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          CUDA by Example

          聯(lián)合創(chuàng)作 · 2023-10-06 21:03

          "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...

          "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

          Jason Sanders是NVIDIA公司CUDA平臺小組的高級軟件工程師。他在NVIDIA的工作包括幫助開發(fā)早期的CUDA系統(tǒng)軟件,并參與OpenCL 1.0規(guī)范的制定,該規(guī)范是一個用于異構計算的行業(yè)標準。Jason在加州大學伯克利分校獲得計算機科學碩士學位,他發(fā)表了關于GPU計算的研究論文。此外,他還獲得了普林斯頓大學電子工程專業(yè)學士學位。在加入NVIDIA公司之前,他曾在ATI技術公司、Apple公司以及Novell公司工作過。

          Edward Kandrot是NVIDIA公司CUDA算法小組的高級軟件工程師。他在代碼優(yōu)化和提升性能等方面擁有20余年的工作經(jīng)驗,參與過Photoshop和Mozilla等項目。Kandrot曾經(jīng)在Adobe公司、Microsoft公司工作過,他還是許多公司的咨詢師,包括Apple公司和Autodesk公司。

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