使用Python开发基于分布式代理的建模工具包的经验
Nicholson T Collier1, Jonathan Ozik1, Eric R Tatara1
1Decision and Infrastructure Sciences, Argonne National Laboratory, Lemont, IL USA.
概括
我们开发了Repast4Py,这是一个基于Python的工具包,用于在高性能计算 (HPC) 资源上进行分布式代理式建模 (ABM). 该工具包旨在简化复杂系统模型的创建,以便更广泛地采用科学方法.
科学领域:
- 计算科学 计算科学
- 复杂系统建模 复杂系统建模
- 基于代理的建模模型
背景情况:
- 基于分布式代理的建模 (ABM) 为大型复杂系统提供了先进的模拟功能.
- 专业知识要求目前限制了分布式ABM的广泛采用.
研究的目的:
- 介绍Repast4Py的开发,这是一个基于Python的分布式ABM工具包.
- 根据先前的经验,确定一个用户友好的分布式ABM工具包的关键元素.
主要方法:
- 为了提高性能,利用Python的C-API,Numba,NumPy和PyTorch.
- 在开发Repast for High Performance Computing (Repast HPC) 的经验基础上.
主要成果:
- 已经开发了Repast4Py的初始实现.
- 该工具包旨在在大型高性能计算 (HPC) 资源上实现可扩展性.
结论:
- Repast4Py旨在降低分布式ABM开发的进入壁垒.
- 该工具包有助于利用先进的计算架构进行复杂的系统模拟.
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