In the last few years, the
Non-negative Matrix Factorization
(
NMF
) technique has gained a great interest among the Bioinformatics community, since it is able to extract interpretable parts from high-dimensional datasets. However, the computing time required to process large data matrices may become impractical, even for a parallel application running on a multiprocessors cluster.
%0 Journal Article
%1 MejAaRoa2015NMFmGPU
%A Mej\ Aa-Roa, Edgardo
%A Tabas-Madrid, Daniel
%A Setoain, Javier
%A Garc\ Aa, Carlos
%A Tirado, Francisco
%A Pascual-Montano, Alberto
%D 2015
%I BioMed Central Ltd
%J BMC Bioinformatics
%K gpu matrix-factorisation
%N 1
%P 43+
%R 10.1186/s12859-015-0485-4
%T NMF-mGPU: non-negative matrix factorization on multi-GPU systems
%U http://dx.doi.org/10.1186/s12859-015-0485-4
%V 16
%X In the last few years, the
Non-negative Matrix Factorization
(
NMF
) technique has gained a great interest among the Bioinformatics community, since it is able to extract interpretable parts from high-dimensional datasets. However, the computing time required to process large data matrices may become impractical, even for a parallel application running on a multiprocessors cluster.
@article{MejAaRoa2015NMFmGPU,
abstract = {In the last few years, the
Non-negative Matrix Factorization
(
{NMF}
) technique has gained a great interest among the Bioinformatics community, since it is able to extract interpretable parts from high-dimensional datasets. However, the computing time required to process large data matrices may become impractical, even for a parallel application running on a multiprocessors cluster.},
added-at = {2018-12-02T16:09:07.000+0100},
author = {Mej\ {A}a-Roa, Edgardo and Tabas-Madrid, Daniel and Setoain, Javier and Garc\ {A}a, Carlos and Tirado, Francisco and Pascual-Montano, Alberto},
biburl = {https://www.bibsonomy.org/bibtex/29c980d68e65cb5571627371f32b6af87/karthikraman},
citeulike-article-id = {13517218},
citeulike-linkout-0 = {http://dx.doi.org/10.1186/s12859-015-0485-4},
day = 13,
doi = {10.1186/s12859-015-0485-4},
interhash = {43f934679db45a469f52fe6b913a7fe7},
intrahash = {9c980d68e65cb5571627371f32b6af87},
issn = {1471-2105},
journal = {BMC Bioinformatics},
keywords = {gpu matrix-factorisation},
month = feb,
number = 1,
pages = {43+},
posted-at = {2015-04-15 10:09:14},
priority = {2},
publisher = {BioMed Central Ltd},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {{NMF}-{mGPU}: non-negative matrix factorization on {multi-GPU} systems},
url = {http://dx.doi.org/10.1186/s12859-015-0485-4},
volume = 16,
year = 2015
}