Parallelization of K-Means Clustering Algorithm for Data Mining

Parallelization of K-Means Clustering Algorithm for Data Mining

In this paper, we studied the parallelization of K-Means clustering algorithm, proposed a parallel scheme, designed a corresponding algorithm, and implemented the algorithm in GPU environment. The experimental result shows that the GPU-based parallelization algorithm has a good acceleration effect c...

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Main Authors: Jiang Hao, Yu Liyan
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:ITM Web of Conferences
Online Access:https://doi.org/10.1051/itmconf/20171203048
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spelling doaj-e6208cf5c2d74423998da12295e8c3fe2021-02-02T00:45:37ZengEDP SciencesITM Web of Conferences2271-20972017-01-01120304810.1051/itmconf/20171203048itmconf_ita2017_03048Parallelization of K-Means Clustering Algorithm for Data MiningJiang HaoYu LiyanIn this paper, we studied the parallelization of K-Means clustering algorithm, proposed a parallel scheme, designed a corresponding algorithm, and implemented the algorithm in GPU environment. The experimental result shows that the GPU-based parallelization algorithm has a good acceleration effect compared with the CPU-based serialization algorithm.https://doi.org/10.1051/itmconf/20171203048
collection DOAJ
language English
format Article
sources DOAJ
author Jiang Hao
Yu Liyan
spellingShingle Jiang Hao
Yu Liyan
Parallelization of K-Means Clustering Algorithm for Data Mining
ITM Web of Conferences
author_facet Jiang Hao
Yu Liyan
author_sort Jiang Hao
title Parallelization of K-Means Clustering Algorithm for Data Mining
title_short Parallelization of K-Means Clustering Algorithm for Data Mining
title_full Parallelization of K-Means Clustering Algorithm for Data Mining
title_fullStr Parallelization of K-Means Clustering Algorithm for Data Mining
title_full_unstemmed Parallelization of K-Means Clustering Algorithm for Data Mining
title_sort parallelization of k-means clustering algorithm for data mining
publisher EDP Sciences
series ITM Web of Conferences
issn 2271-2097
publishDate 2017-01-01
description In this paper, we studied the parallelization of K-Means clustering algorithm, proposed a parallel scheme, designed a corresponding algorithm, and implemented the algorithm in GPU environment. The experimental result shows that the GPU-based parallelization algorithm has a good acceleration effect compared with the CPU-based serialization algorithm.
url https://doi.org/10.1051/itmconf/20171203048
work_keys_str_mv AT jianghao parallelizationofkmeansclusteringalgorithmfordatamining
AT yuliyan parallelizationofkmeansclusteringalgorithmfordatamining
_version_ 1724313133798916096

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