20、FPGA-Based Hardware Accelerators for K-Means Algorithm

FPGA-Based Hardware Accelerators for K-Means Algorithm

1. Introduction to K-Means Algorithm

K-Means is one of the most popular unsupervised learning algorithms used for clustering data points into a specified number of clusters. The algorithm works by minimizing the sum of squared distances between data points and their corresponding cluster centroids. Despite its simplicity, K-Means can be computationally intensive, especially when dealing with large datasets and high-dimensional data. This is where hardware acceleration using Field Programmable Gate Arrays (FPGA) comes into play.

Key Features of K-Means Algorithm:

• Iterative Process: K-Means iteratively assigns data points to clusters and recalculates centroids unti