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Efficient Execution on Long-Distance Geographically Distributed Dedicated Clusters

机译:高距离地理上分布专用集群的高效执行

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Joining, through Internet, geographically distributed dedicated heterogeneous clusters of workstations can be an inexpensive approach to achieve data-intensive computation. This paper describes a master/worker based system architecture and the strategies used to obtain effective collaboration in such a collection of clusters. Based on this architecture an analytical model was built to predict and tune applications' execution performance and behaviour over time This architecture and model were employed for the matrix multiplication algorithm over two heterogeneous clusters, one in Brazil and the other in Spain. Our approach results show that the model reaches 94% prediction, achieving 91% of the clusters' total performance.
机译:加入,通过互联网,地理分布的专用工作站的非均质集群可以是实现数据密集型计算的廉价方法。 本文介绍了基于主/工人的系统架构和用于在此类集群集群中获取有效协作的策略。 基于该架构,建立了一个分析模型,以预测和调整应用程序的执行性能和行为随着时间的推移,这种体系结构和模型用于两个异构群中的矩阵乘法算法,一个在西班牙的巴西和另一个在巴西。 我们的方法结果表明,该模型的预测达到了94%,实现了91%的集群总业绩。

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