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@@ -14,9 +14,47 @@ The GPU Operator allows administrators of Kubernetes clusters to manage GPU node
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Note that the GPU Operator is specifically useful for scenarios where the Kubernetes cluster needs to scale quickly - for example provisioning additional GPU nodes on the cloud or on-prem and managing the lifecycle of the underlying software components. Since the GPU Operator runs everything as containers including NVIDIA drivers, the administrators can easily swap various components - simply by starting or stopping containers.
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## Quick Start
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This section provides a quick guide for deploying the GPU Operator with the data center driver.
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Make sure your Kubernetes cluster meets the [prerequisites](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/getting-started.html#prerequisites) and is listed on the [platform support page](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/platform-support.html#supported-operating-systems-and-kubernetes-platforms).
After installation, the GPU Operator and its operands should be up and running.
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Note:
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To deploy the GPU Operator on OpenShift, follow the instructions in the [official documentation](https://docs.nvidia.com/datacenter/cloud-native/openshift/latest/steps-overview.html).
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## Product Documentation
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For information on platform support and getting started, visit the official documentation [repository](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/overview.html).
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## Roadmap
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- Support the latest NVIDIA Data Center GPUs, systems, and drivers.
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- Support RHEL 10.
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- Support KubeVirt with Ubuntu 24.04.
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- Promote the [NVIDIADriver](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/gpu-driver-configuration.html) CRD to General Availability (GA).
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- Integrate [NVIDIA’s DRA Driver for GPUs](https://github.com/NVIDIA/k8s-dra-driver-gpu) as a managed component of the GPU Operator.
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## Webinar
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[How to easily use GPUs on Kubernetes](https://info.nvidia.com/how-to-use-gpus-on-kubernetes-webinar.html)
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