A hierarchical clustering algorithm for MIMD architecture.

Zhihua Du; Feng Lin

doi:10.1016/j.compbiolchem.2004.09.002

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A hierarchical clustering algorithm for MIMD architecture.

Zhihua Du·Feng Lin

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Abstract

Hierarchical clustering is the most often used method for grouping similar patterns of gene expression data. A fundamental problem with existing implementations of this clustering method is the inability to handle large data sets within a reasonable time and memory resources. We propose a parallelized algorithm of hierarchical clustering to solve this problem. Our implementation on a multiple instruction multiple data (MIMD) architecture shows considerable reduction in computational time and inter-node communication overhead, especially for large data sets. We use the standard message passing library, message passing interface (MPI) for any MIMD systems.

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Zhihua Du, Feng Lin. 2004. A hierarchical clustering algorithm for MIMD architecture.. https://doi.org/10.1016/j.compbiolchem.2004.09.002

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