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.
| Version: | 0.2.5.2 |
| Depends: | R (≥ 3.1.0) |
| Imports: | Rcpp (≥ 0.11.4), Matrix, SparseM, stats, stringr, tools, utils |
| LinkingTo: | Rcpp |
| Suggests: | gdata |
| Published: | 2016-10-17 |
| Author: | Sven Koitka [aut, cre, cph], Christoph M. Friedrich [ctb] |
| Maintainer: | Sven Koitka <sven.koitka at fh-dortmund.de> |
| BugReports: | https://github.com/razorx89/nmfgpu4R/issues |
| License: | GPL-3 | file LICENSE |
| URL: | https://github.com/razorx89/nmfgpu4R |
| NeedsCompilation: | yes |
| SystemRequirements: | CUDA >= v7.0, Nvidia GPU (e.g. GeForce or Tesla) with compute capability >= 3.0 (Kepler) |
| CRAN checks: | nmfgpu4R results |
| Reference manual: | nmfgpu4R.pdf |
| Package source: | nmfgpu4R_0.2.5.2.tar.gz |
| Windows binaries: | r-devel: nmfgpu4R_0.2.5.2.zip, r-release: nmfgpu4R_0.2.5.2.zip, r-oldrel: nmfgpu4R_0.2.5.2.zip |
| macOS binaries: | r-release: nmfgpu4R_0.2.5.2.tgz, r-oldrel: nmfgpu4R_0.2.5.2.tgz |
| Old sources: | nmfgpu4R archive |
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