Non-Negative Matrix Factorization (NMF) using CUDA

Wrapper package for the nmfgpu library, which implements several Non-negative Matrix Factorization (NMF) algorithms for CUDA platforms. By using the acceleration of GPGPU computing, the NMF can be used for real-world problems inside the R environment. All CUDA devices starting with Kepler architecture are supported by the library.


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Reference manual

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install.packages("nmfgpu4R")

0.2.5.2 by Sven Koitka, 2 years ago


https://github.com/razorx89/nmfgpu4R


Report a bug at https://github.com/razorx89/nmfgpu4R/issues


Browse source code at https://github.com/cran/nmfgpu4R


Authors: Sven Koitka [aut, cre, cph] , Christoph M. Friedrich [ctb]


Documentation:   PDF Manual  


GPL-3 | file LICENSE license


Imports Rcpp, Matrix, SparseM, stats, stringr, tools, utils

Suggests gdata

Linking to Rcpp

System requirements: CUDA >= v7.0, Nvidia GPU (e.g. GeForce or Tesla) with compute capability >= 3.0 (Kepler)


See at CRAN