$ ./ai-factory/run-ai
Run:ai & Slurm Orchestration_
Most GPU clusters run under half utilized: capital sitting idle. NVIDIA Run:ai and Slurm give every team compute, guarantee production its share, and lend idle cycles out automatically.
What's in scope
Fractional GPU Sharing
Slice GPUs across notebooks and light inference so experimentation never monopolizes hardware.
Quotas & Fair-Share Scheduling
Guaranteed allocations per team and project, with idle capacity lent out automatically.
Slurm & Batch Scheduling
HPC-style batch queues for training and research, run alongside Run:ai on the same clusters.
Cluster Consolidation
One orchestration layer across DGX systems, cloud GPUs, and existing Kubernetes estates.
Utilization Analytics
Per-team and per-project visibility into who uses what, and what it costs.
Day 2 Co-Administration
The scheduler is run and tuned alongside your operations team long after go-live.
The rest of the factory
NIM Inference Microservices
Optimized, containerized model serving with NVIDIA NIM: production inference endpoints in minutes.
Learn moreAgentic AI
AI agents built on NIM and open models that reason, use tools, and automate real enterprise workflows.
Learn moreIsaac Sim & Robotics
Robot simulation, synthetic data generation, and sim-to-real workflows built on NVIDIA Isaac Sim.
Learn moreOmniverse & Digital Twins
Photorealistic digital twins crafted by in-house digital artists, backed by GPU simulation.
Learn moreDGX & SuperPOD Infrastructure
The factory floor itself: NVIDIA workstations, servers, and SuperPODs sized, cabled, and run as one system.
Learn more