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GPU Accelerated PK-means Algorithm for Gene Clustering

Wuchao Situ, Yau-King Lam, Yi Xiao, P.W.M. Tsang, Chi-Sing Leung
Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
The 2011 International Conference on Bioinformatics & Computational Biology (BIOCOMP’11), 2011

@article{situ2011gpu,

   title={GPU Accelerated PK-means Algorithm for Gene Clustering},

   author={Situ, W. and Lam, Y.K. and Xiao, Y. and Tsang, PWM and Leung, C.S.},

   year={2011}

}

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In this paper, a novel GPU accelerated scheme for the PK-means gene clustering algorithm is proposed. According to the native particle-pair structure of the PKmeans algorithm, a fragment shader program is tailor-made to process a pair of particles in one pass for the computationintensive portion. As the output channel of a fragment consisting of 4 floating-point values is fully utilized, overhead for each data points in searching for its nearest centroid throughout the particle-pair is reduced. Experimental evaluations on three popular gene expression datasets show that the proposed GPU accelerated scheme can attain an order of magnitude speedup as compared with the original PK-means algorithm.
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