Parallelization of K-medoid clustering algorithm

机译：K-medoid聚类算法的并行化

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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：本文提出了一种并行的K-medoid聚类算法。 K-medoid算法将分为多个任务，这些任务将被映射到多处理器系统中。提出了并行表达任务的控制结构和满足这些任务交互机制的通信模型。通过分解处理器之间的任务来构建数据并行模型。并行模型的实现和测试是在Linux OS环境下使用Fedora 11版本的SESE学术模拟器进行的。

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来源
《2013 5th International Conference on Information and Communication Technology for the Muslim World》|2013年|1-4|共4页
会议地点 Rabat(MA);Rabat(MA)
作者
Aljoby Walid; Alenezi Khaled;
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作者单位

Queen Arwa University, Yemenc;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Data parallel model; K-medoid; Parallel model; SIMD;

机译：数据并行模型; K-Medodi;并行模型; Sind;;

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机译：K-yemoid聚类算法的并行化
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机译：在多核处理器上并行化粗糙K-medoids聚类

Parallelization of K-medoid clustering algorithm

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