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2024a workbench image updates (#248)
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* In flight 20241 package changes.

* In-flight updates.

* Further package updates.

* Adjusting table formatting and updating CUDA - RStudio.

* Adjusting Tensorflow columns.

* Updating 2024a elyra package versions.

* Adding new HabanaAI versions.

* Updating references to Habana 1.10.

* Adjusting phrasing around workbenches.

* Removing 1.2 image versions, deprecating 2023.1.

* Updating Habana packages.

* Updates python version for HabanaAI, Kfp-tekton versions.

* Updating kfp-tekton 2024 references.

* Updating to remove 2023.2 for RStudio.
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grainnejenningsRH authored Apr 17, 2024
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3 changes: 2 additions & 1 deletion modules/enabling-habana-gaudi-devices.adoc
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[role='_additional-resources']
.Additional resources
* link:https://docs.habana.ai/en/v1.10.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator for OpenShift].
* link:https://docs.habana.ai/en/v1.10.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator v1.10 for OpenShift].
* link:https://docs.habana.ai/en/v1.13.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator v1.13 for OpenShift].
16 changes: 10 additions & 6 deletions modules/habana-gaudi-integration.adoc
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= Habana Gaudi integration

[role='_abstract']
To accelerate your high-performance deep learning (DL) models, you can integrate Habana Gaudi devices in {productname-short}. {productname-short} also includes the HabanaAI notebook image. This notebook image is pre-built and ready for your data scientists to use after you install or upgrade {productname-short}.
To accelerate your high-performance deep learning (DL) models, you can integrate Habana Gaudi devices in {productname-short}. {productname-short} also includes the HabanaAI workbench image, which is pre-built and ready for your data scientists to use after you install or upgrade {productname-short}.

Before you can successfully enable Habana Gaudi devices in {productname-short}, you must install the necessary dependencies and install the HabanaAI Operator. This allows your data scientists to use Habana libraries and software associated with Habana Gaudi devices from their notebooks. For more information about how to enable your OpenShift environment for Habana Gaudi devices, see link:https://docs.habana.ai/en/v1.10.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator for OpenShift].
Before you can enable Habana Gaudi devices in {productname-short}, you must install the necessary dependencies and the version of the HabanaAI Operator that matches the Habana version of the HabanaAI workbench image in your deployment. This allows your data scientists to use Habana libraries and software associated with Habana Gaudi devices from their workbench.

For more information about how to enable your OpenShift environment for Habana Gaudi devices, see link:https://docs.habana.ai/en/v1.10.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator v1.10 for OpenShift] and link:https://docs.habana.ai/en/v1.13.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator v1.13 for OpenShift].

[IMPORTANT]
====
Currently, Habana Gaudi integration is only supported in OpenShift {ocp-minimum-version}.
You can use Habana Gaudi accelerators on {productname-short} with version 1.10.0 of the Habana Gaudi Operator. For information about the supported configurations for version 1.10 of the Habana Gaudi Operator, see link:https://docs.habana.ai/en/latest/Support_Matrix/Support_Matrix_v1.10.0.html#support-matrix-1-10-0[Support Matrix v1.10.0].
You can use Habana Gaudi accelerators on {productname-short} with versions 1.10.0 and 1.13.0 of the Habana Gaudi Operator. The version of the HabanaAI Operator that you install must match the Habana version of the HabanaAI workbench image in your deployment. This means that only one version of HabanaAI workbench image will work for you at a time.
In addition, the version of the HabanaAI Operator that you install must match the version of the HabanaAI notebook image in your deployment.
For information about the supported configurations for versions 1.10 and 1.13 of the Habana Gaudi Operator, see link:https://docs.habana.ai/en/latest/Support_Matrix/Support_Matrix_v1.10.0.html#support-matrix-1-10-0[Support Matrix v1.10.0] and link:https://docs.habana.ai/en/latest/Support_Matrix/Support_Matrix_v1.13.0.html#support-matrix-1-13-0[Support Matrix v1.13.0].
====

You can use Habana Gaudi devices in an Amazon EC2 DL1 instance on OpenShift. Therefore, your OpenShift platform must support EC2 DL1 instances. Habana Gaudi accelerators are available to your data scientists when they create a workbench, serve a model, and create a notebook.
You can use Habana Gaudi devices in an Amazon EC2 DL1 instance on OpenShift. Therefore, your OpenShift platform must support EC2 DL1 instances. Habana Gaudi accelerators are available to your data scientists when they create a workbench instance or serve a model.

To identify the Habana Gaudi devices present in your deployment, use the `lspci` utility. For more information, see link:https://linux.die.net/man/8/lspci[lspci(8) - Linux man page].

Expand All @@ -30,8 +32,10 @@ Before you can use your Habana Gaudi devices, you must enable them in your OpenS

[role="_additional-resources"]
.Additional resources
* link:https://docs.habana.ai/en/v1.10.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator for OpenShift]
* link:https://docs.habana.ai/en/v1.10.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator v1.10 for OpenShift]
* link:https://docs.habana.ai/en/v1.13.0/Orchestration/HabanaAI_Operator/index.html[HabanaAI Operator v1.13 for OpenShift]
* link:https://linux.die.net/man/8/lspci[lspci(8) - Linux man page]
* link:https://aws.amazon.com/ec2/instance-types/dl1/[Amazon EC2 DL1 Instances]
* link:https://docs.habana.ai/en/latest/Support_Matrix/Support_Matrix_v1.10.0.html#support-matrix-1-10-0[Support Matrix v1.10.0]
* link:https://docs.habana.ai/en/latest/Support_Matrix/Support_Matrix_v1.13.0.html#support-matrix-1-13-0[Support Matrix v1.13.0]
* link:https://access.redhat.com/solutions/4870701[What version of the Kubernetes API is included with each OpenShift 4.x release?]
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