超实时多智能体仿真平台的整体体系结构

T. Suzumura, H. Kanezashi
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引用次数: 7

摘要

本文描述了一个超实时多智能体仿真平台的整体架构,通过实现一个完整的集成仿真堆栈,包括仿真运行时和应用层,可用于交通仿真等情况。对于我们的原型系统,第一个实验在256个节点上的1,536个CPU内核上模拟数百万个代理时测试了性能可伸缩性。通过使用MPI将基于x10的agent仿真系统编译成c++,我们可以在78秒内运行600个仿真步骤,比实时运行快近10倍。然后,我们测试了一个横跨日本的全国性网络,该网络能够在使用128个节点的情况下近乎实时地模拟1亿个代理。这是第一次尝试处理如此大量的智能体,并表明该基础设施可以用于各种领域的大规模智能体模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A holistic architecture for super real-time multiagent simulation platforms
This paper describes a holistic architecture for super real-time multi-agent simulation platforms by implementing a complete and integrated simulation stack including a simulation runtime and an application layer that can be used for such situations as traffic simulations. With our prototype system, the first experiment tested the performance scalability when simulating millions of agents on 1,536 CPU cores over 256 nodes. By compiling the X10-based agent simulation system into C++ using MPI, we could run 600 simulation steps in only 78 seconds, which is nearly 10 times faster than real time. We then tested a national network spanning Japan, which was able to simulate a 100 million agents and at near-real time while using 128 nodes. This was the first attempt to deal with such a large number of agents and shows that this infrastructure could be used for large-scale agent simulations in various fields.
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