Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

中文翻译：

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用于扩展具有多个目标区域的天气模拟的分而治之策略

准确，及时地预测诸如飓风和山洪暴发之类的天气现象，需要在一个粗略的模拟域内对多个较细的目标区域进行高保真度的计算密集型模拟。当前的天气应用程序使用所有可用的处理器顺序执行这些嵌套的模拟，由于它们的亚线性可伸缩性，因此这不是最佳的。在这项工作中，我们提出了一种基于将二维处理器网格划分为与每个域相关的不相交的矩形区域的并行执行多个嵌套域模拟的策略。我们提出了性能预测，处理器分配方法和环形互连上区域的拓扑感知映射的新颖组合。