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

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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 GP...

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Bibliographic Details
Main Authors: Reinders, James (Author), Ashbaugh, Ben (Author), Brodman, James (Author), Kinsner, Michael (Author), Pennycook, John (Author), Tian, Xinmin (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Berkeley, CA : Apress : Imprint: Apress, 2021.
Edition:1st ed. 2021.
Subjects:
Compilers (Computer programs).
Makerspaces.
Compilers and Interpreters.
Maker.
Online Access:Link to Metadata
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Table of Contents:
  • 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.

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