KACU: k-means with hardware centroid-updating

Author

Liu, Wei-Chuan ; Huang, Jiun-Long ; Chen, Ming-Syan

Author_Institution

Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan

fYear

2005

fDate

15-16 Aug. 2005

Abstract

In this paper, we propose a framework, KACU (standing for k-means with hardware centroid updating), to enhance the speed of k-means clustering algorithm by integrating a hardware centroid updating mechanism into the procedure of continuous k-means algorithm. To facilitate performance measurement, KACU is implemented in a commercial field programmable gate array (abbreviated as FPGA) device. The experimental results show that KACU is able to achieve considerably higher performance.

Keywords

data mining; field programmable analogue arrays; pattern clustering; continuous k-means algorithm; field programmable gate array device; hardware centroid-updating; k-means clustering; Acceleration; Algorithm design and analysis; Clustering algorithms; Computer science; Data mining; Field programmable gate arrays; Hardware; Heuristic algorithms; Pipeline processing; Software algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Information Technology Conference, 2005.

Print_ISBN

0-7803-9328-7

Type

conf

DOI

10.1109/EITC.2005.1544347

Filename

1544347

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2580739