Concurrent C is a superset of C that provides parallel programming facilities such as those for the declaring and creating processes, for process synchronization and interaction, and for process termination and abortion. Concurrent C was designed for the effective utilization of multiprocessors and multicomputers. Concurrent C, as a compile-time option, also works with C++, an object-oriented superset of C.

"This book should be on every C++ programmer’s desk. It’s clear, concise, and valuable." - Rob Green, Bowling Green State University This bestseller has been updated and revised to cover all the latest changes to C++ 14 and 17! C++ Concurrency in Action, Second Edition teaches you everything you need to write robust and elegant multithreaded applications in C++17. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology You choose C++ when your applications need to run fast. Well-designed concurrency makes them go even faster. C++ 17 delivers strong support for the multithreaded, multiprocessor programming required for fast graphic processing, machine learning, and other performance-sensitive tasks. This exceptional book unpacks the features, patterns, and best practices of production-grade C++ concurrency. About the Book C++ Concurrency in Action, Second Edition is the definitive guide to writing elegant multithreaded applications in C++. Updated for C++ 17, it carefully addresses every aspect of concurrent development, from starting new threads to designing fully functional multithreaded algorithms and data structures. Concurrency master Anthony Williams presents examples and practical tasks in every chapter, including insights that will delight even the most experienced developer. What's inside Full coverage of new C++ 17 features Starting and managing threads Synchronizing concurrent operations Designing concurrent code Debugging multithreaded applications About the Reader Written for intermediate C and C++ developers. No prior experience with concurrency required. About the Author Anthony Williams has been an active member of the BSI C++ Panel since 2001 and is the developer of the just::thread Pro extensions to the C++ 11 thread library. Table of Contents Hello, world of concurrency in C++! Managing threads Sharing data between threads Synchronizing concurrent operations The C++ memory model and operations on atomic types Designing lock-based concurrent data structures Designing lock-free concurrent data structures Designing concurrent code Advanced thread management Parallel algorithms Testing and debugging multithreaded applications

Multicore microprocessors are now at the heart of nearly all desktop and laptop computers. While these chips offer exciting opportunities for the creation of newer and faster applications, they also challenge students and educators. How can the new generation of computer scientists growing up with multicore chips learn to program applications that exploit this latent processing power? This unique book is an attempt to introduce concurrent programming to first-year computer science students, much earlier than most competing products. This book assumes no programming background but offers a broad coverage of Java. It includes over 150 numbered and numerous inline examples as well as more than 300 exercises categorized as "conceptual," "programming," and "experiments." The problem-oriented approach presents a problem, explains supporting concepts, outlines necessary syntax, and finally provides its solution. All programs in the book are available for download and experimentation. A substantial index of at least 5000 entries makes it easy for readers to locate relevant information. In a fast-changing field, this book is continually updated and refined. The 2014 version is the seventh "draft edition" of this volume, and features numerous revisions based on student feedback. A list of errata for this version can be found on the Purdue University Department of Computer Science website.

This practical book includes a tutorial of the entire set of Windows and .NET APIs required to write concurrent programs. Because so much of the threading and synchronization features of the platform are Windows-general, the author, Joe Duffy, focuses first on the general behavior and then on the API details of native and managed code. Interspersed among the tutorial are many difficult-to-discover, useful insights, and internal details about how things work.

Software -- Programming Languages.

Real-time functionality is essential for developing many consumer, industrial, and systems devices. While the C/C++ programming language is most often used in the creation of real-time software, the Java language, with its simple and familiar object-oriented programming model, offers many advantages over current real-time practices. Concurrent and Real-Time Programming in Java covers the motivations for, and semantics of, the extensions and modifications to the Java programming environment that enable the Java platform (Virtual Machine) to meet the requirements and constraints of real-time development. Key aspects of concurrent and real-time programming and how they are implemented in Java are discussed, such as concurrency, memory management, real-time scheduling, and real-time resource sharing.

If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented: Express parallelism in Haskell with the Eval monad and Evaluation Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network