Hidden Bibliographic Details
| Other authors / contributors: | Ashbaugh, Ben, author.
Brodman, James, author.
Kinsner, Michael, author.
Pennycook, John, author.
Tian, Xinmin, author.
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| ISBN: | 9781484255742
1484255747
1484255739
9781484255735
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| Notes: | Includes index.
Open access
Online resource; title from digital title page (viewed on December 16, 2020).
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| Summary: | Learn how to accelerate C++ programs using data parallelism. 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 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. This book teaches data-parallel programming using C++ and the SYCL standard from the Khronos Group and walks through everything needed to use SYCL for programming heterogeneous systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL 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. You will learn: " How to accelerate C++ programs using data-parallel programming " How to target multiple device types (e.g. CPU, GPU, FPGA) " How to use SYCL and SYCL compilers " How to connect with computing's heterogeneous future via Intel's oneAPI initiative
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| Other form: | Print version: Reinders, James. Data parallel C++. [Place of publication not identified] APRESS, 2020 1484255739 9781484255735
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| Standard no.: | 10.1007/978-1-4842-5574-2
9781484255742
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