26th IEEE Signal Processing and Communications Applications Conference (SIU), İzmir, Türkiye, 2 - 05 Mayıs 2018
K-means algorithm is one of the clustering algorithms that increase in popularity day by day. The intensive mathematical operations and the continuous increase of the data size while clustering on large data using the K-means algorithm prevent the algorithm from operating at high performance. Therefore, the K-means algorithm that works on large data needs to be implemented on very fast hardware. FPGAs capable of parallel processing can be mathematically processed much faster than traditional processors. Therefore, realization of algorithms that require intensive mathematical computations such as K-means using FPGAs is of great importance for the performance of applications.