Data parallel C++: Mastering DPC++ for programming of heterogeneous systems using C++ and SYCL

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Abstract

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.

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Reinders, J., Ashbaugh, B., Brodman, J., Kinsner, M., Pennycook, J., & Tian, X. (2020). Data parallel C++: Mastering DPC++ for programming of heterogeneous systems using C++ and SYCL. Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL (pp. 1–548). Apress Media LLC. https://doi.org/10.1007/978-1-4842-5574-2

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