为什么在线动态网格细化对并行气候模型更好

C. Schepke, N. Maillard, Jörg Schneider, Hans-Ulrich Heiß
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引用次数: 2

摘要

气候模式的预报精度受到计算能力和执行时间的限制。随着计算中处理器的数量和速度的增加,用于表示地球大气的网格的分辨率可以提高,从而使数值预报更加准确,并显示局部现象。然而,一个更精细的网格分辨率,能够在全球大气整合中包括局部现象,仍然是不可能的。为了克服这种情况,可以对不同的区域同时使用不同的网格细化级别。在此背景下,本文评估了运行时网格细化如何提高气候模型的性能。为了便于分析,开发了一种在线动态网格细化方法。当在执行过程中注册特殊的大气条件时,它增加了并行分布式模型部分的网格分辨率。结果表明,这种改进的并行执行在不显著增加执行时间的情况下提供了更好的网格分辨率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Why Online Dynamic Mesh Refinement is Better for Parallel Climatological Models
Forecast precisions of climatological models are limited by computing power and time available for the executions. As more and faster processors are used in the computation, the resolution of the mesh adopted to represent the Earth's atmosphere can be increased, and consequently the numerical forecast is more accurate and shows local phenomena. However, a finer mesh resolution, able to include local phenomena in a global atmosphere integration, is still not possible. To overcome this situation, different mesh refinement levels can be used at the same time for different areas. In this context, this paper evaluates how mesh refinement at run time can improve performance for climatological models. In order to contribute with this analysis, an online dynamic mesh refinement was developed. It increases mesh resolution in parts of a parallel distributed model, when special atmosphere conditions are registered during the execution. The results show that the parallel execution of this improvement provides better resolution for the meshes, without a significant increase of execution time.
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