Parallel Programming with OpenACC

Informationen zum Autor Rob Farber has served as a scientist in Europe at the Irish Center for High-End Computing as well as U.S. national labs in Los Alamos, Berkeley, and the Pacific Northwest. He has also been on the external faculty at the Santa Fe Institute, consultant to fortune 100 companies, and co-founder of two computational startups that achieved liquidity events. He is the author of CUDA Application Design and Development? as well as numerous articles and tutorials that have appeared in Dr. Dobb's Journal and Scientific Computing, The Code Project and others. Klappentext Parallel Programming with OpenACC is a modern! practical guide to implementing dependable computing systems. Parallel Programming with OpenACC 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 will help you get the most from the latest NVIDIA and AMD GPU plus multicore CPU architectures (and soon for Intel® Xeon Phi(TM) 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 pitfalls to avoid. Throughout! the book demonstrates using clear! simple! working examples that can be adapted to solve your application needs.

Autorentext
Rob Farber has served as a scientist in Europe at the Irish Center for High-End Computing as well as U.S. national labs in Los Alamos, Berkeley, and the Pacific Northwest. He has also been on the external faculty at the Santa Fe Institute, consultant to fortune 100 companies, and co-founder of two computational startups that achieved liquidity events. He is the author of CUDA Application Design and Development” as well as numerous articles and tutorials that have appeared in Dr. Dobb's Journal and Scientific Computing, The Code Project and others.

Klappentext

Parallel Programming with OpenACC is a modern, practical guide to implementing dependable computing systems. Parallel Programming with OpenACC 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 will help you get the most from the latest NVIDIA and AMD GPU plus multicore CPU architectures (and soon for Intel® Xeon Phi(TM) 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 pitfalls to avoid. Throughout, the book demonstrates using clear, simple, working examples that can be adapted to solve your application needs.

Inhalt

Foreword
Michael Wolfe
1. From Serial to Parallel Programming using OpenACC
Rob Farber
2. Profile-Guided Development with OpenACC
Jeff Larkin

3. Profiling Performance of Hybrid Applications with Score-P and Vampir
   Guido Jukeland
4. Pipelining Data Transfers with OpenACC
   Jeff Larkin
5. Advanced Data Management
   Mat Colgrove
   6. Tuning OpenACC loop execution
   Saber Feki
   7. Multi Device Programming with OpenACC
   Jiri Kraus
   8. Using OpenACC for Stencil and Feldkamp Algorithms
   Sunita Chandrasekaran
   9. Accelerating 3D Wave Equations using OpenACC
   Ty McKercher
   10. The Detailed Development of an OpenACC Application
   Andy Herdman
6. GPU-Accelerated Molecular Dynamics Clustering Analysis with OpenACC
   John Stone
7. Incrementally accelerating the RI-MP2 correlated method of electronic structure theory using OpenACC compiler directives
   Janus J. Eriksen
8. Using OpenACC to port large legacy climate and weather modelling code to GPUs
   Xavier Lapillonne