OpenCL 2.2开发指南:API与命令队列详解

3星 · 超过75%的资源 需积分: 10 7 下载量 35 浏览量 更新于2024-07-19 1 收藏 1.42MB PDF 举报
OpenCL 2.2 Reference Guide 是一份全面的开发指南,旨在帮助用户有效地利用 OpenCL 进行高效且并行计算。这份文档的核心内容围绕着 OpenCL API(Application Programming Interface),它是 OpenCL 运行时的核心组件,负责管理 OpenCL 对象如命令队列、内存对象、程序对象和内核对象,以及执行与这些对象相关的操作。 在 OpenCL API 中,"cl_command_queue" 是一个关键概念,它代表了程序执行命令的线程池,是 OpenCL 程序的基本工作单元。"clCreateCommandQueueWithProperties" 函数是创建命令队列的基石,该函数接受四个参数: 1. `cl_context context`:表示上下文,是程序运行的环境,包含了设备和内存等资源。 2. `cl_device_id device`:指定执行命令的设备,可以是 CPU、GPU 或其他硬件加速器。 3. `const cl_command_queue_properties* properties`:这是一个指向包含队列属性的零终止列表,属性包括但不限于: - `CL_QUEUE_SIZE`:设置命令队列的大小,用于控制并发任务的数量。 - `CL_QUEUE_PROPERTIES`:这是一个位字段,可以设置多个属性,例如支持异步执行模式(OUT_OF_ORDER_EXEC_MODE_ENABLE)、启用性能分析(PROFILING_ENABLE)或在设备上执行默认行为(ON_DEVICE)。 - `CL_QUEUE_THROTTLE_{HIGH,MED,LOW}_KHR`:在 Khronos 钩子扩展下,用于调整设备执行命令的速度,如低优先级(LOW)、中等优先级(MED)或高优先级(HIGH)。 - `CL_QUEUE_PRIORITY_KHR`:优先级标记,允许开发者设置高(CL_QUEUE_PRIORITY_HIGH_KHR)、中(CL_QUEUE_PRIORITY_MED_KHR)或低(CL_QUEUE_PRIORITY_LOW_KHR)的执行顺序,需要 cl_khr_priority_hints 扩展支持。 通过这个函数,开发者可以定制命令队列的行为,以便根据应用需求优化性能和资源使用。创建命令队列后,开发者可以使用其执行 kernel(内核)调用、读取或写入内存对象,从而实现并行计算任务。 总结来说,OpenCL 2.2 Reference Guide 提供了丰富的开发工具,使得用户能够深入了解如何创建、配置和管理命令队列,进而利用 OpenCL 架构进行高性能计算。对于想要在不同硬件平台上实现并行处理的开发者来说,理解和掌握这部分内容至关重要。
2014-05-24 上传
Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. processor. Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. This is the first comprehensive, authoritative, and practical guide to OpenCL 1.1 specifically for working developers and software architects. Written by five leading OpenCL authorities, OpenCL Programming Guide covers the entire specification. It reviews key use cases, shows how OpenCL can express a wide range of parallel algorithms, and offers complete reference material on both the API and OpenCL C programming language. Through complete case studies and downloadable code examples, the authors show how to write complex parallel programs that decompose workloads across many different devices. They also present all the essentials of OpenCL software performance optimization, including probing and adapting to hardware. Coverage includes Understanding OpenCL’s architecture, concepts, terminology, goals, and rationale Programming with OpenCL C and the runtime API Using buffers, sub-buffers, images, samplers, and events Sharing and synchronizing data with OpenGL and Microsoft’s Direct3D Simplifying development with the C++ Wrapper API Using OpenCL Embedded Profiles to support devices ranging from cellphones to supercomputer nodes Case studies dealing with physics simulation; image and signal processing, such as image histograms, edge detection filters, Fast Fourier Transforms, and optical flow; math libraries, such as matrix multiplication and high-performance sparse matrix multiplication; and more Source code for this book is available at https://code.google.com/p/opencl-book-samples/