Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL
暫譯: 數據並行 C++：掌握 DPC++ 以使用 C++ 和 SYCL 編程異構系統

Reinders, James, Ashbaugh, Ben, Brodman, James

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

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商品描述

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-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++.

 

商品描述(中文翻譯)

學習如何使用資料平行性加速 C++ 程式。這本開放存取的書籍使 C++ 程式設計師能夠站在這一令人興奮且重要的新發展的最前沿，這一發展正在幫助計算推向新的高度。書中充滿了實用建議、詳細解釋和代碼範例，以說明關鍵主題。

C++ 中的資料平行性使得在現代異構系統中訪問平行資源成為可能，讓您不再被鎖定在任何特定的計算設備上。現在，單一的 C++ 應用程式可以使用任何適合當前問題的設備組合，包括 GPU、CPU、FPGA 和 AI ASIC。

本書首先介紹資料平行性以及有效使用 Khronos Group 的 SYCL 標準和本書中使用的開源編譯器 Data Parallel C++ (DPC++) 的基礎主題。後面的章節涵蓋了進階主題，包括錯誤處理、硬體特定編程、通信與同步以及記憶體模型考量。

Data Parallel C++ 提供了使用 SYCL 進行異構系統編程所需的一切。

您將學到什麼


  • 使用資料平行編程加速 C++ 程式

  • 針對多種設備類型（例如 CPU、GPU、FPGA）

  • 使用 SYCL 和 SYCL 編譯器

  • 通過 Intel 的 oneAPI 計畫與計算的異構未來連接

本書適合誰

對資料平行編程感興趣的初學者和使用 C++ 的計算機程式設計師。

 

作者簡介

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).

 

作者簡介(中文翻譯)

詹姆斯·瑞德斯（James Reinders）是一位擁有超過三十年平行計算經驗的顧問，也是九本與平行程式設計相關的技術書籍的作者、合著者和編輯。他有幸為全球最快的兩台電腦（在 Top500 名單上排名第一）以及許多其他超級電腦和軟體開發工具做出重要貢獻。詹姆斯於2016年中旬在英特爾（Intel）完成了10,001天（超過27年）的工作，現在繼續在平行計算（高效能計算和人工智慧）相關領域進行寫作、教學、程式設計和顧問工作。

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