USE OF FPGA FOR REAL-TIME K-MEANS CLUSTERİNG ALGORITHM

Year 2019, Volume: 3 Issue: 3, 130 - 136, 28.09.2019

Muhammed Yıldırım , Ahmet Çınar

Abstract

Data mining is important
methods in the data processing step. Due to the fact that computer technologies
are becoming increasingly cheap and their power is increasing day by day, they
allow computers to store data in larger quantities [1]. Owing to the improving
of technology, many transactions are recorded in an electronic device and this
records can be safely stored. This data can easily be accessed when requested. By
means of developing technologies, it is ensured that these processes are
getting more day by day at a lower cost. Therefore, it is of great importance
to be able to process these data of high size. Clustering algorithms that
aggregate the data in the database under groups or clusters to bring together
objects with similar properties have a great deal of data mining proposition. In
this paper, it is aimed to collect 2 clusters based on the similarities of 60
data obtained from 2 different wheat varieties using k-means clustering
algorithm based on Fpga architecture. Since the FPGA architecture has the
ability to perform parallel processing, it will shorten the processing time and
so efficiency will increase. Also, the ability to use FPGA’s over and over
again provides an extra advantage. The proposed system is designed using the
verilog hardware identification language on the DE2_115 Fpga board.

Keywords

Data Mining, Fpga, K-means, Verilog

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