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Book synopsis

Heterogeneous Computing with OpenCL 2.0 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. This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: * Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources * Dynamic parallelism which reduces processor load and avoids bottlenecks * Improved imaging support and integration with OpenGL, a graphics standard * Pipe memory which can be optimized for specific scenarios * Improved integration with Android platforms 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. * Updated throughout to cover the latest developments in OpenCL 2.0 , including improvements in memory handling, parallelism, and imaging support * 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* Presents multiple examples and case studies that demonstrate range of fundamental programming techniques on current system architectures using OpenCL as the target language alongside CPUs, GPUs and APUs

Book details

Book category Books in English Computing & information technology Computer hardware Grid & parallel computing

• Full title: Heterogeneous Computing with OpenCL 2.0
• Author: David Kaeli, Perhaad Mistry, Dana Schaa, Dong Ping Zhang
• Language: English
• Binding: Paperback
• Number of pages: 336
• EAN: 9780128014141
• ISBN: 0128014148
• ID: 05159835
• Publisher: Elsevier Science & Technology
• Weight: 684 g
• Dimensions: 188 × 232 × 19 mm
• Date of publishing: 18. May 2015

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