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Parallelization of K-medoid clustering algorithm

机译:K-yemoid聚类算法的并行化

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摘要

This paper presents an approach for paralleling K-medoid clustering algorithm. The K-medoid algorithm will be divided into tasks, which will be mapped into multiprocessor system. The control structure for the way of expressing the tasks in parallel form and the communication model that satisfied the mechanism for interaction between these tasks is presented. Data parallel model is built by decomposing the tasks among the processors. The implementation and testing of the parallel model have conducted using SESE academic simulator under Fedora 11 version at Linux OS environment.
机译:本文介绍了一种平行k-yemoid聚类算法的方法。 K-METOID算法将分为任务,该任务将被映射到多处理器系统中。 呈现以并行形式表达任务的方式和满足这些任务之间的交互机制的通信模型的控制结构。 数据并行模型是通过分解处理器之间的任务来构建的构建。 并行模型的实施和测试在Linux OS环境下在Fedora 11版本下使用Sese Academic Simulator进行了。

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