Pardicle: Parallel Approximate Density-Based Clustering

Abstract

Dbscan is a widely used isodensity-based clustering algorithm for particle data well-known for its ability to isolate arbitrarily-shaped clusters and to filter noise data. The algorithm is super-linear (<i>O</i>(<i>nlogn</i>)) and computationally expensive for large datasets. Given the need for speed, we propose a fast heuristic algorithm for Dbscan using… (More)
DOI: 10.1109/SC.2014.51

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Cite this paper

@article{Patwary2014PardiclePA, title={Pardicle: Parallel Approximate Density-Based Clustering}, author={Md. Mostofa Ali Patwary and Nadathur Satish and Narayanan Sundaram and Fredrik Manne and Salman Habib and Pradeep Dubey}, journal={SC14: International Conference for High Performance Computing, Networking, Storage and Analysis}, year={2014}, pages={560-571} }