Lightweight 'CUDA' Numerical Computing R package cudaverse version 0.4.1 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. Software Imports: Matrix, methods, stats Suggests: igraph (>= 2.0.0), knitr, rmarkdown, RSpectra, Rtsne, S4Vectors, SingleCellExperiment, testthat (>= 3.0.0), torch, uwot Yaoxiang Li <liyaoxiang@outlook.com> Comprehensive R Archive Network (CRAN) Yaoxiang Li [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=cudaverse/LICENSE) 2026-09-10 application/tgz https://CRAN.R-project.org/package=cudaverse doi:10.32614/CRAN.package.cudaverse en-US