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2005
Springer

A Coarse Grained Parallel Algorithm for Closest Larger Ancestors in Trees with Applications to Single Link Clustering

9 years 2 months ago
A Coarse Grained Parallel Algorithm for Closest Larger Ancestors in Trees with Applications to Single Link Clustering
Hierarchical clustering methods are important in many data mining and pattern recognition tasks. In this paper we present an efficient coarse grained parallel algorithm for Single Link Clustering; a standard inter-cluster linkage metric. Our approach is to first describe algorithms for the Prefix Larger Integer Set and the Closest Larger Ancestor problems and then to show how these can be applied to solve the Single Link Clustering problem. In an extensive performance analysis on a Linux-based cluster an implementation of these algorithms has shows proven to scale well, exhibiting near linear relative speedup on up to twenty-four processors.
Albert Chan, Chunmei Gao, Andrew Rau-Chaplin
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where HPCC
Authors Albert Chan, Chunmei Gao, Andrew Rau-Chaplin
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