并行离散事件仿真中的负载感知动态时间同步

Ali Eker, Yehia Arafa, Abdel-Hameed A. Badawy, N. Santhi, S. Eidenbenz, D. Ponomarev
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引用次数: 4

摘要

传统的并行离散事件仿真(PDES)系统采用单片方法选择线程同步协议。它们要么实现基于时间窗口的保守同步,要么实现基于时间扭曲同步的乐观事件处理能力。在本文中,我们证明了这种二元选择是次优的和不必要的,特别是在负载分布随时间变化的现实情况下。因此,我们提出了一种新的PDES同步方案,称为Hybrid PDES,该方案基于仿真运行时特性在保守和乐观同步协议之间动态切换。Hybrid PDES的主要目标是利用乐观事件处理,只要它有利于系统性能和可伸缩性。我们在基于Python和lua的Simian PDES引擎中实现混合PDES,并在基于hold, La-pdes和PPT-GPU仿真应用程序的Intel Knights Landing和AMD EPYC处理器上演示了高达3倍的性能改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Load-Aware Dynamic Time Synchronization in Parallel Discrete Event Simulation
Traditional Parallel Discrete Event Simulation (PDES) systems employ a monolithic approach for choosing their thread synchronization protocol. They either implement a Time Window-based conservative synchronization or an optimistic event processing capability based on the Time Warp synchronization. In this paper, we show that this binary choice is suboptimal and unnecessary, particularly in the realistic situation where the load distribution across the simulation domain changes over time. We thus propose a new PDES synchronization scheme, called Hybrid PDES, that dynamically switches between conservative and optimistic synchronization protocols based on the simulation run time characteristics. The primary objective of Hybrid PDES is to exploit the optimistic event processing as long as it is beneficial for the system performance and scalability. We implement Hybrid PDES in Python- and Lua-based Simian PDES engines and demonstrate up to 3X performance improvements on Intel Knights Landing and AMD EPYC processors based on the Phold, La-pdes and PPT-GPU simulation applications.
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