General Settings
The General settings section in the Admin panel provides centralized controls for enabling or disabling key platform features. These settings allow administrators to tailor the behavior of the NVIDIA Run:ai environment based on organizational policies, user needs, and workload types.
Analytics
CPU analytics
Enable the CPU analytics dashboard for better visibility of CPU intensive workloads. For more information, see the CPU dashboard guide
Consumption Beta
Enable the consumption dashboard to view consumption by segment. For more information, see the Consumption dashboard guide
Advanced metrics
Enable advanced GPU device-level metrics on the Nodes table.Contact Run:ai support to configure the NVIDIA exporter and Run:ai cluster
Dashboard performance optimization
Improve dashboard performance with enhanced queries
Once activated, dashboard data collected before cluster version 2.13 will no longer be visible
Resources
Limit projects from exceeding department quota
Enable to prevent projects’ total quota from exceeding the department’s quota or being less than the total usage by non-preemptible workloads. For more information, see the NVIDIA Run:ai Scheduler guide.
CPU quota
Enable resource quota based on CPU resources. For more information, see the Departments guide and the Projects guide.
Over quota weight
Enable over quota weight to set what proportion of unused resources a project can get on top of its quota. For more information, see the Over quota weight guide.
GPU resource optimization Beta
Enable to set a GPU memory limit for workloads. To enable this on each NVIDIA Run:ai cluster, see the Dynamic GPU fractions guide.
Workloads
Policies
Enable to impose restrictions and default values on workloads' fields. For more information, see the Policies guide
Models Beta
Enable instant deployment of open source models
GPT2 model Experimental
GPT2 model - present OpenAI's GPT2 model in the catalog in favor of demos. This model's compute requirements are relatively low (CPU resources are sufficient for it). The underlying image of this model also consists of a Chatbot UI
Flexible workload submission
Enable to submit workloads via the new flexible form. Allow selecting an existing setup or starting from scratch, reviewing existing setups and understanding policy definitions. The form also includes advanced features tailored for inference workloads. For more information, see Flexible submission.
Flexible workload templates Experimental
Enable to create workload templates via the new flexible form. For more information, see the Workload Templates guide.
Data volumes Beta
Enable to allow creation of data volumes to share underlying data across scopes. For more information, see the Data volumes guide.
Job submission Legacy
Enable to submit interactive and training workloads via the legacy Jobs form
Weights & Biases SWEEP integration
Enable hyperparameter configuration using the SWEEP integration on Weights & Biases cloud for automation and acceleration of the hyperparameter optimization search when submitting a training job via the legacy Jobs form.
MPI distributed training Legacy
Enable to run distributed training workloads via the Kubeflow MPI. To enable it on each Run:ai cluster, see the Distributed training guide.
Set Docker image registry
Set a Docker registry to enable autocomplete search for Docker images on workload submission forms
Improved command line interface
Enable for better data consistency with the UI, auto-upgrade, and interactive mode. For more information, see the CLI guide
Deleted workloads
Enable to view deleted workloads in the Workloads view.
Security
Identity provider
Anyone given access to the NVIDIA Run:ai application via the identity provider system will be able to join the platform and authenticate using SSO. See Single Sign-On (SSO) guide.
Set logout redirect URL
Users will be redirected to this URL after logging out from NVIDIA Run:ai
Set timeout session
Upon session timeout, users will be logged out automatically.
Notifications
Email notification
Set the email server through which the email notifications will be sent
System notification
Write a message that will be displayed to all users
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