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Data Parallel C++

Reinders, James - Personal Name; Ashbaugh, Ben - Personal Name; Brodman, James - Personal Name; Kinsner, Michael - Personal Name; Pennycook, John - Personal Name; Tian, Xinmin - Personal Name;

"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 University

Learn 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 Learn

Accelerate C++ programs using data-parallel programming
Use SYCL and C++ compilers that support SYCL
Write portable code for accelerators that is vendor and device agnostic
Optimize code to improve performance for specific accelerators
Be poised to benefit as new accelerators appear from many vendors

Who This Book Is For

New data-parallel programming and computer programmers interested in data-parallel programming using C++

Availability

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Detail Information

Series Title: -
Call Number: -
Publisher: : Apress Berkeley, CA., 2023
Collation: XXX, 630
Language: English
ISBN/ISSN: 978-1-4842-9690-5
Classification: NONE
Content Type: text
Media Type: computer
Carrier Type: online resource
Edition: -
Subject(s): Programming Languages
Compilers
Interpreters
Hardware and Maker
Specific Detail Info: -
Statement of Responsibility: James Reinders , Ben Ashbaugh , James Brodman , Michael Kinsner , John Pennycook , Xinmin Tian

Other Information

Cataloger: reva
Source: -
Validator: -
Digital Object Identifier (DOI): https://doi.org/10.1007/978-1-4842-9691-2
Journal Volume: -
Journal Issue: -
Subtitle: -
Parallel Title: -

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