大型云模拟的并行事件系统

D. Sallo, G. Kecskeméti
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引用次数: 0

摘要

离散事件模拟(DES)框架在支持和评估云计算环境方面获得了极大的普及。它们支持复杂场景的决策,节省时间和精力。这些框架中的大多数缺乏并行执行。尽管是一个顺序框架,但在模拟基础设施即服务(IaaS)云时,DISSECT-CF带来了显著的性能改进。即使对最先进的顺序模拟器进行了这些改进,也有一些场景(例如,大规模的物联网或无服务器计算系统)是DISSECT-CF无法及时模拟的。为了纠正这种情况,本文将并行执行引入其最抽象的子系统:事件系统。新的事件子系统检测在模拟的特定时间实例中何时发生多个事件,并决定以并行或顺序方式执行它们。该决策主要基于独立事件的数量和特定事件的预期工作负载。在我们的评估中,我们只关注时间管理场景。当我们这样做时,我们确保事件的行为应该等同于现实的,更大规模的模拟场景。这使我们能够理解并行性对整个框架的影响,同时我们还展示了新系统与旧顺序系统相比的增益。关于可伸缩性,我们观察到它与所使用的SMP主机中的内核数量成正比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Parallel Event System for Large-Scale Cloud Simulations in DISSECT-CF
Discrete Event Simulation (DES) frameworks gained significant popularity to support and evaluate cloud computing environments. They support decision-making for complex scenarios, saving time and effort. The majority of these frameworks lack parallel execution. In spite being a sequential framework, DISSECT-CF introduced significant performance improvements when simulating Infrastructure as a Service (IaaS) clouds. Even with these improvements over the state of the art sequential simulators, there are several scenarios (e.g., large scale Internet of Things or serverless computing systems) which DISSECT-CF would not simulate in a timely fashion. To remedy such scenarios this paper introduces parallel execution to its most abstract subsystem: the event system. The new event subsystem detects when multiple events occur at a specific time instance of the simulation and decides to execute them either on a parallel or a sequential fashion. This decision is mainly based on the number of independent events and the expected workload of a particular event. In our evaluation, we focused exclusively on time management scenarios. While we did so, we ensured the behaviour of the events should be equivalent to realistic, larger-scale simulation scenarios. This allowed us to understand the effects of parallelism on the whole framework, while we also shown the gains of the new system compared to the old sequential one. With regards to scaling, we observed it to be proportional to the number of cores in the utilised SMP host.
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