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Data Parallel C++

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Produktnummer: 18635aea3626454f528b1d7d0d099aeca7
Autor: Ashbaugh, Ben Brodman, James Kinsner, Michael Pennycook, John Reinders, James Tian, Xinmin
Themengebiete: Data parallelism FPGA programming GPU programming Intel One API Open Access Parallel programming SYCL heterogenous
Veröffentlichungsdatum: 04.10.2023
EAN: 9781484296905
Auflage: 2
Sprache: Englisch
Seitenzahl: 630
Produktart: Kartoniert / Broschiert
Verlag: APRESS
Untertitel: Programming Accelerated Systems Using C++ and SYCL
Produktinformationen "Data Parallel C++"
"This book, now in is second edition, is the premier resource to learn SYCL 2020 and is the ONLY book you need to become part of this community." Erik Lindahl, GROMACS and Stockholm UniversityLearn how to accelerate C++ programs using data parallelism and SYCL.This open access book enables C++ programmers to be at the forefront of this exciting and important development that is helping to push computing to new levels. This updated second edition is full of practical advice, detailed explanations, and code examples to illustrate key topics.SYCL enables access to parallel resources in modern accelerated heterogeneous systems. Now, a single C++ application can use any combination of devices–including GPUs, CPUs, FPGAs, and ASICs–that are suitable to the problems at hand.This book teaches data-parallel programming using C++ with SYCL and walks through everything needed to program accelerated systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL. Later chapters cover advanced topics, including error handling, hardware-specific programming, communication and synchronization, and memory model considerations.All source code for the examples used in this book is freely available on GitHub. The examples are written in modern SYCL and are regularly updated to ensure compatibility with multiple compilers.What You Will LearnAccelerate C++ programs using data-parallel programmingUse SYCL and C++ compilers that support SYCLWrite portable code for accelerators that is vendor and device agnosticOptimize code to improve performance for specific acceleratorsBe poised to benefit as new accelerators appear from many vendorsWho This Book Is ForNew data-parallel programming and computer programmers interested in data-parallel programming using C++This is an open access book.
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