NG-TEPHRA:网格和云中的大规模并行,Nimrod/ g支持的火山模拟

Santiago Nunez, B. Bethwaite, J. Brenes, Gustavo Barrantes, José Castro, E. Malavassi, D. Abramson
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引用次数: 10

摘要

火山是环太平洋地区的主要危险因素,其关注的焦点主要分为火山碎屑流和火山灰沉积。后者由于其广泛的地理范围和对人类活动和健康的长期影响而具有更大的影响。TEPHRA是一种火山灰分散模型,其基础是平流扩散铃木模型的简单版本,该模型在哥斯达黎加的Iraz\'u火山上进行了重新研究和修改。完整的参数探索是必要的在这种特殊情况下(尽管不充分)由于稀缺的观测数据。我们提出本文模型,其假设和局限性以及应用程序生命周期产生的火山灰分布图形。描述了计算实验设置,特别是使用Nimrod/G进行非均匀参数扫描及其对执行时间的影响。我们还分析了电子科学实验中常见的新参数丢弃机制的实现,其中新参数集的顺序生成必须与早期验证相辅相成,以避免将CPU时间分配给非有效场景。最后,对Amazon EC2 Cloud中传统HPC集群和云计算资源的四个100k场景运行进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NG-TEPHRA: A Massively Parallel, Nimrod/G-enabled Volcanic Simulation in the Grid and the Cloud
Volcanoes are a principal factor of hazard across the Pacific Rim, with their focus of interest mostly divided into pyroclastic flows and ash deposition. The latter has significantly more impact due to its widespread geographical reach and prolonged effects in human activities and health. TEPHRA is a volcanic ash dispersion model based on a simple version of the advection-diffusion Suzuki model, which has been revisited and modified for the Iraz\'u volcano in Costa Rica. A full parameter exploration is necessary in this particular case (albeit not sufficient) due to scarce observational data. We present in this paper the model, its assumptions and limitations as well as application lifecycle with resulting ash distribution graphics. The computational experimental settings are described, in particular the use of Nimrod/G with respect to non-homogeneous parameter sweeps and its impact on execution time. We also analyze the implementation of a new parameter discard mechanism common to e-Science experiments where sequential generation of new parameter sets has to be complemented with an early verification in order to avoid allocation of CPU time to non-valid scenarios. Finally four sample 100K-scenario runs are analyzed for both traditional HPC clustering and Cloud computing resources in the Amazon EC2 Cloud.
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