FPGA vhdl k-mean clustering algorithm code on zynq board

Description: Create a Hardware-Software Codesign version of the k-mean clustering algorithm K-means clustering is a popular data mining algorithm that partitions n samples into k clusters (note: the k-nearest neighbor classifier algorithm used in machine learning can leverage the cluster centers produced by the k-means clustering algorithm). The problem is in general NP-hard but heuristic algorithms have been developed that quickly converge to a local optimum solution. We will consider one of those algorithms in this project. I have provided a C code version of the k-means clustering algorithm, and a Vivado block diagram and memory layout (explained below) that you will use as a starting point. You will need to study the C version and then decide which components to implement as a VHDL module using the BRAM (you also used BRAM in HISTO lab0).