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On an Implementation of the TM5 Global Model on a Cluster of Workstations

机译:关于TM5全局模型在工作站集群上的实现

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TM5 is a global chemistry Transport Model. It allows two-way nested zooming which leads to possibility to run the model on relatively very fine space grid (1° × 1°) over selected regions (Europe is most often used in up to now experiments but North America, Africa and Asia can be treated separately or in combinations). The boundary conditions for the zoomed subdomains are provided consistently from the global model. The TM5 model is a good tool for studying some effects due to the grid refinement on global atmospheric chemistry issues (intercontinental transport of air pollutants, etc.). The huge increase in the number of the multi-processor platforms and their differences leads to a need of different approaches in order to meet the requirements for the optimality of the computer runs. The paper is devoted to an implementation of a parallel version of the TM5 model on a cluster of SUN Workstations and to the developing of a new parallel algorithm. It is based on the decomposition, in some sense, of the computational domain supposing that the zoomed regions are more than one. If it is assumed that the number of zoomed regions is N and the number of the processors available is p. The processors are divided in N/p groups and each group is responsible for the whole computational domain and one of the zoomed regions. Some communications are needed in order to impose the inner boundary conditions. The new algorithm has better parallel feathers than the old one which is used in the inner level. Some results concerning the CPU time, speed up and efficiency can be found.
机译:TM5是全球化学物运输模型。它允许双向嵌套缩放,这使得有可能在选定区域的相对非常精细的空间网格(1°×1°)上运行模型(欧洲是迄今为止最常使用的实验,但北美,非洲和亚洲可以单独或组合处理)。从全局模型中一致地提供了缩放子域的边界条件。 TM5模型是研究网格优化对全球大气化学问题(空气污染物的洲际迁移等)造成的某些影响的良好工具。多处理器平台数量的巨大增加以及它们之间的差异导致需要采用不同的方法来满足计算机运行优化的要求。本文致力于在SUN工作站集群上实现TM5模型的并行版本,并致力于开发新的并行算法。在某种意义上,它是基于对计算域的分解(假定缩放区域大于一个)。如果假定缩放区域的数量为N,并且可用处理器的数量为p。处理器分为N / p个组,每个组负责整个计算域和一个缩放区域。为了强加内部边界条件,需要一些通信。与内部级别使用的旧算法相比,新算法具有更好的并行羽化。可以找到有关CPU时间,速度和效率的一些结果。

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