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Accelerator Programming Using Directives: 8th International Workshop, WACCPD 2021, Virtual Event, November 14, 2021, Proceedings 1st ed. 2022 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 149 pages, height x width: 235x155 mm, weight: 261 g, 40 Illustrations, color; 7 Illustrations, black and white; XIV, 149 p. 47 illus., 40 illus. in color., 1 Paperback / softback
  • Sērija : Programming and Software Engineering 13194
  • Izdošanas datums: 15-May-2022
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030977587
  • ISBN-13: 9783030977580
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Accelerator Programming Using Directives: 8th International Workshop, WACCPD 2021, Virtual Event, November 14, 2021, Proceedings 1st ed. 2022Palielināt
  • Formāts: Paperback / softback, 149 pages, height x width: 235x155 mm, weight: 261 g, 40 Illustrations, color; 7 Illustrations, black and white; XIV, 149 p. 47 illus., 40 illus. in color., 1 Paperback / softback
  • Sērija : Programming and Software Engineering 13194
  • Izdošanas datums: 15-May-2022
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030977587
  • ISBN-13: 9783030977580
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783030977580.html
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This book constitutes the proceedings of the 8th International Workshop on Accelerator Programming Using Directives, WACCPD 2021, which took place in November 2021. The conference was held as hybrid event. 





WACCPD is one of the major forums for bringing together users, developers, and the software and tools community to share knowledge and experiences when programming emerging complex parallel computing systems. The 7 papers presented in this volume were carefully reviewed and selected from 11 submissions. They were organized in topical sections named: Directive Alternatives; Directive Extensions; and Directive Case Studies.
Can Fortran's `do concurrent' Replace Directives for Accelerated
Computing?.- Achieving near native runtime performance and cross-platform
performance portability for random number generation through SYCL
interoperability.- Extending OpenMP for Machine Learning-Driven Adaptation.-
GPU porting of scalable implicit solver with Greens function-based neural
networks by OpenACC.- Challenges Porting a C++ Template-Metaprogramming
Abstraction Layer to Directive-based Offloading.- Accelerating quantum
many-body configuration interaction with directives.- GPU offloading of a
large-scale gyrokinetic particle-in-cell Fortran code: From OpenACC to OpenMP.