Parallel Algorithms for Hierarchical Clustering and Cluster Validity

Parallel algorithms on SIMD (single-instruction stream multiple-data stream) machines for hierarchical clustering and cluster validity computation are proposed. The machine model uses a parallel memory system and an alignment network to facilitate parallel access to both pattern matrix and proximity matrix. For a problem with N patterns, the number of memory accesses is reduced from O(N/sup 3/) on a sequential machine to O(N/sup 2/) on an SIMD machine with N PEs. >

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