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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams

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The paper investigates parallel data processing in a hybrid CPU+GPU(s) system using multiple CUDA streams for overlapping communication and computations. This is crucial for efficient processing of data, in particular incoming data stream processing that would naturally be forwarded using multiple CUDA streams to GPUs. Performance is evaluated for various compute time to host-device communication time ratios, numbers of CUDA streams, for various numbers of threads managing computations on GPUs. Tests also reveal benefits of using CUDA MPS for overlapping communication and computations when using multiple processes. Furthermore, using standard memory allocation on a GPU and Unified Memory versions are compared, the latter including programmer added prefetching. Performance of a hybrid CPU+GPU version as well as scaling across multiple GPUs are demonstrated showing good speed-ups of the approach. Finally, the performance per power consumption of selected configurations are presented for various numbers of streams and various relative performances of GPUs and CPUs.

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Wersja publikacji
Accepted albo Published Version
Licencja
Copyright (2020 Institute of Informatics Slovak Academy of Sciences)

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Informacje szczegółowe

Kategoria:
Publikacja w czasopiśmie
Typ:
artykuły w czasopismach
Opublikowano w:
COMPUTING AND INFORMATICS nr 39, strony 510 - 536,
ISSN: 1335-9150
Język:
angielski
Rok wydania:
2020
Opis bibliograficzny:
Czarnul P.: Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams// COMPUTING AND INFORMATICS -Vol. 39,iss. 3 (2020), s.510-536
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.31577/cai_2020_3_510
Weryfikacja:
Politechnika Gdańska

wyświetlono 14 razy

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