NVIDIA Run:ai
NVIDIA Run:ai is a GPU orchestration and optimization platform that helps organizations maximize compute utilization for AI workloads. By optimizing the use of expensive compute resources, NVIDIA Run:ai accelerates AI development cycles, and drives faster time-to-market for AI-powered innovations.
Review the requirements and install or upgrade
Configure authenticated access for users to securely access the NVIDIA Run:ai platform, Command Line Interface (CLI), and APIs
Tailor your NVIDIA Run:ai cluster deployment to meet specific operational requirements and optimize resource management
Monitor, manage, and restore NVIDIA Run:ai clusters
Monitor physical resources (cluster, nodes, GPUs) and application resources (departments, projects, workloads)
Set up NVIDIA Run:ai projects and departments to align with your organization's structure and management practices
Define how resources are allocated to optimize resource distribution based on your organization's needs
Manage users roles and access to the different objects of the system, its resources, and the set of allowed actions
Establish policies to enforce best practices and standardize processes for workload submission across your organization
Monitor real-time performance, track trends, detect anomalies, and optimize resource usage with dashboards and visualizations
Review the list of workload types and features supported
Use preconfigured building blocks such as environments and data sources to simplify and templatize workload submission
Conduct research, experiment with data sets and test algorithms to streamline model development using Workspaces
Scale model training with standard and distributed training workloads, utilizing more compute resources and large data sets
Deploy trained models using inference workloads to serve real-time or batch predictions, while dynamically scaling resources
Explore how the Scheduler optimizes GPU resource allocation and ensures efficient workload distribution
Create client credentials to obtain a token and use it within subsequent API calls
Integrate and automate workflows with APIs, enabling seamless interaction with system resources, monitoring, and management functions
Collect, analyze, and use system metrics to create custom dashboards or integrate metric data into other monitoring systems