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Optimization of the Communications between Processors in a General Parallel Computing Approach Using the Selected Data Technique

机译:使用所选数据技术的通用并行计算方法中处理器之间的通信优化

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A large variety of problems that are out of reach of single processor computer capabilities. Many approaches are offered today to get round this. Each of these has its own strengths and weaknesses : a compromise has to be found. We will introduce a general parallel computing method for engineering problems dedicated to all users. We have searched an easy method for code development. A technique of data selection (Selected Data Technique - SDT) is used for the determination of the data dedicated to each processor. Several problems associated with the communication times are posed and solutions are proposed in accordance with the number of processors. This method is applied to very large CPU cost problems, particularly the unsteady problems or steady problems using an iterative method. So the domain of potential applications is very wide. The SDT-parallelization is performed by an expert system called AMS (Automatic Multi-grid System) included in the software. This new concept is a natural way for the standardization of parallel codes. An example is presented hereafter.
机译:单处理器计算机功能无法解决的许多问题。今天提供了许多方法来解决这个问题。这些中的每一个都有其优点和缺点:必须找到一个折衷方案。我们将针对所有用户介绍针对工程问题的通用并行计算方法。我们搜索了一种简单的代码开发方法。数据选择技术(Selected Data Technique-SDT)用于确定每个处理器专用的数据。提出了与通信时间有关的几个问题,并根据处理器的数量提出了解决方案。此方法适用于非常大的CPU成本问题,尤其是使用迭代方法的不稳定问题或稳定问题。因此,潜在的应用领域非常广泛。 SDT并行化由软件中包含的称为AMS(自动多网格系统)的专家系统执行。这个新概念是并行代码标准化的自然方法。此后给出一个例子。

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