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Parallel Programming with OpenACC is a modern, practical guide to implementing dependable computing systems. The book explains how anyone can use OpenACC to quickly ramp-up application performance using high-level code directives called pragmas. The OpenACC directive-based programming model is designed to provide a simple, yet powerful, approach to accelerators without significant programming effort. Author Rob Farber, working with a team of expert contributors, demonstrates how to turn existing applications into portable GPU accelerated programs that demonstrate immediate speedups. The book also helps users get the most from the latest NVIDIA and AMD GPU plus multicore CPU architectures (and soon for Intel® Xeon Phi™ as well). Downloadable example codes provide hands-on OpenACC experience for common problems in scientific, commercial, big-data, and real-time systems. Topics include writing reusable code, asynchronous capabilities, using libraries, multicore clusters, and much more. Each chapter explains how a specific aspect of OpenACC technology fits, how it works, and the pitfalls to avoid. Throughout, the book demonstrates how the use of simple working examples that can be adapted to solve application needs. Presents the simplest way to leverage GPUs to achieve application speedups Shows how OpenACC works, including working examples that can be adapted for application needs Allows readers to download source code and slides from the book's companion web page

Parallel programming (Computer science)

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Parallel processing (Electronic computers) --- Parallel programming (Computer science)

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Parallel programming (Computer science) --- Computer programming --- Parallel processing (Electronic computers)

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"Recent developments in parallel computing mean that the use of machine learning techniques and intelligence to handle the huge volume of available data have brought the faster solutions offered by advanced technologies to various fields of application. This book presents the proceedings of the Virtual International Conference on Advances in Parallel Computing Technologies and Applications (ICAPTA 2021), hosted in Chennai, India, and held online as a virtual event on 15 and 16 April 2021.The aim of the conference was to provide a forum for sharing knowledge in various aspects of parallel computing in communications systems and networking, including cloud and virtualization solutions, management technologies, and vertical application areas. It also provided a platform for scientists, researchers, practitioners and academicians to present and discuss the most recent innovations and trends, as well as the concerns and practical challenges encountered in this field. Included here are 52 full length papers, accepted from over 100 submissions based on the reviews and comments of subject experts. Topics covered include parallel computing in communication, machine learning intelligence for parallel computing and parallel computing for software services in theoretical and practical aspects. Providing an overview of the latest developments in the field, the book will be of interest to all those whose work involves the use of parallel computing technologies"--

Parallel processing (Electronic computers). --- Parallel programming (Computer science).

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Concurrent Constraint Programming introduces a new and rich class of programming languages based on the notion of computing with partial information, or constraints, that synthesize and extend work on concurrent logic programming and that offer a promising approach for treating thorny issues in the semantics of concurrent, nondeterministic programming languages. Saraswat develops an elegant and semantically tractable framework for computing with constraints, emphasizing their importance for communication and control in concurrent, programming languages. He describes the basic paradigm, illustrates its structure, discusses various augmentations, gives a simple implementation of a concrete language, and specifies its connections with other formalisms. In this framework, concurrently executing agents communicate by placing and checking constraints on shared variables in a common store. The major form of concurrency control in the system is through the operations of Atomic Tell - an agent may instantaneously place constraints only if they are consistent with constraints that have already been placed - and Blocking Ask - an agent must block when it checks a constraint that is not yet known to hold. Other operations at a finer granularity of atomicity are also presented. Saraswat introduces and develops the concurrent constraint family of programming languages based on these ideas, shows how various constraint systems can naturally realize data structures common in computer science, and presents a formal operational semantics for many languages in the concurrent constraint family. In addition, he provides a concrete realization of the paradigm on a sequential machine by presenting a compiler for the concurrent constraint language Herbrand and demonstrates a number of constraint-based concurrent programming techniques that lead to novel presentations of algorithms for many concurrent programming problems. Vijay A. Saraswat is Member of the Research Staff at Xerox Palo Alto Research Center.

Constraint programming (Computer science) --- Parallel programming (Computer science) --- Constraint programming (Computer science). --- Parallel programming (Computer science). --- Computer programming --- Parallel processing (Electronic computers)