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HPC Large-Scale Pedestrian Simulation Based on Proxemics Rules

机译:基于专业规则的HPC大规模步行模拟

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摘要

The problem of efficient pedestrian simulation, when large-scale environment is considered, poses a great challenge. When the simulation model size exceeds the capabilities of a single computing node or the results are expected quickly, the simulation algorithm has to use many cores and nodes. The problem considered in the presented work is the task of splitting the data-intensive computations with a common data structure into separate computational domains, while preserving the crucial features of the simulation model. We propose a new model created on the basis of some popular pedestrian models, which can be applied in parallel processing. We describe its implementation in a highly scalable simulation framework. Additionally, the preliminary results are presented and outcomes are discussed.
机译:当考虑大规模环境时,有效的行人模拟问题,构成了巨大的挑战。 当仿真模型大小超过单个计算节点的功能或预期的结果,模拟算法必须使用许多核心和节点。 在所呈现的工作中考虑的问题是将数据密集型计算与公共数据结构分成单独的计算域,同时保留模拟模型的关键特征。 我们提出了一种在一些流行的行人模型的基础上创建的新模型,可以应用于并行处理。 我们在高度可扩展的仿真框架中描述了其实现。 另外,介绍了初步结果并讨论了结果。

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