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Fast Density-Based Clustering Using Graphics Processing Units
Woong-Kee LOH Yang-Sae MOON Young-Ho PARK
Publication
IEICE TRANSACTIONS on Information and Systems
Vol.E97-D
No.5
pp.1349-1352 Publication Date: 2014/05/01 Online ISSN: 1745-1361
DOI: 10.1587/transinf.E97.D.1349 Type of Manuscript: LETTER Category: Artificial Intelligence, Data Mining Keyword: density-based clustering, graphics processing units, grid structure,
Full Text: PDF>>
| Errata[Uploaded on July 1,2014]
Summary:
Due to the recent technical advances, GPUs are used for general applications as well as screen display. Many research results have been proposed to the performance of previous CPU-based algorithms by a few hundred times using the GPUs. In this paper, we propose a density-based clustering algorithm called GSCAN, which reduces the number of unnecessary distance computations using a grid structure. As a result of our experiments, GSCAN outperformed CUDA-DClust [2] and DBSCAN [3] by up to 13.9 and 32.6 times, respectively.
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