Package: gputools
Version: 2.1.0
Title: GPU Drop-Ins for Statistics on Wide Data
Authors@R: c(person("Josh", "Buckner", email = "nullsatz@gmail.com",
                    role = c("aut", "cre")),
  person("Mark", "Seligman", email = "mseligman@suiji.org", role = "aut"),
  person("Fan", "Meng", email = "mengf@umich.edu", role = "aut"),
  person("Justin", "Wilson", role = "ctb"))
Depends: R (>= 4.0.0)
Imports: utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr
SystemRequirements: NVIDIA CUDA toolkit (>= 11.7); an NVIDIA GPU to run
        the GPU functions
Description: GPU versions of base R statistics for data with many
    variables, using the NVIDIA 'CUDA' toolkit: correlation matrices
    (Pearson, Spearman and Kendall) and their tests, the strongest
    correlated pairs among tens of thousands of variables without forming
    the matrix, association scans with covariates as in expression
    quantitative trait loci studies (Shabalin 2012
    <doi:10.1093/bioinformatics/bts163>), permutation tests with
    Westfall-Young maxT adjustment, distance matrices, hierarchical and
    k-means clustering, Granger causality tests, B-spline mutual
    information, principal components, and least-squares fits. Results
    agree with the base R functions they replace. Without 'CUDA' the
    package installs, and its functions explain how to get a 'CUDA' build.
    Described in Buckner et al. (2010) <doi:10.1093/bioinformatics/btp608>.
License: GPL-3
URL: https://github.com/nullsatz/gputools
BugReports: https://github.com/nullsatz/gputools/issues
NeedsCompilation: yes
Packaged: 2026-10-15 21:21:49 UTC; josh
Author: Josh Buckner [aut, cre],
  Mark Seligman [aut],
  Fan Meng [aut],
  Justin Wilson [ctb]
Maintainer: Josh Buckner <nullsatz@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:40:02 UTC
Built: R 4.5.2; x86_64-apple-darwin20; 2026-10-24 17:53:13 UTC; unix
Archs: gputools.so.dSYM
