This book describes computing innovation, using non-volatile memory for a sustainable world. It appeals to both computing engineers and device engineers by describing a new means of lower power computing innovation, without sacrificing performance over conventional low-voltage operation. Readers will be introduced to methods of design and implementation for non-volatile memory which allow computing equipment to be turned off normally when not in use and to be turned on instantly to operate with full performance when needed.

Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. As computers increase in speed and power, their energy issues become more and more prevalent. The need to develop and promote environmentally friendly computer technologies and systems has also come to the forefront

This book provides basic and fundamental knowledge of various aspects of energy-aware computing at the component, software, and system level. It provides a broad range of topics dealing with power-, energy-, and temperature-related research areas for individuals from industry and academia.

Nanotechnology for Microelectronics and Photonics, Second Edition has been thoroughly revised, expanded, and updated. The aim of the book is to present the most recent advances in the field of nanomaterials, as well as the devices being developed for novel nanoelectronics and nanophotonic systems. It covers the many novel nanoscale applications in microelectronics and photonics that have been developed in recent years. Looking to the future, the book suggests what other applications are currently in development and may become feasible within the next few decades based on novel materials such as graphene, nanotubes, and organic semiconductors. In addition, the inclusion of new chapters and new sections to keep up with the latest developments in this rapidly-evolving field makes Nanotechnology for Microelectronics and Photonics, Second Edition an invaluable reference to research and industrial scientists looking for a guide on how nanostructured materials and nanoscale devices are used in microelectronics, optoelectronics, and photonics today and in future developments. - Presents the fundamental scientific principles that explain the novel properties and applications of nanostructured materials in the quantum frontier - Offers clear and concise coverage of how nanotechnology is currently used in the areas of microelectronics, optoelectronics, and photonics, as well as future proposed devices - Includes nearly a hundred problems along with helpful hints and full solutions for more than half of them

Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system. This is driven by the requirements of data-intensive applications in artificial intelligence, autonomous systems, and edge computing. We are at an exciting time in the semiconductor industry where several innovative device and technology concepts are being developed to respond to these demands, and capture shares of the fast growing market for AI-related hardware. This special issue is devoted to highlighting, discussing and presenting the latest advancements in this area, drawing on the best work on emerging memory devices including magnetic, resistive, phase change, and other types of memory. The special issue is interested in work that presents concepts, ideas, and recent progress ranging from materials, to memory devices, physics of switching mechanisms, circuits, and system applications, as well as progress in modeling and design tools. Contributions that bridge across several of these layers are especially encouraged.

Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making. Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.

This book constitutes the refereed conference proceedings of the Third International Conference on Emerging Technologies in Computing, iCEtiC 2020, held in London, UK, in August 2020. Due to VOVID-19 pandemic the conference was helt virtually.The 25 revised full papers were reviewed and selected from 65 submissions and are organized in topical sections covering blockchain and cloud computing; security, wireless sensor networks and IoT; AI, big data and data analytics; emerging technologies in engineering, education and sustainable development.

The papers of this volume focus on the foundational aspects of computer science, the thematic origin and stronghold of LNCS, under the title “Computing and Software Science: State of the Art and Perspectives”. They are organized in two parts: The first part, Computation and Complexity, presents a collection of expository papers on fashionable themes in algorithmics, optimization, and complexity. The second part, Methods, Languages and Tools for Future System Development, aims at sketching the methodological evolution that helps guaranteeing that future systems meet their increasingly critical requirements. Chapter 3 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

The book intends to bring under one roof research work of leading groups from across the globe working on advanced applications of emerging memory technology nanodevices. The applications dealt in the text will be beyond conventional storage application of semiconductor memory devices. The text will deal with material and device physical principles that give rise to interesting characteristics and phenomena in the emerging memory device that can be exploited for a wide variety of applications. Applications covered will include system-centric cases such as – caches, NVSRAM, NVTCAM, Hybrid CMOS-RRAM circuits for: Machine Learning, In-Memory Computing, Hardware Security - RNG/PUF, Biosensing and other misc beyond storage applications. The book is envisioned for multi-purpose use as a textbook in advanced UG/PG courses and a research text for scientists working in the domain.

The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. This, the 24th issue of the Transactions on Computational Science journal, guest edited by Himanshu Thapliyal and Nagarajan Ranganathan, is devoted to the topic of reversible computing. It is comprised of eight selected papers on reversible energy recovery designs, design of reversible logic gates and arithmetic circuits in optical computing, reversible basic linear algebra subprograms, quantum circuit description language, and reversible circuit and logic synthesis.