Data Parallel C++
"This book, now in is second edition, is the premier resource to learn SYCL 2020 and is the ONLY book you need to become part of this community." Erik Lindahl, GROMACS and Stockholm University Learn how to accelerate C++ programs using data parallelism and SYCL. This open access book enables C++ pro...
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| Format: | Online |
| Langue: | anglais |
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Springer Nature
2023
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| Accès en ligne: | ONIX_20231013_9781484296912_4 |
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| _version_ | 1869518678998908928 |
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| author | Reinders, James Ashbaugh, Ben Brodman, James Kinsner, Michael Pennycook, John Tian, Xinmin |
| author_browse | Ashbaugh, Ben Brodman, James Kinsner, Michael Pennycook, John Reinders, James Tian, Xinmin |
| author_facet | Reinders, James Ashbaugh, Ben Brodman, James Kinsner, Michael Pennycook, John Tian, Xinmin |
| author_sort | Reinders, James |
| collection | Directory of Open Access Books |
| description | "This book, now in is second edition, is the premier resource to learn SYCL 2020 and is the ONLY book you need to become part of this community." Erik Lindahl, GROMACS and Stockholm University Learn how to accelerate C++ programs using data parallelism and SYCL. This open access book enables C++ programmers to be at the forefront of this exciting and important development that is helping to push computing to new levels. This updated second edition is full of practical advice, detailed explanations, and code examples to illustrate key topics. SYCL enables access to parallel resources in modern accelerated heterogeneous systems. Now, a single C++ application can use any combination of devices–including GPUs, CPUs, FPGAs, and ASICs–that are suitable to the problems at hand. This book teaches data-parallel programming using C++ with SYCL and walks through everything needed to program accelerated systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL. Later chapters cover advanced topics, including error handling, hardware-specific programming, communication and synchronization, and memory model considerations. All source code for the examples used in this book is freely available on GitHub. The examples are written in modern SYCL and are regularly updated to ensure compatibility with multiple compilers. What You Will Learn Accelerate C++ programs using data-parallel programming Use SYCL and C++ compilers that support SYCL Write portable code for accelerators that is vendor and device agnostic Optimize code to improve performance for specific accelerators Be poised to benefit as new accelerators appear from many vendors Who This Book Is For New data-parallel programming and computer programmers interested in data-parallel programming using C++ This is an open access book. |
| format | Online |
| id | doab-20.500.12854ir-117557 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1175572025-03-20T04:19:06Z Data Parallel C++ Reinders, James Ashbaugh, Ben Brodman, James Kinsner, Michael Pennycook, John Tian, Xinmin heterogenous FPGA programming GPU programming Parallel programming Data parallelism SYCL Intel One API "This book, now in is second edition, is the premier resource to learn SYCL 2020 and is the ONLY book you need to become part of this community." Erik Lindahl, GROMACS and Stockholm University Learn how to accelerate C++ programs using data parallelism and SYCL. This open access book enables C++ programmers to be at the forefront of this exciting and important development that is helping to push computing to new levels. This updated second edition is full of practical advice, detailed explanations, and code examples to illustrate key topics. SYCL enables access to parallel resources in modern accelerated heterogeneous systems. Now, a single C++ application can use any combination of devices–including GPUs, CPUs, FPGAs, and ASICs–that are suitable to the problems at hand. This book teaches data-parallel programming using C++ with SYCL and walks through everything needed to program accelerated systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL. Later chapters cover advanced topics, including error handling, hardware-specific programming, communication and synchronization, and memory model considerations. All source code for the examples used in this book is freely available on GitHub. The examples are written in modern SYCL and are regularly updated to ensure compatibility with multiple compilers. What You Will Learn Accelerate C++ programs using data-parallel programming Use SYCL and C++ compilers that support SYCL Write portable code for accelerators that is vendor and device agnostic Optimize code to improve performance for specific accelerators Be poised to benefit as new accelerators appear from many vendors Who This Book Is For New data-parallel programming and computer programmers interested in data-parallel programming using C++ This is an open access book. 2023-10-14T04:00:45Z 2023-10-14T04:00:45Z 2023-10-13T15:43:12Z 2023 book ONIX_20231013_9781484296912_4 OCN: 1403550971 https://library.oapen.org/handle/20.500.12657/76704 9781484296912 9781484296905 https://directory.doabooks.org/handle/20.500.12854/117557 eng open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/76704/1/978-1-4842-9691-2.pdf https://library.oapen.org/bitstream/20.500.12657/76704/1/978-1-4842-9691-2.pdf https://library.oapen.org/bitstream/20.500.12657/76704/1/978-1-4842-9691-2.pdf Springer Nature Apress 10.1007/978-1-4842-9691-2 10.1007/978-1-4842-9691-2 9fa3421d-f917-4153-b9ab-fc337c396b5a Intel Corporation ecf22abb-5067-4082-9194-c9d58cc69c39 9781484296912 9781484296905 Apress 630 Berkeley [...] open access |
| spellingShingle | heterogenous FPGA programming GPU programming Parallel programming Data parallelism SYCL Intel One API Reinders, James Ashbaugh, Ben Brodman, James Kinsner, Michael Pennycook, John Tian, Xinmin Data Parallel C++ |
| title | Data Parallel C++ |
| title_full | Data Parallel C++ |
| title_fullStr | Data Parallel C++ |
| title_full_unstemmed | Data Parallel C++ |
| title_short | Data Parallel C++ |
| title_sort | data parallel c |
| topic | heterogenous FPGA programming GPU programming Parallel programming Data parallelism SYCL Intel One API |
| topic_facet | heterogenous FPGA programming GPU programming Parallel programming Data parallelism SYCL Intel One API |
| url | ONIX_20231013_9781484296912_4 |
| work_keys_str_mv | AT reindersjames dataparallelc AT ashbaughben dataparallelc AT brodmanjames dataparallelc AT kinsnermichael dataparallelc AT pennycookjohn dataparallelc AT tianxinmin dataparallelc |