The computing world is in the middle of a revolution: mobile clients and cloud computing have emerged as the dominant paradigms driving programming and hardware innovation. This book focuses on the shift, exploring the ways in which software and technology in the 'cloud' are accessed by cell phones, tablets, laptops, and more

This book is a comprehensive text on basic, undergraduate-level computer architecture. It starts from theoretical preliminaries and simple Boolean algebra. After a quick discussion on logic gates, it describes three classes of assembly languages: a custom RISC ISA called SimpleRisc, ARM, and x86. In the next part, a processor is designed for the SimpleRisc ISA from scratch. This includes the combinational units, ALUs, processor, basic 5-stage pipeline, and a microcode-based design. The last part of the book discusses caches, virtual memory, parallel programming, multiprocessors, storage devices and modern I/O systems. The book's website has links to slides for each chapter and video lectures hosted on YouTube.

The dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure. Software architects, developers, and even data scientists need to understand how exploit the fundamental structure of computer performance to harness it for future applications. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast – how size scaling drives performance; Implicit parallelism – how a sequential program can be executed faster with parallelism; Dynamic locality – skirting physical limits, by arranging data in a smaller space; Parallelism – increasing performance with teams of workers. These principles and models provide approachable high-level insights and quantitative modelling without distracting low-level detail. Finally, the text covers the GPU and machine-learning accelerators that have become increasingly important for mainstream applications.

This textbook provides a clear and concise introduction to computer architecture and implementation. Two important themes are interwoven throughout the book. The first is an overview of the major concepts and design philosophies of computer architecture and organization. The second is the early introduction and use of analytic modeling of computer performance. A unique feature of the book is that memory systems are discussed before processor implementations. The book contains many worked examples and over 130 homework exercises. It is an ideal textbook for a one-semester undergraduate course in computer architecture and implementation.

Quantum mechanics, the subfield of physics that describes the behavior of very small (quantum) particles, provides the basis for a new paradigm of computing. First proposed in the 1980s as a way to improve computational modeling of quantum systems, the field of quantum computing has recently garnered significant attention due to progress in building small-scale devices. However, significant technical advances will be required before a large-scale, practical quantum computer can be achieved. Quantum Computing: Progress and Prospects provides an introduction to the field, including the unique characteristics and constraints of the technology, and assesses the feasibility and implications of creating a functional quantum computer capable of addressing real-world problems. This report considers hardware and software requirements, quantum algorithms, drivers of advances in quantum computing and quantum devices, benchmarks associated with relevant use cases, the time and resources required, and how to assess the probability of success.

The human brain, the ultimate intelligent processor, can handle ambiguous and uncertain information adequately. The implementation of such a human-brain architecture and function is called OC brainwareOCO. Brainware is a candidate for the new tool that will realize a human-friendly computer society. As one of the LSI implementations of brainware, a OC bio-inspiredOCO hardware system is discussed in this book. Consisting of eight enriched versions of papers selected from IIZUKA ''98, this volume provides wide coverage, from neuronal function devices to vision systems, chaotic systems, and also an effective design methodology of hierarchical large-scale neural systems inspired by neuroscience. It can serve as a reference for graduate students and researchers working in the field of brainware. It is also a source of inspiration for research towards the realization of a silicon brain. Contents: Neuron MOS Transistor: The Concept and Its Application (T Shibata); Adaptive Learning Neuron Integrated Circuits Using Ferroelectric-Gate FETs (S-M Yoon et al.); An AnalogOCoDigital Merged Circuit Architecture Using PWM Techniques for Bio-Inspired Nonlinear Dynamical Systems (T Morie et al.); Application-Driven Design of Bio-Inspired Low-Power Vision Circuits and Systems (A KAnig et al.); Motion Detection with Bio-Inspired Analog MOS Circuits (H Yonezu et al.); cents MOS Cellular-Automaton Circuit for Picture Processing (M Ikebe & Y Amemiya); Semiconductor Chaos-Generating Elements of Simple Structure and Their Integration (K Hoh et al.); Computation in Single Neuron with Dendritic Trees (N Katayama et al.). Readership: Graduate students, researchers and industrialists in artificial intelligence, neural networks, machine perception, computer vision, pattern/handwriting recognition, image analysis and biocomputing."

A new version of the classic and widely used text adapted for the JavaScript programming language. Since the publication of its first edition in 1984 and its second edition in 1996, Structure and Interpretation of Computer Programs (SICP) has influenced computer science curricula around the world. Widely adopted as a textbook, the book has its origins in a popular entry-level computer science course taught by Harold Abelson and Gerald Jay Sussman at MIT. SICP introduces the reader to central ideas of computation by establishing a series of mental models for computation. Earlier editions used the programming language Scheme in their program examples. This new version of the second edition has been adapted for JavaScript. The first three chapters of SICP cover programming concepts that are common to all modern high-level programming languages. Chapters four and five, which used Scheme to formulate language processors for Scheme, required significant revision. Chapter four offers new material, in particular an introduction to the notion of program parsing. The evaluator and compiler in chapter five introduce a subtle stack discipline to support return statements (a prominent feature of statement-oriented languages) without sacrificing tail recursion. The JavaScript programs included in the book run in any implementation of the language that complies with the ECMAScript 2020 specification, using the JavaScript package sicp provided by the MIT Press website.