A GPU-based interactive bio-inspired visual clustering

Abstract

In this work, we present an interactive visual clustering approach for the exploration and analysis of vast volumes of data. Our proposed approach is a bio-inspired collective behavioral model to be used in a 3D graphics environment. Our paper illustrates an extension of the behavioral model for clustering and a parallel implementation, using Compute Unified Device Architecture to exploit the computational power of Graphics Processor Units (GPUs). The advantage of our approach is that, as data enters the environment, the user is directly involved in the data mining process. Our experiments illustrate the effectiveness and efficiency provided by our approach when applied to a number of real and synthetic data sets.