利用CodeXL调试OpenCL:从图像处理到并发模型详解

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"《使用CodeXL调试OpenCL内核 - 数字图像处理》是一本专注于讲解异构计算及其在OpenCL中的应用的教程。该书深入介绍了异构计算的基本概念,如并行思想、并发和并行编程模型,以及线程和共享内存的概念,同时探讨了不同层次的消息通讯机制和并行性粒度。OpenCL作为一种跨平台的并行计算框架,被用于实现异构计算环境下的高性能计算,包括硬件的权衡和架构设计空间的讨论。 在第3章,作者详细解释了OpenCL的各个方面,包括其简介、平台和执行模型,内核编程模型,以及内存模型。例如,通过OpenCL C++ Wrapper中的向量加法示例,让CUDA程序员理解如何迁移到OpenCL。章节中还提醒了CUDA程序员需要注意的关键点。 第4章和第5章深入到OpenCL的实际应用,涵盖了诸如直方图计算、图像旋转、卷积、生产者-消费者模型等典型案例,以及命令和排队模型、工作项、工作组和NDRange等概念。这些内容展示了OpenCL在数字图像处理中的强大功能。 第6和7章专门讨论内存管理,分别从主机端和设备端的角度,涵盖了内存对象、内存管理策略、共享虚拟内存、全局内存、常量内存、局部内存和私有内存等关键概念。这些对于理解和优化OpenCL程序性能至关重要。 最后,第8章聚焦于在异构系统中的OpenCL操作解析,探讨了如何有效地在不同的硬件平台上管理和协调计算任务。整体而言,这本书为读者提供了全面的OpenCL调试指南,特别是针对数字图像处理任务的实践技巧和注意事项。"
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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