Design of a hardware accelerator for density based clustering applications

Data mining is beginning to be widely used in various application fields. Density based clustering algorithms perform data mining by grouping high-density regions of points to form clusters. In recent years, the data sizes and the problem complexity of this algorithm have increased significantly leading to slower execution of the applications. Faster engines that perform the application tasks quickly and efficiently are the need of the hour. In this paper, we propose a hardware accelerator for density based clustering applications. This accelerator improves the execution speed of the core kernels of this application, which include density calculation and the migration of points to denser regions. We show that this accelerator when integrated with general purpose processors, speed up the kernel execution times by at least 300X.