“This book is required reading for anyone working with accelerator-based computing systems.” –From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C.   CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance.   Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA.http://developer.nvidia.com/object/cuda-by-example.html

这本书是任何从事基于加速器的计算系统的人的必读书目。" -摘自田纳西大学和橡树岭国家实验室Jack Dongarra的前言 CUDA是一个旨在促进并行程序开发的计算架构。与综合软件平台相结合，CUDA架构使程序员在构建高性能应用程序时能够利用图形处理单元（GPU）的巨大能量。当然，GPU早已可用于要求苛刻的图形和游戏应用。现在，CUDA为从事其他领域应用的程序员带来了这一宝贵资源，包括科学、工程和金融领域。本书由CUDA软件平台团队的两位高级成员编写，向程序员展示了如何使用这项新技术。作者通过工作实例介绍了CUDA开发的各个领域。在简要介绍了CUDA平台和架构，以及CUDA C的快速入门指南之后，本书详细介绍了与每个关键CUDA功能相关的技术和权衡。你会发现什么时候使用每个CUDA C扩展，以及如何编写能提供真正出色性能的CUDA软件。  主要内容包括 并行编程 线程合作 恒定内存和事件 纹理内存 图形互操作性 原子流 在多个GPU上的CUDA C 高级原子学 其他CUDA资源 你需要的所有CUDA软件工具均可从NVIDIA.http://developer.nvidia.com/object/cuda-by-example.html 免费下载。