"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 fo...(展开全部)

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...(展开全部)

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 an...(展开全部)

《OpenCL异构计算》讲解了OpenCL和如何为复杂的异构系统（多核处理器、GPU和APU）进行并行编程。OpenCL是为支持多平台设计的，受行业广泛支持，有助于帮助读者为异构环境编写高性能应用程序。 本书由并行计算和OpenCL社区中的领头人所撰写，可帮助读者体验OpenCL从而了解大量基础的并行算法。书中探索了内存空间、优化技术、图形的互操作、性能扩展，调试和性能剖析等。 本书读者对象为软件工程师、程序员、硬件工程师、高年级本科生/研究生，可供并行编程课程使用，包含有详细的案例，附有额外的网上练习和其他支持材料。 本书特色 · 解释OpenCL并行编程的原理和策略，从理解四大抽象模型开始，一直介绍到测试和调试完整的应用 · 覆盖图像处理、Web插件、粒子模拟、视频编辑和性能优化等主题 · 展示OpenCL如何映射到目标体系结构，并解释一些映射到...(展开全部)

This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming.If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not necessary.

《OpenCL异构计算》讲解了OpenCL和如何为复杂的异构系统（多核处理器、GPU和APU）进行并行编程。OpenCL是为支持多平台设计的，受行业广泛支持，有助于帮助读者为异构环境编写高性能应用程序。 本书由并行计算和OpenCL社区中的领头人所撰写，可帮助读者体验OpenCL从而了解大量基础的并行算法。书中探索了内存空间、优化技术、图形的互操作、性能扩展，调试和性能剖析等。 本书读者对象为软件工程师、程序员、硬件工程师、高年级本科生/研究生，可供并行编程课程使用，包含有详细的案例，附有额外的网上练习和其他支持材料。 本书特色 · 解释OpenCL并行编程的原理和策略，从理解四大抽象模型开始，一直介绍到测试和调试完整的应用 · 覆盖图像处理、Web插件、粒子模拟、视频编辑和性能优化等主题 · 展示OpenCL如何映射到目标体系结构，并解释一些映射到...(展开全部)

This book differs from traditional numerical analysis texts in that it focuses on the motivation and ideas behind the algorithms presented rather than on detailed analyses of them. It presents a broad overview of methods and software for solving mathematical problems arising in computational modeling and data analysis, including proper problem formulation, selection of effectiv...(展开全部)

《GPGPU编程技术:从GLSL、CUDA到OpenCL》详细介绍了能够反映GPGPU技术现状的三种编程框架及其编程方法：基于OpenGL／GLSL的经典GPGPU技术、NVIDIA的CUDA架构以及跨平台的解决方案OpenGL。《GPGPU编程技术:从GLSL、CUDA到OpenCL》内容涵盖了从软件的安装和编译、编程语言的语法和使用技巧、程序优化，到高级开发中可能遇到的各种情况及应对方案等主题，并为深入学习和研究指引了参考资料，是一本实用的技术指导书。GPGPU技术是快速发展的新兴编程技术，《GPGPU编程技术:从GLSL、CUDA到OpenCL》在编写过程中结合了至2011年国外最新的技术现状。

This book is for Python developers who have developed Python programs for data processing and now want to learn how to write fast, efficient programs that perform CPU-intensive data processing tasks.