Data parallel C++ : mastering DPC++ for programming of heterogeneous systems using C++ and SYCL /

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 G...

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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Reinders, James (Auteur), Ashbaugh, Ben (Auteur), Brodman, James (Auteur), Kinsner, Michael (Auteur), Pennycook, John (Auteur), Tian, Xinmin (Auteur)
Format: Électronique eBook
Langue:Inglés
Publié: New York, NY : Apress, [2020]
Sujets:
Heterogeneous computing.
C++ (Computer program language)
OpenCL (Computer program language)
Calcul hétérogène.
C++ (Langage de programmation)
OpenCL (Langage de programmation)
Accès en ligne:Texto completo (Requiere registro previo con correo institucional)
Table des matières:
  • 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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