Data Parallel C++

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 t...

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Auteurs principaux: Reinders, James, Ashbaugh, Ben, Brodman, James, Kinsner, Michael, Pennycook, John, Tian, Xinmin
Format: Online
Langue:anglais
Publié: Springer Nature 2021
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Accès en ligne:ONIX_20201113_9781484255742_23
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author Reinders, James
Ashbaugh, Ben
Brodman, James
Kinsner, Michael
Pennycook, John
Tian, Xinmin
author_browse Ashbaugh, Ben
Brodman, James
Kinsner, Michael
Pennycook, John
Reinders, James
Tian, Xinmin
author_facet Reinders, James
Ashbaugh, Ben
Brodman, James
Kinsner, Michael
Pennycook, John
Tian, Xinmin
author_sort Reinders, James
collection Directory of Open Access Books
description 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++.
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institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
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publisher Springer Nature
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spelling doab-20.500.12854ir-303052025-07-30T10:20:46Z Data Parallel C++ Reinders, James Ashbaugh, Ben Brodman, James Kinsner, Michael Pennycook, John Tian, Xinmin 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 thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general thema EDItEUR::U Computing and Information Technology::UK Computer hardware thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general thema EDItEUR::U Computing and Information Technology::UK Computer hardware 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++. 2021-02-10T13:40:11Z 2021-02-10T13:40:11Z 2020-11-13T13:35:04Z 2021 book ONIX_20201113_9781484255742_23 OCN: 1204226016 https://library.oapen.org/handle/20.500.12657/42917 https://directory.doabooks.org/handle/20.500.12854/30305 eng open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/42917/1/2021_Book_DataParallelC.pdf https://library.oapen.org/bitstream/20.500.12657/42917/1/2021_Book_DataParallelC.pdf https://library.oapen.org/bitstream/20.500.12657/42917/1/2021_Book_DataParallelC.pdf Springer Nature Apress 10.1007/978-1-4842-5574-2 10.1007/978-1-4842-5574-2 9fa3421d-f917-4153-b9ab-fc337c396b5a Apress 548 open access
spellingShingle 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
thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general
thema EDItEUR::U Computing and Information Technology::UK Computer hardware
thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general
thema EDItEUR::U Computing and Information Technology::UK Computer hardware
Reinders, James
Ashbaugh, Ben
Brodman, James
Kinsner, Michael
Pennycook, John
Tian, Xinmin
Data Parallel C++
title Data Parallel C++
title_full Data Parallel C++
title_fullStr Data Parallel C++
title_full_unstemmed Data Parallel C++
title_short Data Parallel C++
title_sort data parallel c
topic 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
thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general
thema EDItEUR::U Computing and Information Technology::UK Computer hardware
thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general
thema EDItEUR::U Computing and Information Technology::UK Computer hardware
topic_facet 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
thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general
thema EDItEUR::U Computing and Information Technology::UK Computer hardware
thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMX Programming and scripting languages: general
thema EDItEUR::U Computing and Information Technology::UK Computer hardware
url ONIX_20201113_9781484255742_23
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