A general framework for utilizing R to harness the power of NVIDIA GPU's. The "gmatrix" and "gvector" classes allow for easy management of the separate device and host memory spaces. Numerous numerical operations are implemented for these objects on the GPU. These operations include matrix multiplication, addition, subtraction, the kronecker product, the outer product, comparison operators, logical operators, trigonometric functions, indexing, sorting, random number generation and many more.
| Version: | 0.3 |
| Depends: | methods, stats |
| OS_type: | unix |
| Published: | 2015-12-01 |
| Author: | Nathan Morris |
| Maintainer: | Nathan Morris <njm18 at case.edu> |
| License: | GPL-3 | file LICENSE |
| URL: | https://github.com/njm18/gmatrix |
| NeedsCompilation: | yes |
| SystemRequirements: | Nvidia's CUDA toolkit (>= release 5.0) and Nvidia GPU with compute capibility >=2.0 |
| Materials: | README |
| In views: | HighPerformanceComputing |
| CRAN checks: | gmatrix results |
| Reference manual: | gmatrix.pdf |
| Package source: | gmatrix_0.3.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| OS X El Capitan binaries: | r-release: not available |
| OS X Mavericks binaries: | r-oldrel: not available |
| Old sources: | gmatrix archive |
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