Virtual GPU Software User Guide

Virtual GPU Software User Guide

Documentation for administrators that explains how to install and configure NVIDIA Virtual GPU manager, configure virtual GPU software in pass-through mode, and install drivers on guest operating systems.

NVIDIA vGPU software is a graphics virtualization platform that provides virtual machines (VMs) access to NVIDIA GPU technology.

1.1. How NVIDIA vGPU Software Is Used

NVIDIA vGPU software can be used in several ways.

1.1.1. NVIDIA vGPU

NVIDIA Virtual GPU (vGPU) enables multiple virtual machines (VMs) to have simultaneous, direct access to a single physical GPU, using the same NVIDIA graphics drivers that are deployed on non-virtualized operating systems. By doing this, NVIDIA vGPU provides VMs with unparalleled graphics performance, compute performance, and application compatibility, together with the cost-effectiveness and scalability brought about by sharing a GPU among multiple workloads.

For more information, see Installing and Configuring NVIDIA Virtual GPU Manager.

1.1.2. GPU Pass-Through

In GPU pass-through mode, an entire physical GPU is directly assigned to one VM, bypassing the NVIDIA Virtual GPU Manager. In this mode of operation, the GPU is accessed exclusively by the NVIDIA driver running in the VM to which it is assigned. The GPU is not shared among VMs.

For more information, see Using GPU Pass-Through.

1.1.3. Bare-Metal Deployment

In a bare-metal deployment, you can use NVIDIA vGPU software graphics drivers with vWS and vApps licenses to deliver remote virtual desktops and applications. If you intend to use Tesla boards without a hypervisor for this purpose, use NVIDIA vGPU software graphics drivers, not other NVIDIA drivers.

To use NVIDIA vGPU software drivers for a bare-metal deployment, complete these tasks:

1. Install the driver on the physical host.

   For instructions, see Installing the NVIDIA vGPU Software Graphics Driver.

2. License any NVIDIA vGPU software that you are using.

   For instructions, see Virtual GPU Client Licensing User Guide.

3. Configure the platform for remote access.

   To use graphics features with Tesla GPUs, you must use a supported remoting solution, for example, RemoteFX, Citrix Virtual Apps and Desktops, VNC, or similar technology.

4. Use the display settings feature of the host OS to configure the Tesla GPU as the primary display.

   NVIDIA Tesla generally operates as a secondary device on bare-metal platforms.

5. If the system has multiple display adapters, disable display devices connected through adapters that are not from NVIDIA.

   You can use the display settings feature of the host OS or the remoting solution for this purpose. On NVIDIA GPUs, including Tesla GPUs, a default display device is enabled.

   Users can launch applications that require NVIDIA GPU technology for enhanced user experience only after displays that are driven by NVIDIA adapters are enabled.

1.2. Primary Display Adapter Requirements for NVIDIA vGPU Software Deployments

The GPU that is set as the primary display adapter cannot be used for NVIDIA vGPU deployments or GPU pass through deployments. The primary display is the boot display of the hypervisor host, which displays SBIOS console messages and then boot of the OS or hypervisor.

Any GPU that is being used for NVIDIA vGPU deployments or GPU pass through deployments must be set as a secondary display adapter.

Note:

Citrix Hypervisor provides a specific setting to allow the primary display adapter to be used for GPU pass through deployments.

Only the following GPUs are supported as the primary display adapter:

• Tesla M6
• Quadro RTX 6000
• Quadro RTX 8000

All other GPUs that support NVIDIA vGPU software cannot function as the primary display adapter because they are 3D controllers, not VGA devices.

If the hypervisor host does not have an extra graphics adapter, consider installing a low-end display adapter to be used as the primary display adapter. If necessary, ensure that the primary display adapter is set correctly in the BIOS options of the hypervisor host.

1.3. NVIDIA vGPU Software Features

NVIDIA vGPU software includes vWS, vPC, and vApps.

