NVIDIA GPU Operator

NGC Catalog

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Features

Description

Deploy and Manage NVIDIA GPU resources in Kubernetes.

Publisher

NVIDIA

Latest Tag

v24.9.0

Modified

November 7, 2024

Compressed Size

207.03 MB

Multinode Support

Multi-Arch Support

Yes

v24.9.0 (Latest) Security Scan Results

Linux / amd64

Linux / arm64

The NVIDIA GPU Operator manages NVIDIA GPU resources in a Kubernetes cluster and automates tasks related to bootstrapping GPU nodes. Since the GPU is a special resource in the cluster, it requires a few components to be installed before application workloads can be deployed onto the GPU. These components include the NVIDIA drivers (to enable CUDA), Kubernetes device plugin, container runtime and others such as automatic node labelling, monitoring and more.

A Helm chart is provided for easily deploying the GPU operator in a cluster to provision the NVIDIA software on GPU-enabled nodes.

Need enterprise support? NVIDIA global support is available for NVIDIA GPU Operator with the NVIDIA AI Enterprise software suite. Check out NVIDIA LaunchPad for free access to a of hands-on lab with the NVIDIA GPU Operator on NVIDIA infrastructure.

Usage

For information on platform support and getting started, visit the official documentation repository.

License Agreements

The NVIDIA GPU Operator source code is is licensed under Apache 2.0 and contributions are accepted with a DCO. See the contributing document for more information on how to contribute and the release artifacts.

An End User License Agreement is included with this product. By pulling and using the containers from NGC, you accept the terms and conditions of this license.

The NVIDIA GPU Operator includes components governed by the following NVIDIA End User License Agreements. By installing and using the GPU Operator, you accept the terms and conditions of these licenses.

NVIDIA Driver The license for the NVIDIA datacenter drivers is available at this link.
NVIDIA Data Center GPU Manager (DCGM) The license for the NVIDIA DCGM is available on the product page.

Since the underlying images may include components licensed under open-source licenses such as GPL, the sources for these components are archived on the CUDA opensource index.