Package: gpuinfo 0.2.0

gpuinfo: Lightweight Hardware and GPU Compute Detection

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.

Authors:Stefano Cacciatore [aut, cre]