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Open access
Title
Data parallel C++ : mastering DPC++ for programming of heterogeneous systems using C++ and SYCL / James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook, Xinmin Tian.
ISBN
9781484255742 (electronic book)
1484255747 (electronic book)
1484255739 (Print)
9781484255735 (Print)
Published
New York, NY : Apress, [2020]
Language
English
Description
1 online resource (xxvi, 548 pages) : illustrations (some color)
Item Number
10.1007/978-1-4842-5574-2 doi
9781484255742
Call Number
QA76.88 .R45 2020
Dewey Decimal Classification
004.35
Summary
Learn how to accelerate C++ programs using data parallelism. 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 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. This book teaches data-parallel programming using C++ and the SYCL standard from the Khronos Group and walks through everything needed to use SYCL for programming heterogeneous systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL 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. You will learn: " How to accelerate C++ programs using data-parallel programming " How to target multiple device types (e.g. CPU, GPU, FPGA) " How to use SYCL and SYCL compilers " How to connect with computing's heterogeneous future via Intel's oneAPI initiative
Note
Includes index.
Access Note
Open access
Source of Description
Online resource; title from digital title page (viewed on December 16, 2020).
Chapter 1: Introduction
Chapter 2: Where code executes
Chapter 3: Data management and ordering the uses of data
Chapter 4: Expressing parallelism
Chapter 5: Error handling
Chapter 6: USM in detail
Chapter 7: Buffers in detail
Chapter 8: DAG scheduling in detail
Chapter 9: Local memory and work-group barriers
Chapter 10: Defining kernels
Chapter 11: Vectors
Chapter 12: Device-specific extension mechanism
Chapter 13: Programming for GPUs
Chapter 14: Programming for CPUs
Chapter 15: Programming for FPGAs
Chapter 16: Address spaces and multi_ptr
Chapter 17: Using libraries
Chapter 18: Working with OpenCL
Chapter 19: Memory model and atomics.
