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R interface for RAPIDS cuML (<https://github.com/NVIDIA/cuml>), a suite of GPU-accelerated machine learning libraries powered by CUDA (<https://en.wikipedia.org/wiki/CUDA>).
| Version: | 0.4.0 |
| Depends: | R (≥ 4.1) |
| Imports: | bundle, digest, ellipsis, filelock, hardhat, jsonlite, Rcpp (≥ 1.0.6), rlang (≥ 0.3.0) |
| Suggests: | callr, glmnet, knitr, MASS, modeldata, palmerpenguins, parsnip, purrr, recipes, reticulate, rmarkdown, testthat (≥ 3.1.7), workflows, xgboost |
| OS_type: | unix |
| Published: | 2026-08-21 |
| DOI: | 10.32614/CRAN.package.cuda.ml |
| Author: | Yitao Li |
| Maintainer: | Tomasz Kalinowski <tomasz at posit.co> |
| BugReports: | https://github.com/mlverse/cuda.ml/issues |
| License: | MIT + file LICENSE |
| Copyright: | file inst/COPYRIGHTS cuda.ml copyright details |
| URL: | https://mlverse.github.io/cuda.ml/, https://github.com/mlverse/cuda.ml |
| NeedsCompilation: | no |
| SystemRequirements: | Native operations require Linux x86_64 with glibc 2.28 or newer. GPU-backed operations require a supported NVIDIA GPU and driver 580 or newer. |
| CRAN checks: | cuda.ml results |
| Reference manual: | cuda.ml.html , cuda.ml.pdf |
| Vignettes: |
Get started with cuda.ml (source, R code) Install and manage cuda.ml (source, R code) Save and restore models (source, R code) nvForest inference and deployment (source, R code) Use cuda.ml with tidymodels (source, R code) |
| Package source: | cuda.ml_0.4.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): cuda.ml_0.4.0.tgz, r-oldrel (arm64): cuda.ml_0.4.0.tgz, r-release (x86_64): cuda.ml_0.4.0.tgz, r-oldrel (x86_64): cuda.ml_0.4.0.tgz |
| Old sources: | cuda.ml archive |
Please use the canonical form https://CRAN.R-project.org/package=cuda.ml to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.