Multi-core for k-means clustering on FPGA

In this paper, a configurable many-core hardware/ software architecture is proposed to efficiently execute the widely known and commonly used K-means clustering algorithm. A prototype was designed and implemented on a Xilinx Zynq- 7000 All Programmable SoC. A single core configured with the slowest configuration achieves a 10X speed-up compared to the software only solution. The system is fully scalable and capable of achieving much higher speed-ups by increasing its parallelism