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

opencl原版英文教程

opencl-2.0 开发文档，介绍了opencl框架，API借口函数的详细说明。内存使用，kernel创建以及使用

openclbook OpenCL教科书《使用OpenCL 2.0进行异构计算》的样本和材料 OpenCL书的示例将在此处上传。 笔记： 这些是初始版本。 我们正在测试它们，随着时间的推移它们将得到改进。 反馈 对于错误和注释，请在github中创建一个问题

AMD高性能计算首席科学家写的一本关于OpenCL的书。 本书将介绍在复杂环境下的OpenCL和并行编程。这里的复杂环境包含多种设备架构，比如：多芯CPU，GPU，以及完全集成的加速处理单元(APU)。