CUDA Handbook: A Comprehensive Guide to GPU Programming, The

CUDA Handbook: A Comprehensive Guide to GPU Programming, The

MIA KARTS BOOKS

CUDA Handbook: A Comprehensive Guide to GPU Programming, The
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    CUDA Handbook: A Comprehensive Guide to GPU Programming, The

    $59.00 CAD
     per 
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    Book Details

    Format
    Paperback
    Language
    English
    Category
    Computer Science
    Condition
    New
    ISBN-13
    9780321809469
    ISBN-10
    0321809467

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    Product description

    ISBN: 0321809467

    Author: Wilt, Nicholas

    Condition: New

    The CUDA Handbook begins where CUDA by Example (Addison-Wesley, 2011) leaves off, discussing CUDA hardware and software in greater detail and covering both CUDA 5.0 and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will see how the hardware processes commands and how the driver checks progress; more experienced CUDA developers will appreciate the expert coverage of topics such as the driver API and context migration, as well as the guidance on how best to structure CPU/GPU data interchange and synchronization.The accompanying open source code-more than 25,000 lines of it, freely available at www.cudahandbook.com-is specifically intended to be reused and repurposed by developers.Designed to be both a comprehensive reference and a practical cookbook, the text is divided into the following three parts:Part I, Overview, gives high-level descriptions of the hardware and software that make CUDA possible.Part II, Details, provides thorough descriptions of every aspect of CUDA, includingMemory Streams and events Models of execution, including the dynamic parallelism feature, new with CUDA 5.0 and SM 3.5 The streaming multiprocessors, including descriptions of all features through SM 3.5 Programming multiple GPUs TexturingThe source code accompanying Part II is presented as reusable microbenchmarks and microdemos, designed to expose specific hardware characteristics or highlight specific use cases.Part III, Select Applications, details specific families of CUDA applications and key parallel algorithms, including Streaming workloadsReduction Parallel prefix sum (Scan)N-body Image Processing These algorithms cover the full range of potential CUDA applications.

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