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        Data Parallel C++

        Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL

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        Author(s)
        Reinders, James
        Ashbaugh, Ben
        Brodman, James
        Kinsner, Michael
        Pennycook, John
        Tian, Xinmin
        Language
        English
        Show full item record
        Abstract
        Learn how to accelerate C++ programs using data parallelism. This open access book enables C++ programmers to be at the forefront of this exciting and important new development that is helping to push computing to new levels. It is full of practical advice, detailed explanations, and code examples to illustrate key topics. Data parallelism in C++ enables access to parallel resources in a modern heterogeneous system, freeing you from being locked into any particular computing device. Now a single C++ application can use any combination of devices—including GPUs, CPUs, FPGAs and AI ASICs—that are suitable to the problems at hand. This book begins by introducing data parallelism and foundational topics for effective use of the SYCL standard from the Khronos Group and Data Parallel C++ (DPC++), the open source compiler used in this book. Later chapters cover advanced topics including error handling, hardware-specific programming, communication and synchronization, and memory model considerations. Data Parallel C++ provides you with everything needed to use SYCL for programming heterogeneous systems. What You'll Learn Accelerate C++ programs using data-parallel programming Target multiple device types (e.g. CPU, GPU, FPGA) Use SYCL and SYCL compilers Connect with computing’s heterogeneous future via Intel’s oneAPI initiative Who This Book Is For Those new data-parallel programming and computer programmers interested in data-parallel programming using C++.
        URI
        https://library.oapen.org/handle/20.500.12657/42917
        Keywords
        Programming Languages, Compilers, Interpreters; Hardware and Maker; Maker; heterogenous; FPGA programming; GPU programming; Parallel programming; Data parallelism; SYCL; Intel One API; Programming & scripting languages: general; Compilers & interpreters; Computer hardware
        DOI
        10.1007/978-1-4842-5574-2
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        2021
        Imprint
        Apress
        Classification
        Programming and scripting languages: general
        Computer hardware
        Pages
        548
        Rights
        http://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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