We introduce the concept of “coded computing”, a novel computing paradigm that utilizes coding theory to effectively inject and leverage data/computation redundancy to mitigate several fundamental bottlenecks in large-scale distributed computing, namely communication bandwidth, straggler’s (i.e., slow or failing nodes) delay, privacy and security bottlenecks.
An introduction to fundamental theories of concurrent computation and associated programming languages for developing distributed and mobile computing systems. Starting from the premise that understanding the foundations of concurrent programming is key to developing distributed computing systems, this book first presents the fundamental theories of concurrent computing and then introduces the programming languages that help develop distributed computing systems at a high level of abstraction. The major theories of concurrent computation—including the π-calculus, the actor model, the join calculus, and mobile ambients—are explained with a focus on how they help design and reason about distributed and mobile computing systems. The book then presents programming languages that follow the theoretical models already described, including Pict, SALSA, and JoCaml. The parallel structure of the chapters in both part one (theory) and part two (practice) enable the reader not only to compare the different theories but also to see clearly how a programming language supports a theoretical model. The book is unique in bridging the gap between the theory and the practice of programming distributed computing systems. It can be used as a textbook for graduate and advanced undergraduate students in computer science or as a reference for researchers in the area of programming technology for distributed computing. By presenting theory first, the book allows readers to focus on the essential components of concurrency, distribution, and mobility without getting bogged down in syntactic details of specific programming languages. Once the theory is understood, the practical part of implementing a system in an actual programming language becomes much easier.
The classic guide to how computers work, updated with new chapters and interactive graphics "For me, Code was a revelation. It was the first book about programming that spoke to me. It started with a story, and it built up, layer by layer, analogy by analogy, until I understood not just the Code, but the System. Code is a book that is as much about Systems Thinking and abstractions as it is about code and programming. Code teaches us how many unseen layers there are between the computer systems that we as users look at every day and the magical silicon rocks that we infused with lightning and taught to think." - Scott Hanselman, Partner Program Director, Microsoft, and host of Hanselminutes Computers are everywhere, most obviously in our laptops and smartphones, but also our cars, televisions, microwave ovens, alarm clocks, robot vacuum cleaners, and other smart appliances. Have you ever wondered what goes on inside these devices to make our lives easier but occasionally more infuriating? For more than 20 years, readers have delighted in Charles Petzold's illuminating story of the secret inner life of computers, and now he has revised it for this new age of computing. Cleverly illustrated and easy to understand, this is the book that cracks the mystery. You'll discover what flashlights, black cats, seesaws, and the ride of Paul Revere can teach you about computing, and how human ingenuity and our compulsion to communicate have shaped every electronic device we use. This new expanded edition explores more deeply the bit-by-bit and gate-by-gate construction of the heart of every smart device, the central processing unit that combines the simplest of basic operations to perform the most complex of feats. Petzold's companion website, CodeHiddenLanguage.com, uses animated graphics of key circuits in the book to make computers even easier to comprehend. In addition to substantially revised and updated content, new chapters include: Chapter 18: Let's Build a Clock! Chapter 21: The Arithmetic Logic Unit Chapter 22: Registers and Busses Chapter 23: CPU Control Signals Chapter 24: Jumps, Loops, and Calls Chapter 28: The World Brain From the simple ticking of clocks to the worldwide hum of the internet, Code reveals the essence of the digital revolution.
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
The computing profession faces a serious gender crisis. Today, fewer women enter computing than anytime in the past 25 years. This book provides an unprecedented look at the history of women and men in computing, detailing how the computing profession emerged and matured, and how the field became male coded. Women's experiences working in offices, education, libraries, programming, and government are examined for clues on how and where women succeeded—and where they struggled. It also provides a unique international dimension with studies examining the U.S., Great Britain, Germany, Norway, and Greece. Scholars in history, gender/women's studies, and science and technology studies, as well as department chairs and hiring directors will find this volume illuminating.
Good software design is simple and easy to understand. Unfortunately, the average computer program today is so complex that no one could possibly comprehend how all the code works. This concise guide helps you understand the fundamentals of good design through scientific laws—principles you can apply to any programming language or project from here to eternity. Whether you’re a junior programmer, senior software engineer, or non-technical manager, you’ll learn how to create a sound plan for your software project, and make better decisions about the pattern and structure of your system. Discover why good software design has become the missing science Understand the ultimate purpose of software and the goals of good design Determine the value of your design now and in the future Examine real-world examples that demonstrate how a system changes over time Create designs that allow for the most change in the environment with the least change in the software Make easier changes in the future by keeping your code simpler now Gain better knowledge of your software’s behavior with more accurate tests
Analyzes cognitive, social and technical issues of end user programming. Drawing on empirical research on existing end user systems, this text examines the importance of task-specific programming languages, visual application frameworks and collaborative work practices for end user computing.
This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system.
Quantum computers are poised to kick-start a new computing revolution—and you can join in right away. If you’re in software engineering, computer graphics, data science, or just an intrigued computerphile, this book provides a hands-on programmer’s guide to understanding quantum computing. Rather than labor through math and theory, you’ll work directly with examples that demonstrate this technology’s unique capabilities. Quantum computing specialists Eric Johnston, Nic Harrigan, and Mercedes Gimeno-Segovia show you how to build the skills, tools, and intuition required to write quantum programs at the center of applications. You’ll understand what quantum computers can do and learn how to identify the types of problems they can solve. This book includes three multichapter sections: Programming for a QPU—Explore core concepts for programming quantum processing units, including how to describe and manipulate qubits and how to perform quantum teleportation. QPU Primitives—Learn algorithmic primitives and techniques, including amplitude amplification, the Quantum Fourier Transform, and phase estimation. QPU Applications—Investigate how QPU primitives are used to build existing applications, including quantum search techniques and Shor’s factoring algorithm.
Books on computation in the marketplace tend to discuss the topics within specific fields. Many computational algorithms, however, share common roots. Great advantages emerge if numerical methodologies break the boundaries and find their uses across disciplines. Interdisciplinary Computing In Java Programming Language introduces readers of different backgrounds to the beauty of the selected algorithms. Serious quantitative researchers, writing customized codes for computation, enjoy cracking source codes as opposed to the black-box approach. Most C and Fortran programs, despite being slightly faster in program execution, lack built-in support for plotting and graphical user interface. This book selects Java as the platform where source codes are developed and applications are run, helping readers/users best appreciate the fun of computation. Interdisciplinary Computing In Java Programming Language is designed to meet the needs of a professional audience composed of practitioners and researchers in science and technology. This book is also suitable for senior undergraduate and graduate-level students in computer science, as a secondary text.