Selecting the Right NVIDIA GPU Virtualization Software
NVIDIA GPU virtualization software products are optimized for different classes of workload. Therefore, you should select the right NVIDIA GPU virtualization software product on the basis of the workloads that your users are running.
This table summarizes the differences in features between the various NVIDIA GPU virtualization software products.
Feature | NVIDIA vPC | NVIDIA RTX vWS |
|---|---|---|
| Configuration and Deployment | ||
| Microsoft Windows support | ✔ | ✔ |
| Linux distributions support | ✔ | ✔ |
| NVIDIA graphics driver | ✔ | ✔ |
| NVIDIA RTX Enterprise driver | — | ✔ |
| Multiple vGPUs per VM | — | ✔ |
| NVLink | — | ✔ |
| ECC reporting and handling | — | ✔ |
| Page retirement | — | ✔ |
| Display | ||
| Maximum hardware-rendered display |
|
|
| Maximum resolution | 5120×2880 | 7680×4320 |
| Maximum pixel count | 17,694,720 | 66,355,200 |
| Advanced Professional Features | ||
| ISV certifications | — | ✔ |
| NVIDIA CUDA Toolkit / OpenCL support | — | ✔ |
| Graphics Features and APIs | ||
| NVENC | ✔ | ✔ |
| OpenGL extensions (WebGL) | ✔ | ✔ |
| RTX platform optimizations | — | ✔ |
| DirectX | ✔ | ✔ |
| Vulkan | — | ✔ |
For detailed information about vGPU licensing, refer to the NVIDIA Virtual GPU Packaging, Pricing, and Licensing Guide.
Each NVIDIA GPU virtualization software product is designed for a specific class of workload.
NVIDIA RTX Virtual Workstation
NVIDIA RTX Virtual Workstation (RTX vWS) software is designed for professional graphics workloads that benefit from the following NVIDIA RTX vWS features:
RTX Enterprise platform drivers and ISV certifications
Support for NVIDIA® CUDA® Toolkit and OpenCL
Higher resolution displays
vGPU profiles with larger amounts of frame buffer
NVIDIA RTX vWS accelerates professional design and visualization applications such as:
Autodesk Revit
Dassault Systèmes CATIA
Esri ArcGIS Pro
Autodesk Maya
SLB Petrel
Dassault Systèmes Solidworks
NVIDIA Virtual PC
NVIDIA Virtual PC (vPC) software is designed for knowledge worker VDI workloads to accelerate the following software and peripheral devices:
Office productivity applications
Streaming video
The Microsoft Windows and Linux distributions
Multiple monitors
High-resolution monitors
2D electric design automation (EDA)
NVIDIA vGPU software enables multiple virtual machines (VMs) to share a single physical GPU. This improves overall GPU utilization, but the way resources are shared depends on the underlying virtualization technology: either time-sliced vGPU or MIG-backed vGPU.
Time-Sliced vGPU Sharing
With time-sliced vGPU, multiple VMs share GPU access over time. NVIDIA vGPU software uses the best effort scheduler by default, which aims to balance performance across vGPUs.
Scheduling Options for GPU Sharing
To accommodate a variety of Quality of Service (QoS) levels for sharing a GPU, NVIDIA vGPU software provides multiple GPU scheduling options. For more information about these GPU scheduling options, refer to vGPU Schedulers.
MIG-Backed vGPU Sharing
With MIG (Multi-Instance GPU), a single physical GPU is partitioned at the hardware level into multiple fully isolated GPU instances. This provides guaranteed performance isolation between VMs.
Performance Allocation
Unlike time-sliced vGPU, MIG does not rely on time-sharing. Instead, each MIG-backed vGPU is assigned a dedicated slice of GPU resources with its own Streaming Multiprocessors (SMs) and memory subsystem. For example:
When four MIG instances are created, each instance delivers consistent and isolated performance to its assigned VM.
Within each MIG slice, up to 12 vGPUs can be created and time-sliced within that isolated slice. These vGPUs can be assigned to separate VMs, which continue to benefit from MIG’s hardware-level isolation boundaries.