Parallel Programming with OpenACC

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 PhiTM 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

Produk Detail:

  • Author : Rob Farber
  • Publisher : Newnes
  • Pages : 326 pages
  • ISBN : 0124104592
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKParallel Programming with OpenACC

Parallel Programming with OpenACC

Parallel Programming with OpenACC
  • Author : Rob Farber
  • Publisher : Newnes
  • Release : 14 October 2016
GET THIS BOOKParallel Programming with OpenACC

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

Programming Massively Parallel Processors

Programming Massively Parallel Processors
  • Author : David B. Kirk,Wen-mei W. Hwu
  • Publisher : Morgan Kaufmann
  • Release : 24 November 2016
GET THIS BOOKProgramming Massively Parallel Processors

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries,

Euro-Par 2012 Parallel Processing

Euro-Par 2012 Parallel Processing
  • Author : Christos Kaklamanis,Theodore Papatheodorou,Paul G. Spirakis
  • Publisher : Springer
  • Release : 23 August 2012
GET THIS BOOKEuro-Par 2012 Parallel Processing

This book constitutes the thoroughly refereed proceedings of the 18th International Conference, Euro-Par 2012, held in Rhodes Islands, Greece, in August 2012. The 75 revised full papers presented were carefully reviewed and selected from 228 submissions. The papers are organized in topical sections on support tools and environments; performance prediction and evaluation; scheduling and load balancing; high-performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; peer to peer computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical

OpenCL Programming by Example

OpenCL Programming by Example
  • Author : Ravishekhar Banger,Koushik Bhattacharyya
  • Publisher : Packt Publishing Ltd
  • Release : 23 December 2013
GET THIS BOOKOpenCL Programming by Example

This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming. If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not

Parallel Programming

Parallel Programming
  • Author : Bertil Schmidt,Jorge Gonzalez-Dominguez,Christian Hundt,Moritz Schlarb
  • Publisher : Morgan Kaufmann
  • Release : 20 November 2017
GET THIS BOOKParallel Programming

Parallel Programming: Concepts and Practice provides an upper level introduction to parallel programming. In addition to covering general parallelism concepts, this text teaches practical programming skills for both shared memory and distributed memory architectures. The authors’ open-source system for automated code evaluation provides easy access to parallel computing resources, making the book particularly suitable for classroom settings. Covers parallel programming approaches for single computer nodes and HPC clusters: OpenMP, multithreading, SIMD vectorization, MPI, UPC++ Contains numerous practical parallel programming exercises

Hands-On GPU Programming with Python and CUDA

Hands-On GPU Programming with Python and CUDA
  • Author : Dr. Brian Tuomanen
  • Publisher : Packt Publishing Ltd
  • Release : 27 November 2018
GET THIS BOOKHands-On GPU Programming with Python and CUDA

Build real-world applications by writing effective GPU code, CUDA kernels, and device functions with the latest features of Python 3.7, CUDA 9 and CUDA 10 Key Features Expand your background in GPU programming—PyCUDA, scikit-cuda, and Nsight Effectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolver Apply GPU programming to modern data science applications Book Description Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler

CUDA Programming

CUDA Programming
  • Author : Shane Cook
  • Publisher : Newnes
  • Release : 16 June 2021
GET THIS BOOKCUDA Programming

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

Multicore and GPU Programming

Multicore and GPU Programming
  • Author : Gerassimos Barlas
  • Publisher : Elsevier
  • Release : 16 December 2014
GET THIS BOOKMulticore and GPU Programming

Multicore and GPU Programming offers broad coverage of the key parallel computing skillsets: multicore CPU programming and manycore "massively parallel" computing. Using threads, OpenMP, MPI, and CUDA, it teaches the design and development of software capable of taking advantage of today’s computing platforms incorporating CPU and GPU hardware and explains how to transition from sequential programming to a parallel computing paradigm. Presenting material refined over more than a decade of teaching parallel computing, author Gerassimos Barlas minimizes the challenge

Programming Massively Parallel Processors

Programming Massively Parallel Processors
  • Author : David B. Kirk,Wen-mei W. Hwu
  • Publisher : Newnes
  • Release : 31 December 2012
GET THIS BOOKProgramming Massively Parallel Processors

Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered

OpenCL Parallel Programming Development Cookbook

OpenCL Parallel Programming Development Cookbook
  • Author : Raymond Tay
  • Publisher : Packt Publishing Ltd
  • Release : 01 January 2013
GET THIS BOOKOpenCL Parallel Programming Development Cookbook

OpenCL Parallel Programming Development Cookbook will provide a set of advanced recipes that can be utilized to optimize existing code. This book is therefore ideal for experienced developers with a working knowledge of C/C++ and OpenCL.This book is intended for software developers who have often wondered what to do with that newly bought CPU or GPU they bought other than using it for playing computer games; this book is also for developers who have a working knowledge of

Professional CUDA C Programming

Professional CUDA C Programming
  • Author : John Cheng,Max Grossman,Ty McKercher
  • Publisher : John Wiley & Sons
  • Release : 08 September 2014
GET THIS BOOKProfessional CUDA C Programming

Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers

Parallel Programming for Modern High Performance Computing Systems

Parallel Programming for Modern High Performance Computing Systems
  • Author : Pawel Czarnul
  • Publisher : CRC Press
  • Release : 05 March 2018
GET THIS BOOKParallel Programming for Modern High Performance Computing Systems

In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such

CUDA Application Design and Development

CUDA Application Design and Development
  • Author : Rob Farber
  • Publisher : Elsevier
  • Release : 16 June 2021
GET THIS BOOKCUDA Application Design and Development

Machine generated contents note: 1. How to think in CUDA 2. Tools to build, debug and profile 3. The GPU performance envelope 4. The CUDA memory subsystems 5. Exploiting the CUDA execution grid 6. MultiGPU applications and scaling 7. Numerical CUDA, libraries and high-level language bindings 8. Mixing CUDA with rendering 9. High Performance Machine Learning 10. Scientific Visualization 11. Multimedia with OpenCV 12. Ultra Low-power Devices: Tegra.

CUDA for Engineers

CUDA for Engineers
  • Author : Duane Storti,Mete Yurtoglu
  • Publisher : Addison-Wesley Professional
  • Release : 02 November 2015
GET THIS BOOKCUDA for Engineers

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you’ll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects

Using MPI

Using MPI
  • Author : William Gropp,William D.. Gropp,Ewing Lusk,Anthony Skjellum,Argonne Distinguished Fellow Emeritus Ewing Lusk
  • Publisher : MIT Press
  • Release : 16 June 1999
GET THIS BOOKUsing MPI

The authors introduce the core function of the Message Printing Interface (MPI). This edition adds material on the C++ and Fortran 90 binding for MPI.