| 书目名称 | Data Parallel C++ | | 副标题 | Mastering DPC++ for | | 编辑 | James Reinders,Ben Ashbaugh,Xinmin Tian | | 视频video | | | 概述 | 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 extensi | | 图书封面 |  | | 描述 | .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-parallelprogramming.Target | | 出版日期 | Book‘‘‘‘‘‘‘‘ 20211st edition | | 关键词 | heterogenous; FPGA programming; GPU programming; Parallel programming; Data parallelism; SYCL; Intel One A | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-5574-2 | | isbn_ebook | 978-1-4842-5574-2 | | copyright | Intel Corporation 2021 |
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发表于 2025-3-21 16:57:15
