Robust Nano-Computing focuses on various issues of robust nano-computing, defect-tolerance design for nano-technology at different design abstraction levels. It addresses both redundancy- and configuration-based methods as well as fault detecting techniques through the development of accurate computation models and tools. The contents present an insightful view of the ongoing researches on nano-electronic devices, circuits, architectures, and design methods, as well as provide promising directions for future research.

This reference text covers a wide spectrum for designing robust embedded memory and peripheral circuitry. It will serve as a useful text for senior undergraduate and graduate students and professionals in areas including electronics and communications engineering, electrical engineering, mechanical engineering, and aerospace engineering. Discusses low-power design methodologies for static random-access memory (SRAM) Covers radiation-hardened SRAM design for aerospace applications Focuses on various reliability issues that are faced by submicron technologies Exhibits more stable memory topologies Nanoscale technologies unveiled significant challenges to the design of energy- efficient and reliable SRAMs. This reference text investigates the impact of process variation, leakage, aging, soft errors and related reliability issues in embedded memory and periphery circuitry. The text adopts a unique way to explain the SRAM bitcell, array design, and analysis of its design parameters to meet the sub-nano-regime challenges for complementary metal-oxide semiconductor devices. It comprehensively covers low- power-design methodologies for SRAM, exhibits more stable memory topologies, and radiation-hardened SRAM design for aerospace applications. Every chapter includes a glossary, highlights, a question bank, and problems. The text will serve as a useful text for senior undergraduate students, graduate students, and professionals in areas including electronics and communications engineering, electrical engineering, mechanical engineering, and aerospace engineering. Discussing comprehensive studies of variability-induced failure mechanism in sense amplifiers and power, delay, and read yield trade-offs, this reference text will serve as a useful text for senior undergraduate, graduate students, and professionals in areas including electronics and communications engineering, electrical engineering, mechanical engineering, and aerospace engineering. It covers the development of robust SRAMs, well suited for low-power multi-core processors for wireless sensors node, battery-operated portable devices, personal health care assistants, and smart Internet of Things applications.

This book comprehensively and systematically treats modern understanding of the Nano-Bio-Technology and its therapeutic applications. The contents range from the nanomedicine, imaging, targeted therapeutic applications, experimental results along with modelling approaches. It will provide the readers with fundamentals on computational and modelling aspects of advanced nano-materials and nano-technology specifically in the field of biomedicine, and also provide the readers with inspirations for new development of diagnostic imaging and targeted therapeutic applications.

This book explains the application of recent advances in computational intelligence – algorithms, design methodologies, and synthesis techniques – to the design of integrated circuits and systems. It highlights new biasing and sizing approaches and optimization techniques and their application to the design of high-performance digital, VLSI, radio-frequency, and mixed-signal circuits and systems. This second of two related volumes addresses digital and network designs and applications, with 12 chapters grouped into parts on digital circuit design, network optimization, and applications. It will be of interest to practitioners and researchers in computer science and electronics engineering engaged with the design of electronic circuits.

Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities—and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks. The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware. Includes cross-layer survey of hardware accelerators for neuromorphic algorithms Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.

Computational Finite Element Methods in Nanotechnology demonstrates the capabilities of finite element methods in nanotechnology for a range of fields. Bringing together contributions from researchers around the world, it covers key concepts as well as cutting-edge research and applications to inspire new developments and future interdisciplinary research. In particular, it emphasizes the importance of finite element methods (FEMs) for computational tools in the development of efficient nanoscale systems. The book explores a variety of topics, including: A novel FE-based thermo-electrical-mechanical-coupled model to study mechanical stress, temperature, and electric fields in nano- and microelectronics The integration of distributed element, lumped element, and system-level methods for the design, modeling, and simulation of nano- and micro-electromechanical systems (N/MEMS) Challenges in the simulation of nanorobotic systems and macro-dimensions The simulation of structures and processes such as dislocations, growth of epitaxial films, and precipitation Modeling of self-positioning nanostructures, nanocomposites, and carbon nanotubes and their composites Progress in using FEM to analyze the electric field formed in needleless electrospinning How molecular dynamic (MD) simulations can be integrated into the FEM Applications of finite element analysis in nanomaterials and systems used in medicine, dentistry, biotechnology, and other areas The book includes numerous examples and case studies, as well as recent applications of microscale and nanoscale modeling systems with FEMs using COMSOL Multiphysics® and MATLAB®. A one-stop reference for professionals, researchers, and students, this is also an accessible introduction to computational FEMs in nanotechnology for those new to the field.

One of the grand challenges in the nano-scopic computing era is guarantees of robustness. Robust computing system design is confronted with quantum physical, probabilistic, and even biological phenomena, and guaranteeing high reliability is much more difficult than ever before. Scaling devices down to the level of single electron operation will bring forth new challenges due to probabilistic effects and uncertainty in guaranteeing 'zero-one' based computing. Minuscule devices imply billions of devices on a single chip, which may help mitigate the challenge of uncertainty by replication and redundancy. However, such device densities will create a design and validation nightmare with the shear scale. The questions that confront computer engineers regarding the current status of nanocomputing material and the reliability of systems built from such miniscule devices, are difficult to articulate and answer. We have found a lack of resources in the confines of a single volume that at least partially attempts to answer these questions. We believe that this volume contains a large amount of research material as well as new ideas that will be very useful for some one starting research in the arena of nanocomputing, not at the device level, but the problems one would face at system level design and validation when nanoscopic physicality will be present at the device level.

The primary aim of this book is to discuss various aspects of nanoscale device design and their applications including transport mechanism, modeling, and circuit applications. . Provides a platform for modeling and analysis of state-of-the-art devices in nanoscale regime, reviews issues related to optimizing the sub-nanometer device performance and addresses simulation aspect and/or fabrication process of devices Also, includes design problems at the end of each chapter

Society is approaching and advancing nano- and microtechnology from various angles of science and engineering. The need for further fundamental, applied, and experimental research is matched by the demand for quality references that capture the multidisciplinary and multifaceted nature of the science. Presenting cutting-edge information that is applicable to many fields, Nano- and Micro-Electromechanical Systems: Fundamentals of Nano and Microengineering, Second Edition builds the theoretical foundation for understanding, modeling, controlling, simulating, and designing nano- and microsystems. The book focuses on the fundamentals of nano- and microengineering and nano- and microtechnology. It emphasizes the multidisciplinary principles of NEMS and MEMS and practical applications of the basic theory in engineering practice and technology development. Significantly revised to reflect both fundamental and technological aspects, this second edition introduces the concepts, methods, techniques, and technologies needed to solve a wide variety of problems related to high-performance nano- and microsystems. The book is written in a textbook style and now includes homework problems, examples, and reference lists in every chapter, as well as a separate solutions manual. It is designed to satisfy the growing demands of undergraduate and graduate students, researchers, and professionals in the fields of nano- and microengineering, and to enable them to contribute to the nanotechnology revolution.

This book describes novel software concepts to increase reliability under user-defined constraints. The authors’ approach bridges, for the first time, the reliability gap between hardware and software. Readers will learn how to achieve increased soft error resilience on unreliable hardware, while exploiting the inherent error masking characteristics and error (stemming from soft errors, aging, and process variations) mitigations potential at different software layers.