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Implementation and performance evaluation of a parallel ocean model

机译:平行海洋模型的实施和性能评估

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Ocean models have been used to study global phenomena such as the El Nino Southern Oscillation. The effects of El Nino are felt worldwide and are of importance to all segments of society. High resolution ocean models are being developed to run more sophisticated simulations. The demand for computing power is expected to increase drastically with the use of high resolution models. Running extended simulations with high resolution models on current vector supercomputers will require computing power which is not available or prohibitively expensive. We have developed a parallel implementation suitable for running high resolution simulations. We studied performance issues such as the communication overhead and cache hit rate. Our experiments with grid partitioning and inter--processor communication techniques enabled us to obtain an efficient parallel implementation. Three grid partitioning techniques are evaluated. Two schemes to gather and scatter global grid data among processors are compared. A cache model to analyze performance is described.
机译:海洋模型已用于研究全球现象,例如厄尔尼诺南方涛动。厄尔尼诺现象的影响在世界范围内都感受到,对社会各阶层都至关重要。正在开发高分辨率海洋模型以运行更复杂的模拟。随着高分辨率模型的使用,对计算能力的需求预计将急剧增加。在当前的矢量超级计算机上使用高分辨率模型运行扩展的仿真将需要计算能力,而这是不可用的,或者价格过高。我们已经开发了适用于运行高分辨率仿真的并行实现。我们研究了性能问题,例如通信开销和缓存命中率。我们对网格划分和处理器间通信技术的实验使我们能够获得有效的并行实现。评估了三种网格划分技术。比较了两种在处理器之间收集和分散全局网格数据的方案。描述了一种用于分析性能的缓存模型。

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