Clustering on GPU – A Brief Survey

V.Saveetha, S.Sophia, V.Anusha Sowbarnika
Info Institute of Engineering
Research Journal of Computer Systems Engineering (RJCSE), Vol 04, Special Issue, 2013



   author={Saveetha, V and Sophia, S and Sowbarnika, V Anusha},



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Clustering, as a process of partitioning data elements with similar properties, is an essential task in many application areas. Due to technological advances, the amount as well as the dimensionality of data sets in general is steadily growing. Graphics Processing Units in today’s desktops can be thought of as a high performance parallel processor. As major advantage GPUs provide extremely high parallelism combined with a high bandwidth in memory transfer at low cost. Each single processor within the GPU is able to execute different tasks independently but concurrently. Such computational capabilities of the GPU are being exploited in the domain of Data Clustering. The compute unified device architecture (CUDA) is a framework for scientific general purpose computing on NVIDIA GPUs. This survey tries to introduce the different clustering techniques implemented using GPU’s.
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