NVIDIA vGPU for Compute Installation#
Install NVIDIA vGPU for Compute to enable GPU virtualization. The procedure has three phases - host setup, guest VM driver installation, and AI workload deployment - each documented on its own page below.
Installation Overview
Verify Prerequisites: Confirm hardware, BIOS settings, and licensing requirements
Install NGC CLI: Download software from NVIDIA NGC Catalog
Install Virtual GPU Manager: Deploy on hypervisor host (VMware, KVM, Nutanix)
Verify Fabric Manager: Included in the NVIDIA AI Enterprise drivers for HGX multi-GPU configurations
Install vGPU Guest Driver: Deploy in each virtual machine
Configure Licensing: Connect VMs to NVIDIA License System
Refer to the NVIDIA AI Enterprise Product Support Matrix for supported platforms and versions.
Installation Tasks#
Subpage |
Audience |
Use when you need |
|---|---|---|
Hypervisor administrator |
To verify prerequisites and BIOS, install the NGC CLI, deploy the Virtual GPU Manager on the hypervisor, and confirm Fabric Manager on HGX servers. |
|
Guest VM owner |
To install the vGPU Guest Driver in each VM (Ubuntu, Red Hat, Windows, or other Linux), then license the VM and configure profiles. |
|
AI / DS / workload deployer |
To install the NVIDIA GPU Operator (Bash script) and pull NVIDIA AI Enterprise application containers via Docker, Podman, or Cloud Native Stack on licensed Guest VMs. |
Next Steps#
After installing the vGPU Manager and guest drivers:
Configure vGPU for Compute - create vGPU devices (MIG-backed or time-sliced) and assign them to VMs.
License your vGPU VMs - configure the NVIDIA License System so VMs run at full performance.
Install the NVIDIA GPU Operator - deploy the GPU Operator for container workloads on licensed VMs.