Heterogeneous Computing with OpenCL, Second Edition

Author: Benedict Gaster
Edition: 2
Binding: Paperback
ISBN: 0124058949

Heterogeneous Computing with OpenCL, Second Edition: Revised OpenCL 1.2 Edition

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. Get Heterogeneous Computing with OpenCL, Second Edition computer books for free.
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 programmi Check Heterogeneous Computing with OpenCL, Second Edition our best computer books for 2013. All books are available in pdf format and downloadable from rapidshare, 4shared, and mediafire.

Heterogeneous Computing with OpenCL, Second Edition Free

Intended to support a parallel programmi

Related Computer Books

OpenCL in Action: How to Accelerate Graphics and Computations

SummaryOpenCL in Action is a thorough, hands-on presentation of OpenCL, with an eye toward showing developers how to build high-performance applications of their own. It begins by presenting the core concepts behind OpenCL, including ve

Programming Massively Parallel Processors, Second Edition: A Hands-on Approach

Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in det

OpenCL Programming Guide

Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. processor. Already implemented by Apple, AMD, Intel,

CUDA Programming: A Developer's Guide to Parallel Computing with GPUs (Applications of GPU Computing Series)

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