Null Convention Logic applications of asynchronous design in nanotechnology and cryptographic security

This dissertation presents two Null Convention Logic (NCL) applications of asynchronous logic circuit design in nanotechnology and cryptographic security. The first application is the Asynchronous Nanowire Reconfigurable Crossbar Architecture (ANRCA); the second one is an asynchronous S-Box design for cryptographic system against Side-Channel Attacks (SCA). The following are the contributions of the first application: 1) Proposed a diode- and resistor-based ANRCA (DR-ANRCA). Three configurable logic block (CLB) structures were designed to efficiently reconfigure a given DR-PGMB as one of the 27 arbitrary NCL threshold gates. A hierarchical architecture was also proposed to implement the higher level logic that requires a large number of DR-PGMBs, such as multiple-bit NCL registers. 2) Proposed a memristor look-up-table based ANRCA (MLUT-ANRCA). An equivalent circuit simulation model has been presented in VHDL and simulated in Quartus II. Meanwhile, the comparison between these two ANRCAs have been analyzed numerically. 3) Presented the defect-tolerance and repair strategies for both DR-ANRCA and MLUT-ANRCA. The following are the contributions of the second application: 1) Designed an NCL based S-Box for Advanced Encryption Standard (AES). Functional verification has been done using Modelsim and Field-Programmable Gate Array (FPGA). 2) Implemented two different power analysis attacks on both NCL S-Box and conventional synchronous S-Box. 3) Developed a novel approach based on stochastic logics to enhance the resistance against DPA and CPA attacks. The functionality of the proposed design has been verified using an 8-bit AES S-box design. The effects of decision weight, bitstream length, and input repetition times on error rates have been also studied. Experimental results shows that the proposed approach enhances the resistance to against the CPA attack by successfully protecting the hidden key --Abstract, page iii

2022 roadmap on neuromorphic computing and engineering

Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10$^{18}$ calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community

Cutting Edge Nanotechnology

The main purpose of this book is to describe important issues in various types of devices ranging from conventional transistors (opening chapters of the book) to molecular electronic devices whose fabrication and operation is discussed in the last few chapters of the book. As such, this book can serve as a guide for identifications of important areas of research in micro, nano and molecular electronics. We deeply acknowledge valuable contributions that each of the authors made in writing these excellent chapters

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

Simulation and implementation of novel deep learning hardware architectures for resource constrained devices

Corey Lammie designed mixed signal memristive-complementary metal–oxide–semiconductor (CMOS) and field programmable gate arrays (FPGA) hardware architectures, which were used to reduce the power and resource requirements of Deep Learning (DL) systems; both during inference and training. Disruptive design methodologies, such as those explored in this thesis, can be used to facilitate the design of next-generation DL systems

Predicting power scalability in a reconfigurable platform

This thesis focuses on the evolution of digital hardware systems. A reconfigurable platform is proposed and analysed based on thin-body, fully-depleted silicon-on-insulator Schottky-barrier transistors with metal gates and silicide source/drain (TBFDSBSOI). These offer the potential for simplified processing that will allow them to reach ultimate nanoscale gate dimensions. Technology CAD was used to show that the threshold voltage in TBFDSBSOI devices will be controllable by gate potentials that scale down with the channel dimensions while remaining within appropriate gate reliability limits. SPICE simulations determined that the magnitude of the threshold shift predicted by TCAD software would be sufficient to control the logic configuration of a simple, regular array of these TBFDSBSOI transistors as well as to constrain its overall subthreshold power growth. Using these devices, a reconfigurable platform is proposed based on a regular 6-input, 6-output NOR LUT block in which the logic and configuration functions of the array are mapped onto separate gates of the double-gate device. A new analytic model of the relationship between power (P), area (A) and performance (T) has been developed based on a simple VLSI complexity metric of the form ATσ = constant. As σ defines the performance “return” gained as a result of an increase in area, it also represents a bound on the architectural options available in power-scalable digital systems. This analytic model was used to determine that simple computing functions mapped to the reconfigurable platform will exhibit continuous power-area-performance scaling behavior. A number of simple arithmetic circuits were mapped to the array and their delay and subthreshold leakage analysed over a representative range of supply and threshold voltages, thus determining a worse-case range for the device/circuit-level parameters of the model. Finally, an architectural simulation was built in VHDL-AMS. The frequency scaling described by σ, combined with the device/circuit-level parameters predicts the overall power and performance scaling of parallel architectures mapped to the array

Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented