Parallel pruning for k-means clustering on shared memory architectures
Author
Gürsoy, Attila
Cengiz, Ilker
Date
2001Source Title
Euro-Par 2001 Parallel Processing
Print ISSN
0302-9743
Publisher
Springer Verlag
Volume
2150
Pages
321 - 325
Language
English
Type
Conference PaperItem Usage Stats
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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 algorithmsDistributed 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