NDLI: Online accelarated implementation of the Fuzzy C-means algorithm with the use of the GPU platform

Content Provider	IEEE Xplore Digital Library
Author	Srikanthan, S. Krishnan, V. Kumar, A.
Copyright Year	2011
Description	Author affiliation: Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology, Allahabad, India (Kumar, A.) \|\| BrahMos Aerospace Private, Limited, Delhi, India (Srikanthan, S.) \|\| Department of Electronics and Communication Engineering, SSN College of Engineering, Chennai, India (Krishnan, V.)
Abstract	Fuzzy C-means is a very widely covered topic in literature. It is a very successful clustering method whose subtle variations are involved in various clustering related applications. Despite its success, it shares a disadvantage with almost all of its contemporary pattern discovery algorithms — computational complexity. With the explosion in multimedia data over the internet and growing storage systems, there is a lot of research done in content based data retrieval. Fuzzy C-means is an integral part of this goal but its innate complexity makes it a strictly offline algorithm. Online pattern discovery is the need of the hour and our paper aims to address this issue without the use of powerful servers for implementing Fuzzy C-Means (FCM). We aim at accelerating the algorithm using Graphical Processing Units (GPUs), which are basically graphic cards common in desktop computers. We aim at restructuring the algorithm in a manner in which maximum data parallelism could be extracted thus utilizing the resources of the GPU to the fullest extent. In this paper we compare the speed of our approach using a NVIDIA Tesla C1060 GPU to that of sequential versions running on an Intel Xeon 2.93 GHz and an Intel Dual Core 2GHz.
Starting Page	385
Ending Page	388
File Size	644679
Page Count	4
File Format	PDF
ISBN	9781457713859
e-ISBN	9781457713866
DOI	10.1109/ICCCT.2011.6075148
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-15
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Unsupervised pattern discovery Clustering algorithms Signal processing algorithms Speech recognition Parallel processing Vectors Optimization Graphics processing unit
Content Type	Text
Resource Type	Article

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