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Grid implementation of the weather research and forecasting model

机译:网格实现的天气研究与预报模型

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Atmospheric science is advancing towards very complex phenomena at ever smaller temporal and spatial scales. One of the principal tools utilized in atmospheric science are weather prediction models. These models usually demand large execution times and resource allocation, such as CPU time and storage space. The main goal of our research is porting of the Weather Research and Forecasting model to the Grid infrastructure. Porting has been done through bash scripts that are using existing Grid tools for job and data management, authentification mechanisms, and other application level services produced within the SEEGRID project. In this paper, through a few model runs on the Grid we describe certain benefits not only in the overall execution time but also in the ability of performing concurrent runs of the same model especially for scientific purposes. During the execution, we have also faced some drawbacks in data bandwidth, unreliability of some Grid services and relatively hard control of the model execution flow. The final conclusion is that there is a big need and justification for porting the WRF model to the Grid, although it takes a lot of effort to be properly implemented.
机译:大气科学正在以越来越小的时空尺度向非常复杂的现象发展。大气科学中使用的主要工具之一是天气预报模型。这些模型通常需要较长的执行时间和资源分配,例如CPU时间和存储空间。我们研究的主要目标是将天气研究和预测模型移植到Grid基础设施。已通过bash脚本完成了移植,这些脚本使用现有的Grid工具进行作业和数据管理,身份验证机制以及SEEGRID项目中产生的其他应用程序级别的服务。在本文中,通过在Grid上运行一些模型,我们不仅在总体执行时间上描述了某些好处,而且还描​​述了执行同一模型的并发运行的能力(特别是出于科学目的)的某些好处。在执行过程中,我们还面临数据带宽,某些Grid服务的不可靠性以及对模型执行流程的相对较难控制等缺点。最后的结论是,将WRF模型移植到Grid有很大的需求和理由,尽管需要花费大量精力才能正确实施。

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