savings at relatively low clock frequencies (in the order of a few MHz). The efficiency and applicability of ZSCC is demonstrated through an ANSI S1.11 1/3 octave filter bank chip for binaural hearing aids with two microphones per ear. Fabricated in a 65nm CMOS process, this charge-recovery chip consumes 13.8µW with a 1.75MHz clock frequency, achieving 9.7x power reduction per input in comparison with a 40nm monophonic single-input chip that represents the published state of the art. The ability of ZSCC to further increase the energy efficiency of the heterogeneous neural network architecture is demonstrated through the design and evaluation of a ZSCC-based front-end. Simulation results show 17x power reduction compared with a conventional static CMOS implementation of the same architecture.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147614/1/hsiwu_1.pd