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      • Department of Computer Engineering
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      Parallel pruning for k-means clustering on shared memory architectures

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      Author
      Gürsoy, Attila
      Cengiz, Ilker
      Date
      2001
      Source Title
      Euro-Par 2001 Parallel Processing
      Print ISSN
      0302-9743
      Publisher
      Springer Verlag
      Volume
      2150
      Pages
      321 - 325
      Language
      English
      Type
      Conference Paper
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      Abstract
      We have developed and evaluated two parallelization schemes for a tree-based k-means clustering method on shared memory machines. One scheme is to partition the pattern space across processors. We have determined that spatial decomposition of patterns outperforms random decomposition even though random decomposition has almost no load imbalance problem. The other scheme is the parallel traverse of the search tree. This approach solves the load imbalance problem and performs slightly better than the spatial decomposition, but the efficiency is reduced due to thread synchronizations. In both cases, parallel treebased k-means clustering is significantly faster than the direct parallel k-means. © Springer-Verlag Berlin Heidelberg 2001.
      Keywords
      Clustering algorithms
      Distributed computer systems
      Parallel architectures
      K-means clustering
      K-means clustering method
      Parallelizations
      Random decomposition
      Shared memory architecture
      Shared memory machines
      Spatial decompositions
      Thread synchronization
      Memory architecture
      Permalink
      http://hdl.handle.net/11693/27617
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