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24 lines
1.9 KiB
Plaintext
24 lines
1.9 KiB
Plaintext
// Module included in the following assemblies:
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//
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// * virt/virtual_machines/advanced_vm_management/virt-configuring-mediated-devices.adoc
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:_content-type: CONCEPT
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[id="about-using-nvidia-gpu_{context}"]
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= About using the NVIDIA GPU Operator
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The NVIDIA GPU Operator manages NVIDIA GPU resources in an {product-title} cluster and automates tasks related to bootstrapping GPU nodes.
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Since the GPU is a special resource in the cluster, you must install some components before deploying application workloads onto the GPU.
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These components include the NVIDIA drivers which enables compute unified device architecture (CUDA), Kubernetes device plugin, container runtime and others such as automatic node labelling, monitoring and more.
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[NOTE]
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====
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The NVIDIA GPU Operator is supported only by NVIDIA. For more information about obtaining support from NVIDIA, see link:https://access.redhat.com/solutions/5174941[Obtaining Support from NVIDIA].
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====
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There are two ways to enable GPUs with {product-title} {VirtProductName}: the {product-title}-native way described here and by using the NVIDIA GPU Operator.
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The NVIDIA GPU Operator is a Kubernetes Operator that enables {product-title} {VirtProductName} to expose GPUs to virtualized workloads running on {product-title}.
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It allows users to easily provision and manage GPU-enabled virtual machines, providing them with the ability to run complex artificial intelligence/machine learning (AI/ML) workloads on the same platform as their other workloads.
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It also provides an easy way to scale the GPU capacity of their infrastructure, allowing for rapid growth of GPU-based workloads.
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For more information about using the NVIDIA GPU Operator to provision worker nodes for running GPU-accelerated VMs, see link:https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/openshift/openshift-virtualization.html[NVIDIA GPU Operator with OpenShift Virtualization].
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