This package provides R interfaces to a handful of common statistical algorithms. These algorithms are implemented in parallel using a mixture of Nvidia's CUDA langauge, Nvidia's CUBLAS library, and EMI Photonics' CULA libraries. On a computer equiped with an Nvidia GPU some of these functions may be substantially more efficient than native R routines. Thanks to Craig Stark at UC Irvine for donating time on his lab's Mac hardware.
| Version: | 0.26 |
| Depends: | R (≥ 2.8.0) |
| Published: | 2011-11-03 |
| Author: | Josh Buckner, Mark Seligman, Justin Wilson |
| Maintainer: | Josh Buckner <bucknerj at umich.edu> |
| License: | GPL-3 |
| URL: | http://brainarray.mbni.med.umich.edu/Brainarray/Rgpgpu |
| SystemRequirements: | Nvidia's CUDA toolkit (>= release 2.3) |
| Installation: | gputools installation info |
| In views: | HighPerformanceComputing |
| CRAN checks: | gputools results |
| Package source: | gputools_0.26.tar.gz |
| MacOS X binary: | not available, see check log. |
| Windows binary: | not available, see ReadMe. |
| Reference manual: | gputools.pdf |
| News/ChangeLog: | NEWS |
| Old sources: | gputools archive |
| Reverse suggests: | gcbd |