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.

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 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. These simplifications translate into lower power consumption, smaller form factors, and dynamic data rates that are tolerant to clock discrepancies between transmitter and receiver. Readers will be introduced to signal encoding that uses edge-coded signaling, based on the coding of binary data as counts of transmitted pulses. The authors fully explore the far-reaching implications of these novel signal-encoding techniques and illustrate how their usage can help minimize the need for complex circuitries for either clock and data recovery or duty-cycle correction. They also provide a detailed description of a complete ecosystem of hardware and firmware built around edge-code signaling. The ecosystem comprises an application-specific processor, automatic protocol configuration, power and data rate management, cryptographic primitives, and automatic failure recovery modes. The innovative IoT communication link and its associated ecosystem are fully in line with the standard IoT requirements on power, footprint, security, robustness, and reliability.

This book addresses important aspects of MEMS designs that are well established in engineering practice but rarely discussed in the standard textbooks. One such aspect is the ubiquitous use of tapered beams in the sensing and actuation elements of MEMS designs. As explained in this book, the tapered beam has distinct advantages over the standard rectangular beam but these advantages are often left unarticulated due to the blind trust in the finite-element models of MEMS devices. In this monograph, the authors take a fundamental, physics-based approach to the modeling of tapered beams in MEMS that is based on a rigorous perturbation analysis of the traditional Euler-Bernoulli beam. The authors demonstrate how perturbation methods combined with symbolic modeling and the tools of computer algebra enable the development of semi-analytical models for tapered-beam MEMS elements. They pay particular attention to the application of these novel models to piezoelectric MEMS energy harvesters with tapered-beam elements, including the development of lumped-parameter circuit models that can be readily used for fast electro-mechanical simulations. Another important aspect of MEMS designs that is extensively addressed in the book is the uncertainty quantification (UQ) of tapered-beam MEMS elements using both Monte Carlo and polynomial chaos expansion methods. These UQ methods are applied to the design of variation-aware piezoelectric energy harvesters. With consistent focus on MEMS devices with tapered beam elements, this up-to-date monograph

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.