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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). 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

Designed to work on multiple platforms, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book explores memory spaces, optimization techniques, extensions, debugging and profiling. Multiple case studies and examples illustrate high-performance algorithms, distributing work across heterogeneous systems, embedded domain-specific languages, and will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms.

• Updated content to cover the latest developments in OpenCL 2.0, including improvements in memory handling, parallelism, and imaging support
• Explanations of principles and strategies to learn parallel programming with OpenCL, from understanding the abstraction models to thoroughly testing and debugging complete applications
• Example code covering image analytics, web plugins, particle simulations, video editing, performance optimization, and more

Heterogeneous Computing with OpenCL 2.0

Foreword Ch 1: Introduction Ch 2: Device Architectures Ch 3: Introduction to OpenCL Ch 4: Examples Ch 5: Execution Model Ch 6: host-side memory model Ch 7: device-side memory model Ch 8: Implementation Ch 9: Case study: Image Clustering and Search Ch 10: Profiling and Debugging Ch 11: C++ AMP Ch 12: WebCL Ch 13: Foreign Lands: Plugging OpenCL In