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oapen-20.500.12657-767042023-10-14T02:42:47Z 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 bic Book Industry Communication::U Computing & information technology::UM Computer programming / software development::UMX Programming & scripting languages: general bic Book Industry Communication::U Computing & information technology::UK Computer hardware "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. 2023-10-13T15:43:12Z 2023-10-13T15:43:12Z 2023 book ONIX_20231013_9781484296912_4 9781484296912 9781484296905 https://library.oapen.org/handle/20.500.12657/76704 eng application/pdf n/a 978-1-4842-9691-2.pdf https://link.springer.com/978-1-4842-9691-2 Springer Nature Apress 10.1007/978-1-4842-9691-2 10.1007/978-1-4842-9691-2 6c6992af-b843-4f46-859c-f6e9998e40d5 ecf22abb-5067-4082-9194-c9d58cc69c39 9781484296912 9781484296905 Apress 630 Berkeley [...] Intel Corporation Intel open access
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"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.
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