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The Journal of Supercomputing

Erschienen in:

19.01.2018

Experiences with implementing parallel discrete-event simulation on GPU

verfasst von: Janche Sang, Che-Rung Lee, Vernon Rego, Chung-Ta King

Erschienen in: The Journal of Supercomputing | Ausgabe 8/2019

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Abstract

Modern graphics processing units (GPUs) offer much more computational power than recent CPUs by providing a vast number of simple, data-parallel, multithreaded cores. In this study, we focus on the use of a GPU to perform parallel discrete-event simulation. Our approach is to use a modified service time distribution function to allow more independent events to be processed in parallel. The implementation issues and alternative strategies will be discussed in detail. We describe and compare our experience and results in using Thrust and CUB, two open-source parallel algorithms libraries which resemble the C\({++}\) Standard Template Library, to build our tool. The experimental results show that our implementation can be two orders of magnitude faster than the sequential simulation for large-scale simulation models.

Vorheriger Artikel On dynamic memory allocation in sliding-window parallel patterns for streaming analytics

Nächster Artikel Multi-objective algorithms for the application mapping problem in heterogeneous multiprocessor embedded system design

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Titel: Experiences with implementing parallel discrete-event simulation on GPU
verfasst von: Janche Sang
Che-Rung Lee
Vernon Rego
Chung-Ta King
Publikationsdatum: 19.01.2018
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 8/2019
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-018-2254-4

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