|
| Titre : |
Data Parallel C++ : Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL |
| Type de document : |
document électronique |
| Auteurs : |
James Reinders, Auteur ; Ben Ashbaugh, Auteur ; James Brodman, Auteur |
| Editeur : |
Berlin [Germany] : Springer Nature Limited |
| Année de publication : |
2021 |
| Importance : |
548 p. |
| Présentation : |
ill. |
| ISBN/ISSN/EAN : |
978-1-4842-5574-2 |
| Langues : |
Anglais (eng) |
| Catégories : |
Open Access Publications
|
| Tags : |
heterogenous FPGA programming GPU programming Parallel programming Data parallelism SYCL Intel One API |
| Index. décimale : |
005.133 Langages de programmation particuliers |
| Résumé : |
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. |
| En ligne : |
https://doi.org/10.1007/978-1-4842-5574-2 |
Data Parallel C++ : Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL [document électronique] / James Reinders, Auteur ; Ben Ashbaugh, Auteur ; James Brodman, Auteur . - Berlin (Germany) : Springer Nature Limited, 2021 . - 548 p. : ill. ISBN : 978-1-4842-5574-2 Langues : Anglais ( eng)
| Catégories : |
Open Access Publications
|
| Tags : |
heterogenous FPGA programming GPU programming Parallel programming Data parallelism SYCL Intel One API |
| Index. décimale : |
005.133 Langages de programmation particuliers |
| Résumé : |
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. |
| En ligne : |
https://doi.org/10.1007/978-1-4842-5574-2 |
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Accueil
Data Parallel C++
