Parallel implementation of the greedy heuristic clustering algorithms

被引：2

作者：

Kazakovtsev, L. A. ^{[1
,2
]}

Rozhnov, I. P. ^{[1
]}

Popov, E. A. ^{[1
]}

Karaseva, M. V. ^{[1
,2
]}

Stupina, A. A. ^{[1
,2
]}

机构：

[1] Reshetnev Siberian State Univ Sci & Technol, 31 Krasnoyarskiy Rabochiy Ave, Krasnoyarsk 660031, Russia

[2] Siberian Fed Univ, 79 Svobodny Ave, Krasnoyarsk 660041, Russia

来源：

INTERNATIONAL WORKSHOP ADVANCED TECHNOLOGIES IN MATERIAL SCIENCE, MECHANICAL AND AUTOMATION ENGINEERING - MIP: ENGINEERING - 2019 | 2019年 / 537卷

关键词：

D O I：

10.1088/1757-899X/537/2/022052

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Authors propose parallel greedy heuristic k-means clustering algorithms for implementation on the graphical processing units (GPU) for solving large-scale problems. The computational experiments illustrate high performance of the GPUs in comparison with running the greedy heuristic algorithms on a central processor unit which is especially significant in the case of big datasets and bug numbers of clusters. The efficiency of the greedy heuristic algorithms in comparison with the standard k-means algorithm remains.

引用

页数：6

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