Evolutionary clustering on CUDA

Abstract

Unsupervised clustering of large data sets is a complicated task. Due to its complexity, various meta-heuristic machine learning algorithms have been used to automate the clustering process. Genetic and evolutionary algorithms have been deployed to find clusters in data sets with success. The GPU computing is a recent programming paradigm introducing high performance parallel computing to general audience. This work presents an acceleration of a genetic algorithm for density based clustering on the GPU using the nVidia compute unified device architecture (CUDA).