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  • Book
  • Open Access
  • © 2021

Data Parallel C++

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

  • Learn heterogenous programming for CPU, GPU, FPGA, ASIC, etc.

  • Gain a vision for the future of parallel programming support in C++

  • Program with industrial strength implementations of SYCL, with extensions

Table of contents (19 chapters)

  1. Back Matter

    Pages 531-548

About this book

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++.


  • heterogenous
  • FPGA programming
  • GPU programming
  • Parallel programming
  • Data parallelism
  • SYCL
  • Intel One API

Authors and Affiliations

  • Beaverton, USA

    James Reinders

  • Folsom, USA

    Ben Ashbaugh

  • Marlborough, USA

    James Brodman

  • Halifax, Canada

    Michael Kinsner

  • San Jose, USA

    John Pennycook

  • Fremont, USA

    Xinmin Tian

About the authors

James Reinders is a consultant with more than three decades experience in Parallel Computing, and is an author/co-author/editor of nine technical books related to parallel programming.  He has had the great fortune to help make key contributions to two of the world's fastest computers (#1 on Top500 list) as well as many other supercomputers, and software developer tools. James finished 10,001 days (over 27 years) at Intel in mid-2016, and now continues to write, teach, program, and do consulting in areas related to parallel computing (HPC and AI).  


Bibliographic Information