ARTIFICIAL INTELLIGENCE FOR SEMICONDUCTOR DESIGN (VLSI Design & Semiconductor Engineering)

This book grew out of a simple observation: the field of artificial intelligence for semiconductor design has, within the span of little more than a decade, evolved from a handful of academic curiosities into a body of techniques that touches nearly every stage of how modern chips are conceived, designed, verified, and manufactured. Yet much of the literature documenting this evolution remains scattered across conference papers, vendor white papers, and specialized workshops, without a single volume attempting to draw these threads together into a coherent, comprehensive account suitable for graduate students, practicing engineers, and technology strategists alike.
This book aims to fill that gap. It is written for readers who bring either a computer science and machine learning background and wish to understand the specifics of semiconductor design, or an electrical engineering and VLSI design background and wish to understand how contemporary AI techniques apply to their domain. Chapters are organized to be reasonably self-contained, with cross-references connecting related material, so that readers may approach the book either sequentially, as a complete course of study, or selectively, focusing on the chapters most relevant to their specific interests.
Throughout, I have tried to balance two competing instincts: the desire to convey genuine enthusiasm for what AI has already demonstrably achieved in this field, and an equally important commitment to methodological honesty about what remains uncertain, unproven, or actively debated — most notably in the discussion of reinforcement-learning-based floorplanning in Chapter 13, where I have tried to present both the genuine excitement the original results generated and the important scientific scrutiny that followed. My hope is that readers come away from this book not merely informed about a set of techniques, but equipped with the critical, evidence-based judgment needed to evaluate new claims as this fast-moving field continues to evolve.
I am grateful to the broader community of researchers, engineers, and educators whose published work, conference presentations, and open technical discussions have shaped the understanding this book attempts to synthesize. Any errors of fact or interpretation that remain are, of course, my own.