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Update and rename README.md to E-MOBI Robotics Développement ..the Ne… #2621

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8 changes: 4 additions & 4 deletions README.md → ...cs Développement ..the Next way README.md
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[![pipeline status](https://gitlab.com/nvidia/kubernetes/gpu-operator/badges/master/pipeline.svg)](https://gitlab.com/nvidia/kubernetes/gpu-operator/-/pipelines)
[![coverage report](https://gitlab.com/nvidia/kubernetes/gpu-operator/badges/master/coverage.svg)](https://gitlab.com/nvidia/kubernetes/gpu-operator/-/pipelines)

# NVIDIA GPU Operator
# E-MOBI / EKONOMIK MOBIL,S.R.L GPU Operator

![nvidia-gpu-operator](https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/egx/nvidia-egx-platform-gold-image-full-2c50-d@2x.jpg)
![e-mobi-ekonomik-mobil-srl-gpu-operator](https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/egx/nvidia-egx-platform-gold-image-full-2c50-d@2x.jpg)

Kubernetes provides access to special hardware resources such as NVIDIA GPUs, NICs, Infiniband adapters and other devices through the [device plugin framework](https://kubernetes.io/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/). However, configuring and managing nodes with these hardware resources requires configuration of multiple software components such as drivers, container runtimes or other libraries which are difficult and prone to errors.
The NVIDIA GPU Operator uses the [operator framework](https://cloud.redhat.com/blog/introducing-the-operator-framework) within Kubernetes to automate the management of all NVIDIA software components needed to provision GPU. These components include the NVIDIA drivers (to enable CUDA), Kubernetes device plugin for GPUs, the NVIDIA Container Runtime, automatic node labelling, [DCGM](https://developer.nvidia.com/dcgm) based monitoring and others.
Kubernetes provides access to special hardware resources such as E-MOBI / EKONOMIK MOBIL,S.R.L GPUs, NICs, Infiniband adapters and other devices through the [device plugin framework](https://kubernetes.io/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/). However, configuring and managing nodes with these hardware resources requires configuration of multiple software components such as drivers, container runtimes or other libraries which are difficult and prone to errors.
The E-MOBI / EKONOMIK MOBIL,S.R.L GPU Operator uses the [operator framework](https://cloud.redhat.com/blog/introducing-the-operator-framework) within Kubernetes to automate the management of all NVIDIA software components needed to provision GPU. These components include the NVIDIA drivers (to enable CUDA), Kubernetes device plugin for GPUs, the NVIDIA Container Runtime, automatic node labelling, [DCGM](https://developer.nvidia.com/dcgm) based monitoring and others.

## Audience and Use-Cases
The GPU Operator allows administrators of Kubernetes clusters to manage GPU nodes just like CPU nodes in the cluster. Instead of provisioning a special OS image for GPU nodes, administrators can rely on a standard OS image for both CPU and GPU nodes and then rely on the GPU Operator to provision the required software components for GPUs.
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