A GPU-based method for computing eigenvector centrality of gene-expression networks

Title: A GPU-based method for computing eigenvector centrality of gene-expression networks
Creator: Arefin, Ahmed Shamsul; Berretta, Regina; Moscato, Pablo
Relation: The 11th Australasian Symposium on Parallel and Distributed Computing (AusPDC 2013). Proceedings of the Eleventh Australasian Symposium on Parallel and Distributed Computing (AusPDC 2013) (Adelaide, S.A. 29 January-1 February, 2013) p. 3-11
Relation: http://dl.acm.org/citation.cfm?id=2525513&CFID=474031479&CFTOKEN=96698675
Publisher: ACM Digital Library
Resource Type: conference paper
Date: 2013
Description: In this paper, we present a fast and scalable method for computing eigenvector centrality using graphics processing units (GPUs). The method is designed to compute the centrality on gene-expression networks, where the network is pre-constructed in the form of kNN graphs from DNA microarray data sets.
Subject: eigenvector; centrality; kNN; CUDA
Identifier: http://hdl.handle.net/1959.13/1057795
Identifier: uon:16267
Identifier: ISBN:9781921770258
Language: eng
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