Package: gpuinfo
Title: Lightweight Hardware and GPU Compute Detection
Version: 0.2.0
Authors@R: person("Stefano", "Cacciatore", role = c("aut", "cre"),
    email = "tkcaccia@gmail.com",
    comment = c(ORCID = "0000-0001-7052-7156"))
Description: Detects central processing unit topology, process-available cores,
    host and container memory, graphics processing unit hardware, and reports
    the apparent availability of 'CUDA', 'Metal', 'ROCm',
    and 'OpenCL' compute backends, with a read-only shared-library inventory for
    the 'CUDA' runtime, 'cuBLAS', 'cuFFT', 'cuSOLVER', 'cuRAND', and optional
    'NCCL' libraries. Detection uses operating-system information,
    documented platform interfaces, and optional command-line utilities,
    without requiring a GPU framework, 'Python', or a vendor software
    development kit. Backend interpretation follows the official 'CUDA'
    <https://docs.nvidia.com/cuda/cuda-driver-api/>, 'Metal'
    <https://developer.apple.com/documentation/metal>, 'ROCm'
    <https://rocm.docs.amd.com/>, and 'OpenCL'
    <https://registry.khronos.org/OpenCL/> documentation. 'NCCL' version
    inspection follows its documented API
    <https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/api/comms.html>.
    Process-level GPU memory samples, multi-device inventories, and versioned
    hardware manifests support reproducible benchmarks. Missing hardware,
    drivers, libraries, and utilities are handled safely.
License: MIT + file LICENSE
URL: https://github.com/tkcaccia/gpuinfo
BugReports: https://github.com/tkcaccia/gpuinfo/issues
Encoding: UTF-8
NeedsCompilation: yes
Depends: R (>= 3.6.0)
Suggests: jsonlite, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/roxygen2/version: 8.1.0
Packaged: 2026-10-14 10:57:57 UTC; stefano
Author: Stefano Cacciatore [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-7052-7156>)
Maintainer: Stefano Cacciatore <tkcaccia@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-14 14:12:07 UTC
