Survey of GPU Accelerated Data Clustering Algorithms
Journal Title: AJIT-e: Bilişim Teknolojileri Online Dergisi - Year 2013, Vol 4, Issue 11
Abstract
Data clustering algorithms are quite important for applications such as search; spam, attack detection; cell, gene, document analysis; analysis of conformations of molecular dynamics simulations. Many tools are developed for data clustering algorithms. However, today technology is improving rapidly so that collected data amount grows more and more. Although increased data amount affects the result of analysis positively, when current data clustering tools work with large scale datasets, they don't meet the requirements of such that applications in terms of speed. Data mining research community is interested in the rol of speed on data clustering for a while. Researchers take advantage of methods such as various optimization techniques, data structure designs, parallel techniques on CPU, using PC cluster systems. However, recently a new approach which offers low cost and high performance, attracts all attention: General Purpose GPU Programming: (GPGPU). Through high parallel computing power of GPUs and more rapid development of graphics carts than CPUs, it has become to benefit graphics carts, which design to do intensive mathematical computations, for general purpose programs. In this paper, we investigate works that increase performance of data clustering algorithms with GPGPU approach, summarize them, mention advantages and disadvantages of these works. In conclusion, considering the advantages of this approach, prospected areas in this matter that could contribute to the science are given and particular points in developing the application by GPGPU approach were exhibited from the outcomes of verified practices.
Authors and Affiliations
Nezire Çetin, Murat Hacıömeroğlu
Keywords
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- EP ID EP142788
- DOI 10.5824/1309‐1581.2013.2.002.x
- Views 72
- Downloads 0
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