Study on Parallel Clustering Based on Asynchronous Communication

Yinghui Zhu, Yuzhen Jiang, Bo Liu
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Abstract

In order to improve the speed of clustering data mining, aiming at the characteristics of BIRCH algorithm, this paper has done research and analysis on rapid clustering data mining in the cluster system, and presented several improvement suggestions such as using data parallel thinking, uniform data distribution strategy , clustering communication mode and the optimization of clustering results. Experiment results show that the paralleling algorithm using asynchronous communication can achieve better performance and speedup than that synchronous one.
基于异步通信的并行聚类研究
为了提高聚类数据挖掘的速度,本文针对BIRCH算法的特点,对聚类系统中的快速聚类数据挖掘进行了研究和分析,提出了采用数据并行思维、统一数据分布策略、聚类通信模式和优化聚类结果等改进建议。实验结果表明,采用异步通信的并行算法比采用同步通信的并行算法性能更好,速度更快。
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