NVIDIA GPU Virtualization
NVIDIA integration with VergeOS enables GPU acceleration for VMs through vGPU and Multi-Instance GPU (MIG) technologies, letting multiple VMs share physical GPU resources with performance isolation.
Overview
The NVIDIA integration with VergeOS enables GPU acceleration for virtual machines through NVIDIA's vGPU and Multi-Instance GPU (MIG) technologies. Multiple VMs can share physical GPU resources while maintaining performance isolation, managed through VergeOS resource groups and policies alongside traditional VMs.
Licensing Required
NVIDIA vGPU functionality requires a valid NVIDIA vGPU software license that matches your selected profile type and workload. See Supported Hardware for details.
Supported Hardware
Only select data center and professional GPUs support vGPU. Verify hardware and driver compatibility in the NVIDIA vGPU Supported GPUs list.
NVIDIA vGPU supports Windows and Linux guest operating systems. Feature availability varies by OS — see the NVIDIA vGPU Product Support Matrix for details.
IOMMU (VT-d) and SR-IOV must be enabled in the host BIOS.
For an overview of licensing options, refer to the NVIDIA Licensing Guide .
Architecture
The NVIDIA integration consists of three layers:
Physical Layer:
NVIDIA GPU hardware installed in VergeOS nodes
NVIDIA vGPU host drivers (uploaded as bundle drivers to the vSAN)
IOMMU/SR-IOV hardware virtualization support
Virtualization Layer:
VergeOS resource groups for GPU device management and allocation
Configurable vGPU profiles for different workload types
Time-sliced vGPU sharing (software-scheduled) or SR-IOV hardware partitioning, depending on the GPU model
Policy-based resource allocation and scheduling
Application Layer:
NVIDIA guest drivers installed within VMs (optionally attached as a driver ISO from the resource group)
CUDA runtime and development libraries
AI frameworks, professional applications, and VDI clients
vGPU Profile Types
When configuring vGPU resources, NVIDIA uses a letter suffix to indicate the profile type and intended workload:
A-Series
Virtual Applications
vApps
No
1
B-Series
Virtual Desktops
vPC
No
Up to 4
C-Series
AI/ML Compute
AI Enterprise
Full
1
Q-Series
Professional Graphics
vWS
Full
Up to 4
Choosing a Profile
B-Series — Standard office VDI deployments where users need basic graphics acceleration without CUDA
Q-Series — Professional workstations running CAD, 3D rendering, or applications that require certified NVIDIA drivers
C-Series — Dedicated GPU compute for AI/ML training and inference workloads with no display requirements
A-Series — Lightweight application streaming (e.g., RDSH/Citrix) where a single display is sufficient
Frame buffer sizes and maximum display counts vary by specific profile within each series. For full profile specifications, see the NVIDIA vGPU User Guide .
Multi-Instance GPU (MIG)
Supported GPUs (such as the A100, H100, and RTX PRO 6000 Blackwell) can be partitioned into multiple isolated GPU instances using NVIDIA MIG technology. Each MIG instance provides dedicated compute, memory, and memory bandwidth — unlike time-slicing, there is no resource contention between instances.
MIG instances can each run their own vGPU profile (A/B/Q), and when combined with time-sliced vGPU sharing within each instance, high-end GPUs like the RTX PRO 6000 Blackwell can support up to 48 concurrent VMs from a single physical GPU.
MIG profiles appear in the VergeOS resource group profile dropdown with a MIG prefix. For details on available MIG configurations, see the NVIDIA MIG User Guide .
Key Capabilities
Shared GPU Resources: Multiple VMs share a single physical GPU, maximizing hardware utilization instead of dedicating a GPU per VM
Live Migration: Move GPU-accelerated VMs between nodes without downtime (requires matching GPU model and vGPU profile on source and destination nodes)
Tenant Isolation: Hardware-level separation and performance guarantees between GPU workloads, with support for passing vGPU devices to tenants
Dynamic Allocation: Scale GPU resources based on workload demands and priorities
Full GPU Passthrough
If your workload requires exclusive access to an entire physical GPU (e.g., for maximum performance or unsupported vGPU hardware), consider PCI device passthrough instead of vGPU.
Implementation Resources
Getting Started
Review Device Passthrough Overview for foundation concepts
Follow the NVIDIA vGPU Configuration guide for step-by-step setup
Advanced Configuration
VM Best Practices — Performance optimization guidelines
Maintenance Mode — Required when rebooting nodes for driver installation
External Documentation
NVIDIA vGPU Documentation — Official NVIDIA vGPU documentation
NVIDIA Developer Portal — CUDA development resources and tools
NVIDIA Enterprise Support — Professional support services
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