Angielski
OpenACC Programming: Simplifying Massively Parallel Computing is a modern, practical guide to implementing dependable computing systems. OpenACC Programming: Simplifying Massively Parallel Computing explains how anyone can use OpenACC to improve application performance, without diving into complex GPU coding. Author Rob Farber, continuing the approach from his book CUDA Application Design and Development, demonstrates how to port existing applications to GPUs and gain immediate speedups. The book also will help you get the most from the latest Kepler architecture from NVIDIA, with examples including CUDA 5 applied to 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 pitfalls to avoid. Throughout, the book demonstrates using clear, simple, working examples that can be adapted to solve your application needs. Presents the simplest way to leverage GPUs to achieve application speedupsShows how OpenACC works, including working examples that can be adapted for your own application needsModeled on the approach developed by author Rob Farber in his previous CUDA book and articles published at Dr. Dobb’s JournalAllows readers to download source code and slides from the book's companion web page
