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gpu/doc: Add Max Series support and a note about SR-IOV

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Signed-off-by: Tuomas Katila <tuomas.katila@intel.com>
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Tuomas Katila 2023-09-13 10:47:39 +03:00
parent a074384c22
commit 031ee64590
1 changed files with 8 additions and 1 deletions
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cmd/gpu_plugin/README.md
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@ -24,6 +24,7 @@ Table of Contents
* [Verify Plugin Registration](#verify-plugin-registration)
* [Testing and Demos](#testing-and-demos)
* [Labels created by GPU plugin](#labels-created-by-gpu-plugin)
* [SR-IOV use with the plugin](#sr-iov-use-with-the-plugin)
* [Issues with media workloads on multi-GPU setups](#issues-with-media-workloads-on-multi-gpu-setups)
* [Workaround for QSV and VA-API](#workaround-for-qsv-and-va-api)
@ -31,7 +32,7 @@ Table of Contents
## Introduction
Intel GPU plugin facilitates Kubernetes workload offloading by providing access to
discrete (including Intel® Data Center GPU Flex Series) and integrated Intel GPU devices
discrete (including Intel® Data Center GPU Flex & Max Series) and integrated Intel GPU devices
supported by the host kernel.
Use cases include, but are not limited to:
@ -344,6 +345,12 @@ The GPU plugin functionality can be verified by deploying an [OpenCL image](../.
If installed with NFD and started with resource-management, plugin will export a set of labels for the node. For detailed info, see [labeling documentation](./labels.md).
## SR-IOV use with the plugin
GPU plugin does __not__ setup SR-IOV. It has to be configured by the cluster admin.
GPU plugin does however support provisioning Virtual Functions (VFs) to containers for a SR-IOV enabled GPU. When the plugin detects a GPU with SR-IOV VFs configured, it will only provision the VFs and leaves the PF device on the host.
## Issues with media workloads on multi-GPU setups
OneVPL media API, 3D and compute APIs provide device discovery