Changing GPU settings

Important: IBM Cloud Pak® for Data Version 4.7 will reach end of support (EOS) on 31 July, 2025. For more information, see the Discontinuance of service announcement for IBM Cloud Pak for Data Version 4.X.

Upgrade to IBM Software Hub Version 5.1 before IBM Cloud Pak for Data Version 4.7 reaches end of support. For more information, see Upgrading IBM Software Hub in the IBM Software Hub Version 5.1 documentation.

The Red Hat® OpenShift® NVIDIA GPU Operator uses the operator framework within Kubernetes to automate the management of all NVIDIA software components that are needed to provision GPU.

Complete the steps to install the NVIDIA GPU operator if you plan to install the following services:

  • Runtime 23.1 on Python 3.10 for GPU
  • Runtime 22.2 on Python 3.10 for GPU
  • Runtime 22.1 on Python 3.9 for GPU
  • Watson Machine Learning Accelerator
Installation phase
You are not here. Setting up a client workstation
You are not here. Setting up a cluster
You are not here. Collecting required information
You are not here. Preparing to run installs from a private container registry
You are here icon. Preparing the cluster for Cloud Pak for Data
You are not here. Preparing to install an instance of Cloud Pak for Data
You are not here. Installing an instance of Cloud Pak for Data
Who needs to complete this task?
A cluster administrator must complete this task.
When do you need to complete this task?
When you need to install the NVIDIA GPU Operator to manage GPU settings on a cluster that is connected to the internet or in an air-gapped environment.

Procedure

Complete the following steps to install the NVIDIA GPU Operator on a cluster that is connected to the internet to automate the management of all NVIDIA software components that are needed to provision GPU:
  1. Install the Node Feature Discovery Operator.
  2. Install the GPU Operator.

To install the NVIDIA GPU Operator on an air-gapped environment, see Deploy GPU Operators in a disconnected or airgapped environment.