MMIX is a RISC computer designed by Don Knuth to illustrate machine-level aspects of programming. In the author's book series "The Art of Computer Programming", MMIX replaces the 1960s-style machine MIX. A particular goal in the design of MMIX was to keep its machine language simple, elegant, and easy to learn. At the same time, all of the complexities needed to achieve high performance in practice are taken into account. This book constitutes a collection of programs written in CWEB that make MMIX a virtual reality. Among other utilities, an assembler converting MMIX symbolic files to MMIX objects and two simulators executing the programs in given object files are provided. The latest version of all programs can be downloaded from MMIX's home page. The book provides a complete documentation of the MMIX computer and its assembly language. It also presents mini-indexes, which make the programs much easier to understand. A corrected reprint of the book has been published in August 2014, replacing the version of 1999.

The MMIX Supplement: Supplement to The Art of Computer ProgrammingVolumes 1, 2, 3 by Donald E. Knuth “I encourage serious programmers everywhere to sharpen their skills by devouring this book.” –Donald E. Knuth In the first edition of Volume 1 of The Art of Computer Programming, Donald E. Knuth introduced the MIX computer and its machine language: a teaching tool that powerfully illuminated the inner workings of the algorithms he documents. Later, with the publication of his Fascicle 1, Knuth introduced MMIX: a modern, 64-bit RISC replacement to the now-obsolete MIX. Now, with Knuth’s guidance and approval, Martin Ruckert has rewritten all MIX example programs from Knuth’s Volumes 1-3 for MMIX, thus completing this MMIX update to the original classic. Building on contributions from the international MMIXmasters volunteer group, Ruckert fully addresses MMIX basic concepts, information structures, random numbers, arithmetic, sorting, and searching. In the preparation of this supplement, about 15,000 lines of MMIX code were written and checked for correctness; over a thousand test cases were written and executed to ensure the code is of the highest possible quality. The MMIX Supplement should be read side by side with The Art of Computer Programming, Volumes 1-3, and Knuth’s Fascicle 1, which introduces the MMIX computer, its design, and its machine language. Throughout, this supplement contains convenient page references to corresponding coverage in the original volumes. To further simplify the transition to MMIX, Ruckert stayed as close as possible to the original–preserving programming style, analysis techniques, and even wording, while highlighting differences where appropriate. The resulting text will serve as a bridge to the future, helping readers apply Knuth’s insights in modern environments, until his revised, “ultimate” edition of The Art of Computer Programming is available. From Donald E. Knuth’s Foreword: “I am thrilled to see the present book by Martin Ruckert: It is jam-packed with goodies from which an extraordinary amount can be learned. Martin has not merely transcribed my early programs for MIX and recast them in a modern idiom. He has penetrated to their essence and rendered them anew with elegance and good taste. His carefully checked code represents a significant contribution to the art of pedagogy as well as to the art of programming.” Dr. Martin Ruckert maintains the MMIX home page at mmix.cs.hm.edu. He is professor of mathematics and computer science at Munich University of Applied Sciences in Munich, Germany.

Check out the boxed set that brings together Volumes 1 - 4B in one elegant case. The Art of Computer Programming, Volumes 1-4B Boxed Set ISBN: 9780137935109 Art of Computer Programming, Volume 1, Fascicle 1, The: MMIX -- A RISC Computer for the New Millennium This multivolume work on the analysis of algorithms has long been recognized as the definitive description of classical computer science. The three complete volumes published to date already comprise a unique and invaluable resource in programming theory and practice. Countless readers have spoken about the profound personal influence of Knuth's writings. Scientists have marveled at the beauty and elegance of his analysis, while practicing programmers have successfully applied his "cookbook" solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books. To begin the fourth and later volumes of the set, and to update parts of the existing three, Knuth has created a series of small books called fascicles, which will be published t regular intervals. Each fascicle will encompass a section or more of wholly new or evised material. Ultimately, the content of these fascicles will be rolled up into the comprehensive, final versions of each volume, and the enormous undertaking that began in 1962 will be complete. Volume 1, Fascicle 1 This first fascicle updates The Art of Computer Programming, Volume 1, Third Edition: Fundamental Algorithms, and ultimately will become part of the fourth edition of that book. Specifically, it provides a programmer's introduction to the long-awaited MMIX, a RISC-based computer that replaces the original MIX, and describes the MMIX assembly language. The fascicle also presents new material on subroutines, coroutines, and interpretive routines. Ebook (PDF version) produced by Mathematical Sciences Publishers (MSP),http://msp.org

Author's pref. : "a series of updates that I plan to make available at regular intervals as I continue working toward the ultimate editions of The art of computer programming", i.e. supplements to the 3rd ed. in anticipation of the 4th ed.

Describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.

Friendly advice on leveraging the power of the new Nexus 7 Google tablet! The arrival of the new Nexus 7 Google tablet is eagerly awaited, thanks to its cutting-edge software, top-notch hardware, unprecedented abilities, and nine-hour battery life. This easy-to-understand, engaging guide covers everything you need to know about this amazing Android tablet. Bestselling Dummies author Dan Gookin uses his friendly writing style to deliver clear instructions for setting up, navigating, and using the device. You'll learn to use all your favorite Google applications that come loaded on the device, personalize it, and much more. Walks you through the touchscreen, wireless access, and software updates Demonstrates how to download, shop for, and fill your Nexus 7 with movies, e-books, games, and music Helps you keep on top of your schedule and appointments and pursue your interests and hobbies with the latest apps and websites Offers guidance on using your device to navigate from here to there and stay connected with friends and family while you're away Nexus 7 For Dummies is an essential companion to your other new companion: the Nexus 7!

Literate programming is a programming methodology that combines a programming language with a documentation language, making programs more easily maintained than programs written only in a high-level language. A literate programmer is an essayist who writes programs for humans to understand. When programs are written in the recommended style they can be transformed into documents by a document compiler and into efficient code by an algebraic compiler. This anthology of essays includes Knuth's early papers on related topics such as structured programming as well as the Computer Journal article that launched literate programming. Many examples are given, including excerpts from the programs for TeX and METAFONT. The final essay is an example of CWEB, a system for literate programming in C and related languages. Index included.

Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you'll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You'll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You'll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author's extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer.

Exploring the design and implementation of assemblers and loaders, this volume describes such important concepts as absolute and relocatable object files, assembler features, the listing file, the properties of assemblers and loaders, and three special assembler types.