Here, we bring together information regarding how to control your computing resources on the C3 AI Suite.
Access Through Static Console
The jupyter service is controlled through the '
Jupyter' type. To start the juptyer service with the default container profile, execute
Jupyter.start() within the static console. To stop the jupyter service execute
To launch jupyter service with a specific config, use
Jupyter.startWithConfig(). This accepts an argument of type
JupyterServiceConfig can represent multiple types of services one of which is the '
resourceProfile'. This can represent pre-designated resource profiles of type
ResourceProfile. To list the available resource profiles do
By default, two
ResourceProfiles exist, 'Basic', and 'BasicGPU'. For example, to launch the Jupyter service using the 'BasicGPU' profile, you would execute
Access Through IDS
Through IDS, clear controls regarding Jupyter are exposed under the 'ML Studio' section for Application. When you've selected a project, you need to start the Jupyter service to access notebooks on that project. In the creation process, you're able to select the container profile to use for your jupyter service. By default, the 'BasicGPU' profile offers a single K80 GPU.
You can create new container profiles. Select the 'App Settings' Menu, and there's a tab called 'Conainer Profiles'. You can create new profiles which have difference resources like more GPUs, and more vCPUs, and more RAM. Create a new container profile, then when creating the Jupyter service select the new profile to gain access to those resources.