Package: cudaverse
Title: Lightweight 'CUDA' Numerical Computing
Version: 0.4.1
Authors@R: 
    person("Yaoxiang", "Li", email = "liyaoxiang@outlook.com",
           role = c("aut", "cre"))
Description: Provides a lightweight interface to graphics processing unit
    (GPU)-accelerated numerical computing using 'CUDA'. Dense tensors, sparse
    matrices, decompositions, distances, exact nearest neighbours, clustering,
    graph workflows, and embeddings share one consistent interface. The native
    backend discovers the 'NVIDIA CUDA Driver API', 'cuBLAS', and 'cuSOLVER'
    libraries at runtime without bundling 'LibTorch' or the 'CUDA Runtime'.
    Stage-level provenance records the backend, device, and data transfers used
    by each result. A portable implementation supports package validation on
    systems without 'CUDA'. Background for the included Leiden community
    detection and uniform manifold approximation and projection methods is given
    by Traag, Waltman and van Eck (2019)
    <doi:10.1038/s41598-019-41695-z> and McInnes et al. (2018)
    <doi:10.21105/joss.00861>, respectively.
License: MIT + file LICENSE
URL: https://cudaverse.github.io/cudaverse/,
        https://github.com/cudaverse/cudaverse
BugReports: https://github.com/cudaverse/cudaverse/issues
Encoding: UTF-8
Language: en-US
Imports: Matrix, methods, stats
Suggests: igraph (>= 2.0.0), knitr, rmarkdown, RSpectra, Rtsne,
        S4Vectors, SingleCellExperiment, testthat (>= 3.0.0), torch,
        uwot
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/roxygen2/version: 8.0.0
SystemRequirements: For GPU execution on Windows or Linux: NVIDIA
        CUDA-capable GPU, NVIDIA driver with CUDA Driver API, NVIDIA
        cuBLAS 12, and NVIDIA cuSOLVER 11
NeedsCompilation: yes
Packaged: 2026-08-29 06:34:48 UTC; Li
Author: Yaoxiang Li [aut, cre]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-10 09:30:02 UTC
