An parallel hierarchical clustering algorithm based on SIMD-EREW

Hierarchial clustering technology plays a very important role in image processing, intrusion detection and bioinformatics applications, which is one of the most extensively studied branch in data mining. Presently the parallel hierarchical algorithms based on SIMD can not process memory conflicts among different processors. To overcome this shortcomings, a new parallel algorithm based on minimum spanning tree is proposed in this paper.The proposed algorithms can cluster n objects with O(p) processors in O(n²/p) time, Performance comparisons show that it is the first parallel hierarchical clustering algorithm algorithms without memory conflicts, and thus it is an improved result over the past researches.