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Experiences with implementing parallel discrete-event simulation on GPU
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Experiences with implementing parallel discrete-event simulation on GPU

Janche Sang, Che-Rung Lee, Vernon RegoChung-Ta King
Journal of Supercomputing, 頁碼.1-18
01/2018

摘要

CUDA;Discrete-event simulation;GPU;Parallel simulation;Thrust/CUB Software Theoretical Computer Science Information Systems Hardware and Architecture

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(Formula presented.) 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.

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