FUTURES-AMR: Towards an Adaptive Mesh Refinement Framework for Geosimulations
FUTURES-AMR: Towards an Adaptive Mesh Refinement Framework for Geosimulations
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FUTURES-AMR：面向地理模拟的自适应网格细化框架
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发表时间：
2018
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通讯作者：
R. Meentemeyer
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作者：
Ashwin Shashidharan;Ranga Raju Vatsavai;D. Berkel;R. Meentemeyer
自适应网格细化（AMR）是一种计算技术，用于减少科学模拟中所需的计算量和内存。地理模拟是使用地理数据的科学模拟，通常用于预测城市研究中的城市化结果。然而，缺乏对AMR技术与地理模拟的支持限制了在多个分辨率下探索预测结果。在本文中，我们提出了一个自适应网格细化框架FUTURES-AMR，基于静态用户定义的政策，使多分辨率的地理模拟。我们开发了一个原型的元胞自动机为基础的城市增长模拟未来利用静态和动态网格细化技术与补丁生长算法（PGA）。虽然静态细化技术支持在某个位置静态定义的固定分辨率网格模拟，但动态细化技术支持在运行时基于模拟结果动态细化分辨率。此外，我们开发了两种方法异步AMR和同步AMR，适合在分布式计算环境中的并行执行与不同的支持解决方案集成的多分辨率结果。最后，在城市研究中使用不同政策的FUTURES-AMR框架，我们证明了减少的执行时间和低内存开销的多分辨率模拟。2012年ACM学科分类计算方法学→分布式仿真，计算方法学→多尺度系统，应用计算→环境科学
Adaptive Mesh Refinement (AMR) is a computational technique used to reduce the amount of computation and memory required in scientific simulations. Geosimulations are scientific simulations using geographic data, routinely used to predict outcomes of urbanization in urban studies. However, the lack of support for AMR techniques with geosimulations limits exploring prediction outcomes at multiple resolutions. In this paper, we propose an adaptive mesh refinement framework FUTURES-AMR, based on static user-defined policies to enable multi-resolution geosimulations. We develop a prototype for the cellular automaton based urban growth simulation FUTURES by exploiting static and dynamic mesh refinement techniques in conjunction with the Patch Growing Algorithm (PGA). While, the static refinement technique supports a statically defined fixed resolution mesh simulation at a location, the dynamic refinement technique supports dynamically refining the resolution based on simulation outcomes at runtime. Further, we develop two approaches asynchronous AMR and synchronous AMR, suitable for parallel execution in a distributed computing environment with varying support for solution integration of the multi-resolution results. Finally, using the FUTURES-AMR framework with different policies in an urban study, we demonstrate reduced execution time, and low memory overhead for a multi-resolution simulation. 2012 ACM Subject Classification Computing methodologies → Distributed simulation, Computing methodologies → Multiscale systems, Applied computing → Environmental sciences