The Physics of Computing gives a foundational view of the physical principles underlying computers. Performance, power, thermal behavior, and reliability are all harder and harder to achieve as transistors shrink to nanometer scales. This book describes the physics of computing at all levels of abstraction from single gates to complete computer systems. It can be used as a course for juniors or seniors in computer engineering and electrical engineering, and can also be used to teach students in other scientific disciplines important concepts in computing. For electrical engineering, the book provides the fundamentals of computing that link core concepts to computing. For computer science, it provides foundations of key challenges such as power consumption, performance, and thermal. The book can also be used as a technical reference by professionals. - Links fundamental physics to the key challenges in computer design, including memory wall, power wall, reliability - Provides all of the background necessary to understand the physical underpinnings of key computing concepts - Covers all the major physical phenomena in computing from transistors to systems, including logic, interconnect, memory, clocking, I/O

This book presents a self-contained introduction to the physics of computing, by addressing the fundamental underlying principles that involve the act of computing, regardless of the actual machine that is used to compute. Questions like “what is the minimum energy required to perform a computation?”, “what is the ultimate computational speed that a computer can achieve?” or “how long can a memory last”, are addressed here, starting from basic physics principles. The book is intended for physicists, engineers, and computer scientists, and it is designed for self-study by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. The theoretical concepts presented in this book are systematically developed from the very beginning, which only requires basic knowledge in physics and mathematics.

Why do computers use so much energy? What are the fundamental physical laws governing the relationship between the precise computation run by a system, whether artificial or natural, and how much energy that computation requires? This volume integrates concepts from diverse fields, cultivating a modern, nonequilibrium thermodynamics of computation.

The Physics of Information Technology explores the familiar devices that we use to collect, transform, transmit, and interact with electronic information. Many such devices operate surprisingly close to very many fundamental physical limits. Understanding how such devices work, and how they can (and cannot) be improved, requires deep insight into the character of physical law as well as engineering practice. The book starts with an introduction to units, forces, and the probabilistic foundations of noise and signalling, then progresses through the electromagnetics of wired and wireless communications, and the quantum mechanics of electronic, optical, and magnetic materials, to discussions of mechanisms for computation, storage, sensing, and display. This self-contained volume will help both physical scientists and computer scientists see beyond the conventional division between hardware and software to understand the implications of physical theory for information manipulation.

A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields.

How differing assessments of risk by physicists and computer scientists have influenced public debate over nuclear defense. In a rapidly changing world, we rely upon experts to assess the promise and risks of new technology. But how do these experts make sense of a highly uncertain future? In Arguments that Count, Rebecca Slayton offers an important new perspective. Drawing on new historical documents and interviews as well as perspectives in science and technology studies, she provides an original account of how scientists came to terms with the unprecedented threat of nuclear-armed intercontinental ballistic missiles (ICBMs). She compares how two different professional communities—physicists and computer scientists—constructed arguments about the risks of missile defense, and how these arguments changed over time. Slayton shows that our understanding of technological risks is shaped by disciplinary repertoires—the codified knowledge and mathematical rules that experts use to frame new challenges. And, significantly, a new repertoire can bring long-neglected risks into clear view. In the 1950s, scientists recognized that high-speed computers would be needed to cope with the unprecedented speed of ICBMs. But the nation's elite science advisors had no way to analyze the risks of computers so used physics to assess what they could: radar and missile performance. Only decades later, after establishing computing as a science, were advisors able to analyze authoritatively the risks associated with complex software—most notably, the risk of a catastrophic failure. As we continue to confront new threats, including that of cyber attack, Slayton offers valuable insight into how different kinds of expertise can limit or expand our capacity to address novel technological risks.

When, in 1984?86, Richard P. Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a ?Feynmanesque? overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.