Heterogeneous Computing with OpenCL Buy on Amazon
Facebook LinkedIn

Heterogeneous Computing with OpenCL

Publisher Morgan Kaufmann
Category Computers
3.96 69.95 -94% USD

In Stock.

Book Details
Author(s) Gaster, Benedict
Publisher Morgan Kaufmann
ISBN / ASIN 0123877660
ISBN-13 9780123877666
Availability In Stock.
Sales Rank #687,580
Category Computers
Marketplace United States 🇺🇸
Description

Heterogeneous Computing with OpenCL teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future.

Written by leaders in the parallel computing and OpenCL communities, this book will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. The authors explore memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. Intended to support a parallel programming course, Heterogeneous Computing with OpenCL includes detailed examples throughout, plus additional online exercises and other supporting materials.

  • Explains principles and strategies to learn parallel programming with OpenCL, from understanding the four abstraction models to thoroughly testing and debugging complete applications.
  • Covers image processing, web plugins, particle simulations, video editing, performance optimization, and more.
  • Shows how OpenCL maps to an example target architecture and explains some of the tradeoffs associated with mapping to various architectures
  • Addresses a range of fundamental programming techniques, with multiple examples and case studies that demonstrate OpenCL extensions for a variety of hardware platforms
Donate to EbookNetworking
Previous Book Computability Theory: An In... Next Book Data Mining: Practical Mach...
Previous Computability The...
Next Data Mining: Prac...