Title :
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
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;
Conference_Titel :
Emerging Information Technology Conference, 2005.
Print_ISBN :
0-7803-9328-7
DOI :
10.1109/EITC.2005.1544347
