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This book presents novel approaches to the formal specification of concurrent and parallel systems, mathematical models for describing such systems, and programming and verification concepts for their implementation. A special emphasis is on methods based on artificial intelligence and machine learning techniques. Chapters are revised selected papers from the 29th International Workshop on Concurrency, Specification, and Programming (CS&P 2021), Berlin, Germany. Nine independent chapters cover formal approaches to topics such as requirements formalization, parsing, or granular computing, as well as their applications in recommender systems, decision making, security, optimization, and other areas. The book thus addresses both researchers and practitioners in its field.
This book is devoted to the most difficult part of concurrent programming, namely synchronization concepts, techniques and principles when the cooperating entities are asynchronous, communicate through a shared memory, and may experience failures. Synchronization is no longer a set of tricks but, due to research results in recent decades, it relies today on sane scientific foundations as explained in this book. In this book the author explains synchronization and the implementation of concurrent objects, presenting in a uniform and comprehensive way the major theoretical and practical results of the past 30 years. Among the key features of the book are a new look at lock-based synchronization (mutual exclusion, semaphores, monitors, path expressions); an introduction to the atomicity consistency criterion and its properties and a specific chapter on transactional memory; an introduction to mutex-freedom and associated progress conditions such as obstruction-freedom and wait-freedom; a presentation of Lamport's hierarchy of safe, regular and atomic registers and associated wait-free constructions; a description of numerous wait-free constructions of concurrent objects (queues, stacks, weak counters, snapshot objects, renaming objects, etc.); a presentation of the computability power of concurrent objects including the notions of universal construction, consensus number and the associated Herlihy's hierarchy; and a survey of failure detector-based constructions of consensus objects. The book is suitable for advanced undergraduate students and graduate students in computer science or computer engineering, graduate students in mathematics interested in the foundations of process synchronization, and practitioners and engineers who need to produce correct concurrent software. The reader should have a basic knowledge of algorithms and operating systems.
Mathematics of Computing -- Parallelism.
“When you begin using multi-threading throughout an application, the importance of clean architecture and design is critical. . . . This places an emphasis on understanding not only the platform’s capabilities but also emerging best practices. Joe does a great job interspersing best practices alongside theory throughout his book.” – From the Foreword by Craig Mundie, Chief Research and Strategy Officer, Microsoft Corporation Author Joe Duffy has risen to the challenge of explaining how to write software that takes full advantage of concurrency and hardware parallelism. In Concurrent Programming on Windows, he explains how to design, implement, and maintain large-scale concurrent programs, primarily using C# and C++ for Windows. Duffy aims to give application, system, and library developers the tools and techniques needed to write efficient, safe code for multicore processors. This is important not only for the kinds of problems where concurrency is inherent and easily exploitable—such as server applications, compute-intensive image manipulation, financial analysis, simulations, and AI algorithms—but also for problems that can be speeded up using parallelism but require more effort—such as math libraries, sort routines, report generation, XML manipulation, and stream processing algorithms. Concurrent Programming on Windows has four major sections: The first introduces concurrency at a high level, followed by a section that focuses on the fundamental platform features, inner workings, and API details. Next, there is a section that describes common patterns, best practices, algorithms, and data structures that emerge while writing concurrent software. The final section covers many of the common system-wide architectural and process concerns of concurrent programming. This is the only book you’ll need in order to learn the best practices and common patterns for programming with concurrency on Windows and .NET.
SR (Synchronizing Resources) is a powerful and flexible language for concurrent programming. With its explicit mechanisms and concurrency, communication, and synchronization, programmers can easily learn to write programs for both shared- and distributed-memory applications and machines.This book, written by the language designers, provides a complete introduction to SR and gives the reader the tools for learning about and experimenting with concurrency. Features Provides an accessible, clear introduction to SR by the language designers. Teaches practical techniques through numerous realistic examples of parallel and distributed programming problems. Examines 'classic' concurrent programming problems as well as many important parallel and distributed programming problems. Illustrates trade-offs between language mechanisms to help the reader understand and make optimum design decisions Reinforces key points with numerous end-of-chapter exercises Includes six appendices that summarize the language for quick reference, show how to develop and execute programs, and describe the implementation. The SR language implementation is available, free, from the SR Project, University of Arizona, at ftp://cs.arizona.edu/sr/. 0805300880B04062001