Installing Runtime 23.1 on Python 3.10 with GPU
An instance administrator can install Runtime 23.1 on Python 3.10 with GPU on IBM Cloud Pak® for Data Version 4.8.
- Who needs to complete this task?
-
Instance administrator To install Runtime 23.1 on Python 3.10 with GPU, you must be an instance administrator. An instance administrator has permission to install software in the following projects:
- When do you need to complete this task?
-
Review the following options to determine whether you need to complete this task:
- Repeat as needed If you are responsible for multiple instances of Cloud Pak for Data, you can repeat this task to install more instances of Runtime 23.1 on Python 3.10 with GPU on the cluster.
Information you need to complete this task
Review the following information before you install Runtime 23.1 on Python 3.10 with GPU:
- Version requirements
-
All of the components that are associated with an instance of Cloud Pak for Data must be installed at the same release. For example, if the Cloud Pak for Data control plane is installed at Version 4.8.7, you must install Runtime 23.1 on Python 3.10 with GPU at Version 4.8.7.
- Environment variables
-
The commands in this task use environment variables so that you can run the commands exactly as written.
- If you don't have the script that defines the environment variables, see Setting up installation environment variables.
- To use the environment variables from the script, you must source the environment variables
before you run the commands in this task. For example,
run:
source ./cpd_vars.sh
- Security context constraint
-
Runtime 23.1 on Python 3.10 with GPU works with the default Red Hat® OpenShift® Container Platform security context constraint,
restricted-v2
.
- Storage requirements
- You don't need to specify storage information when you install Runtime 23.1 on Python 3.10 with GPU.
Before you begin
This task assumes that the following prerequisites are met:
Prerequisite | Where to find more information |
---|---|
The cluster meets the minimum requirements for installing Runtime 23.1 on Python 3.10 with GPU. | If this task is not complete, see System requirements. |
The workstation from which you will run the installation is set up as a client workstation
and includes the following command-line interfaces:
|
If this task is not complete, see Setting up a client workstation. |
The Cloud Pak for Data control plane is installed. | If this task is not complete, see Installing an instance of Cloud Pak for Data. |
For environments that use a private container registry, such as air-gapped environments, the Runtime 23.1 on Python 3.10 with GPU software images are mirrored to the private container registry. | If this task is not complete, see Mirroring images to a private container registry. |
For environments that use a private container registry, such as air-gapped
environments, the cpd-cli is configured to pull the olm-utils-v2 image from the private container registry. |
If this task is not complete, see Pulling the olm-utils-v2 image from the private container registry. |
The node settings are adjusted for Runtime 23.1 on Python 3.10 with GPU. | If this task is not complete, see Changing required node settings. |
Prerequisite services
Before you install Runtime 23.1 on Python 3.10 with GPU, ensure that the following services are installed and running:
Procedure
Complete the following tasks to install Runtime 23.1 on Python 3.10 with GPU:
Installing the service
To install Runtime 23.1 on Python 3.10 with GPU:
-
Log the
cpd-cli
in to the Red Hat OpenShift Container Platform cluster:${CPDM_OC_LOGIN}
Remember:CPDM_OC_LOGIN
is an alias for thecpd-cli manage login-to-ocp
command. - Create the custom resource for Runtime 23.1 on Python 3.10 with
GPU.
cpd-cli manage apply-cr \ --components=ws_runtimes \ --release=${VERSION} \ --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \ --extra-vars="cr_name=ibm-cpd-ws-runtime-231-pygpu" \ --license_acceptance=true
Specifying installation options
You can optionally install the pre-trained NLP models for the Watson Natural Language Processing library.
oc patch -n ${PROJECT_CPD_INST_OPERANDS} NotebookRuntime ibm-cpd-ws-runtime-231-pygpu --type=merge --patch '{"spec":{"install_nlp_models":true}}'
oc get -n ${PROJECT_CPD_INST_OPERANDS} NotebookRuntime
The pre-trained NLP models are available only when the status column for the notebook runtimes changes to Completed.
Validating the installation
apply-cr
command
returns:[SUCCESS]... The apply-cr command ran successfully
If you want to confirm that the custom resource status is
Completed
, you can run the cpd-cli
manage
get-cr-status
command:
cpd-cli manage get-cr-status \
--cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
--components=ws_runtimes
What to do next
This service is ready to use. See Notebook environments.