Kategoria BISAC: Computers >> Programming - Parallel

This accessible text covers the techniques of parallel programming in a practical manner that enables readers to write and evaluate their parallel programs. Supported by the National Science Foundation and exhaustively class-tested, it is the first text of its kind that does not require access to a special multiprocessor system, concentrating instead on parallel programs that can be executed on networked computers using freely available parallel software tools. The book covers the timely topic of cluster programming, interesting to many programmers due to the recent...

"I hope that readers will learn to use the full expressibility and power of OpenMP. This book should provide an excellent introduction to beginners, and the performance section should help those with some experience who want to push OpenMP to its limits." -- from the foreword by David J. Kuck, Intel Fellow, Software and Solutions Group, and Director, Parallel and Distributed Solutions, Intel Corporation

OpenMP, a portable programming interface for shared memory parallel computers, was adopted as an informal standard in 1997 by computer scientists who wanted a unified model on which...

If you're looking to take full advantage of multi-core processors with concurrent programming, this practical book provides the knowledge and hands-on experience you need. The Art of Concurrency is one of the few resources to focus on implementing algorithms in the shared-memory model of multi-core processors, rather than just theoretical models or distributed-memory architectures. The book provides detailed explanations and usable samples to help you transform algorithms from serial to parallel code, along with advice and analysis for avoiding mistakes that programmers typically...

"This book should find a place on any Propellerhead's bookshelf, between Parallax's Propeller Manual and its Programming and Customizing the Multicore Propeller volumes." Make: 24

Programming the Propeller with Spin: A Beginner's Guide to Parallel Processing walks you through the essential skills you need to build and control devices using the Propeller chip and its parallel processing environment. Find out how to use each of the identical 32-bit processors, known as cogs, and make the eight cogs effectively...

Programming multi-core and many-core computing systems

Sabri Pllana, Linnaeus University, Sweden

Fatos Xhafa, Technical University of Catalonia, Spain

Provides state-of-the-art methods for programming multi-core and many-core systems

The book comprises a selection of twenty two chapters covering: fundamental techniques and algorithms; programming approaches; methodologies and frameworks; scheduling and management; testing and evaluation methodologies; and case studies for programming multi-core and many-core systems.

Program...

It's tough to argue with R as a high-quality, cross-platform, open source statistical software product--unless you're in the business of crunching Big Data. This concise book introduces you to several strategies for using R to analyze large datasets, including three chapters on using R and Hadoop together. You'll learn the basics of Snow, Multicore, Parallel, Segue, RHIPE, and Hadoop Streaming, including how to find them, how to use them, when they work well, and when they don't.

With these packages, you can overcome R's single-threaded nature by spreading work across multiple CPUs,...

If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems.