Ibrahim (Abe) M. Elfadel – författare

This book provides readers with an up-to-date account of the use of machine learning frameworks, methodologies, algorithms and techniques in the context of computer-aided design (CAD) for very-large-scale integrated circuits (VLSI). Coverage includes the various machine learning methods used in lithography, physical design, yield prediction, post-silicon performance analysis, reliability and failure analysis, power and thermal analysis, analog design, logic synthesis, verification, and neuromorphic design. Provides up-to-date information on machine learning in VLSI CAD for device modeling, layout verifications, yield prediction, post-silicon validation, and reliability;Discusses the use of machine learning techniques in the context of analog and digital synthesis;Demonstrates how to formulate VLSI CAD objectives as machine learning problems and provides a comprehensive treatment of their efficient solutions;Discusses the tradeoff between the cost of collecting data and prediction accuracy and provides a methodology for using prior data to reduce cost of data collection in the design, testing and validation of both analog and digital VLSI designs.From the Foreword As the semiconductor industry embraces the rising swell of cognitive systems and edge intelligence, this book could serve as a harbinger and example of the osmosis that will exist between our cognitive structures and methods, on the one hand, and the hardware architectures and technologies that will support them, on the other….As we transition from the computing era to the cognitive one, it behooves us to remember the success story of VLSI CAD and to earnestly seek the help of the invisible hand so that our future cognitive systems are used to design more powerful cognitive systems. This book is very much aligned with this on-going transition from computing to cognition, and it is with deep pleasure thatI recommend it to all those who are actively engaged in this exciting transformation.Dr. Ruchir Puri, IBM Fellow, IBM Watson CTO & Chief Architect, IBM T. J. Watson Research Center

This book documents some of the most recent advances on the physical layer of the Internet of Things (IoT), including sensors, circuits, and systems. The book is unique in that it adopts a holistic view of such systems and includes not only the sensor and processing subsystems, but also the power, communication, and security subsystems.

This book contains extended and revised versions of the best papers presented at the 25th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2017, held in Abu Dhabi, United Arab Emirates, in August 2017.

This book contains extended and revised versions of the best papers presented at the 25th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2017, held in Abu Dhabi, United Arab Emirates, in August 2017.

This book discusses single-channel, device-to-device communication in the Internet of Things (IoT) at the signal encoding level and introduces a new family of encoding techniques that result in significant simplifications of the communication circuitry.

This book discusses single-channel, device-to-device communication in the Internet of Things (IoT) at the signal encoding level and introduces a new family of encoding techniques that result in significant simplifications of the communication circuitry.

This book addresses important aspects of MEMS designs that are well established in engineering practice but rarely discussed in the standard textbooks.

This book contains revised and extended versions of a selection of  papers presented at the 31st IFIP WG 10.5/IEEE International Conference on the theme of VLSI-SoC Innovations for Trustworthy Artificial Intelligence, VLSI-SoC 2023, held in Sharjah, United Arab Emirates, during October 16–18, 2023.The 15 full papers included in this volume were carefully revised and expanded from 77 papers submitted to the conference. This edited volume has been organized into four parts: architectures; accelerators; resiliency and robustness; and security and privacy -  and is representing cutting-edge research at the forefront of VLSI technology.

This book explains for readers how 3D chip stacks promise to increase the level of on-chip integration, and to design new heterogeneous semiconductor devices that combine chips of different integration technologies (incl. sensors) in a single package of the smallest possible size.  The authors focus on heterogeneous 3D integration, addressing some of the most important challenges in this emerging technology, including contactless, optics-based, and carbon-nanotube-based 3D integration, as well as signal-integrity and thermal management issues in copper-based 3D integration. Coverage also includes the 3D heterogeneous integration of power sources, photonic devices, and non-volatile memories based on new materials systems.

This book explains for readers how 3D chip stacks promise to increase the level of on-chip integration, and to design new heterogeneous semiconductor devices that combine chips of different integration technologies (incl.