Three-level-parallelization support framework for large-scale analytic simulation

Yi-ping Yao, Dong Meng, Feng Zhu, Lai-bin Yan, Qing-jun Qu, Zhong-wei Lin and Hai-bo Ma

Journal of Simulation, 2017, vol. 11, issue 3, 194-207

Abstract: Fully exploiting the parallelism in large-scale analytic simulation is an essential way to meet the increasing demand for computing resources. This paper deconstructs large-scale analytic simulation using a hierarchical approach. Five computational characteristics that cause the huge computing requirements of analytic simulation are summarized: “Multi-sample”, “Multi-entity”, “Running-as-fast-as-possible”, “Synchronization for constraint of causality”, and “Complex model calculation”. According to these characteristics, a “Sample, Entity, Model” three-level-Parallelization support framework is proposed to exploit the parallelism on three levels. Under the guidance of this framework, a High-Performance Simulation Computer system which integrated software management and hardware support was designed, and then applied in realistic applications. The experimental results show that the designed system can effectively utilize the potential parallelism characteristics in analytic simulation. Consequently, the simulation performance can be improved dozens or even hundreds of times.

Date: 2017
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DOI: 10.1057/s41273-017-0057-x

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