{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/5"}],"enrichment":{"capability":"Queries and monitors NVIDIA GPUs on a machine, providing a CLI and Python API to check availability, memory usage, and running processes, plus optional multi-node monitoring via REST agents.","skillfed_tags":["gpu-management","nvidia-tools","cluster-monitoring"],"use_cases":["Select an available GPU for a single training job before launching a framework to avoid memory conflicts.","Monitor GPU utilization and temperature across a cluster of machines via a web dashboard for capacity planning.","Query which GPUs are free and their memory state programmatically to implement custom job scheduling logic.","Display a colored table of all GPUs, their users, and running processes for quick status checks on a multi-user system."],"what_it_does":"nvgpu wraps nvidia-smi and NVIDIA's NVML library to provide a simpler interface for querying GPU state on multi-GPU machines. It solves the problem of selecting which GPU to use when multiple devices are available and frameworks would otherwise claim all memory, blocking other processes. The package offers both a command-line tool (nvgpu available, nvgpu list) and a Python API (nvgpu.available_gpus(), nvgpu.gpu_info()) to check memory usage, temperature, and running processes per device.\n\nIt also includes an optional distributed monitoring mode: agents on each node expose GPU status as JSON over REST, and a master node aggregates and displays the cluster status in a web dashboard. This is useful for coordinating GPU allocation across a cluster of machines. The package is marked Alpha and has been dormant since its latest release, so it may not be actively maintained or tested against recent driver and Python versions.","worth_installing":"Yes, if you have NVIDIA GPUs and need to programmatically select available devices or monitor a cluster\u2014but with caution. The package is dormant (last release 2023-03-30) and classifiers list Python 2 support, raising questions about compatibility with modern Python and driver versions. High install friction and no recent maintenance mean you should verify it works in your environment before relying on it in production."},"id":"nvgpu","links":{"html":"https://skillfed.io/packages/nvgpu","md":"https://skillfed.io/packages/nvgpu.md","pypi":"https://pypi.org/project/nvgpu/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-03-30","license_spdx":null,"license_treatment":"permissive","name":"nvgpu","python_support":"unspecified","summary":"NVIDIA GPU tools"},"popularity":{"monthly_downloads":87481,"position":13794,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.10.0"}