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cuda.ml: R Interface for the RAPIDS cuML Suite of Libraries

R interface for RAPIDS cuML (<https://github.com/rapidsai/cuml>), a suite of GPU-accelerated machine learning libraries powered by CUDA (<https://en.wikipedia.org/wiki/CUDA>).

Version: 0.3.2
Depends: R (≥ 3.2)
Imports: ellipsis, hardhat, parsnip, Rcpp (≥ 1.0.6), rlang (≥ 0.1.4)
LinkingTo: Rcpp
Suggests: callr, glmnet, MASS, magrittr, mlbench, purrr, reticulate, testthat, xgboost
OS_type: unix
Published: 2022-01-08
Author: Yitao Li ORCID iD [aut, cph], Tomasz Kalinowski [cph, ctb], Daniel Falbel [aut, cre, cph], RStudio [cph, fnd]
Maintainer: Daniel Falbel <daniel at rstudio.com>
BugReports: https://github.com/mlverse/cuda.ml/issues
License: MIT + file LICENSE
URL: https://mlverse.github.io/cuda.ml/
NeedsCompilation: yes
SystemRequirements: RAPIDS cuML (see https://rapids.ai/start.html)
CRAN checks: cuda.ml results

Documentation:

Reference manual: cuda.ml.pdf

Downloads:

Package source: cuda.ml_0.3.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): cuda.ml_0.3.2.tgz, r-oldrel (arm64): cuda.ml_0.3.2.tgz, r-release (x86_64): cuda.ml_0.3.2.tgz, r-oldrel (x86_64): cuda.ml_0.3.2.tgz
Old sources: cuda.ml archive

Linking:

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.
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