1.3.1. API Support on NVIDIA vGPU

NVIDIA vGPU includes support for the following APIs:

• Open Computing Language (OpenCL™ software) 3.0
• OpenGL^® 4.6
• Vulkan^® 1.3
• DirectX 11
• DirectX 12 (Windows 10)
• Direct2D
• DirectX Video Acceleration (DXVA)
• NVIDIA^® CUDA^® 12.4
• NVIDIA vGPU software SDK (remote graphics acceleration)
• NVIDIA RTX (on GPUs based on the NVIDIA Volta graphic architecture and later architectures)

1.3.2. NVIDIA CUDA Toolkit and OpenCL Support on NVIDIA vGPU Software

NVIDIA CUDA Toolkit and OpenCL are supported with NVIDIA vGPU only on a subset of vGPU types and supported GPUs.

For more information about NVIDIA CUDA Toolkit, see CUDA Toolkit Documentation 12.4.

OpenCL and CUDA Application Support

OpenCL and CUDA applications are supported on the following NVIDIA vGPU types:

• The 8Q vGPU type on the Tesla M10 GPU
• All Q-series vGPU types on the following GPUs:
  • NVIDIA L2
  • NVIDIA L4
  • NVIDIA L20
  • NVIDIA L40
  • NVIDIA L40S
  • NVIDIA RTX 5000 Ada
  • NVIDIA RTX 6000 Ada
  • NVIDIA A2
  • NVIDIA A10
  • NVIDIA A16
  • NVIDIA A40
  • NVIDIA RTX A5000
  • NVIDIA RTX A5500
  • NVIDIA RTX A6000
  • Tesla V100 SXM2
  • Tesla V100 SXM2 32GB
  • Tesla V100 PCIe
  • Tesla V100 PCIe 32GB
  • Tesla V100S PCIe 32GB
  • Tesla V100 FHHL
  • Tesla T4
  • Quadro RTX 6000
  • Quadro RTX 6000 passive
  • Quadro RTX 8000
  • Quadro RTX 8000 passive

NVIDIA CUDA Toolkit Development Tool Support

NVIDIA vGPU supports the following NVIDIA CUDA Toolkit development tools on some GPUs:

• Debuggers:
  • CUDA-GDB
  • Compute Sanitizer
• Profilers:
  • The Activity, Callback, and Profiling APIs of the CUDA Profiling Tools Interface (CUPTI)

    Other CUPTI APIs, such as the Event and Metric APIs, are not supported.

  • NVIDIA Nsight™ Compute
  • NVIDIA Nsight Systems
  • NVIDIA Nsight plugin
  • NVIDIA Nsight Visual Studio plugin

  Other CUDA profilers, such as nvprof and NVIDIA Visual Profiler, are not supported.

These tools are supported only in Linux guest VMs.

NVIDIA CUDA Toolkit profilers are supported and can be enabled on a VM for which unified memory is enabled.

The following table lists the GPUs on which NVIDIA vGPU supports these debuggers and profilers.

✓ Feature is supported

- Feature is not supported

Supported NVIDIA CUDA Toolkit Features

NVIDIA vGPU supports the following NVIDIA CUDA Toolkit features if the vGPU type, physical GPU, and the hypervisor software version support the feature:

• Error-correcting code (ECC) memory
• Peer-to-peer CUDA transfers over NVLink
  Note:

  To determine the NVLink topology between physical GPUs in a host or vGPUs assigned to a VM, run the following command from the host or VM:

  Copy

  Copied!

              
  
              
  $ nvidia-smi topo -m
          

• Unified Memory
  Note:

  Unified memory is disabled by default. If used, you must enable unified memory individually for each vGPU that requires it by setting a vGPU plugin parameter. For instructions, see Enabling Unified Memory for a vGPU.

• NVIDIA Nsight Systems GPU context switch trace

Dynamic page retirement is supported for all vGPU types on physical GPUs that support ECC memory, even if ECC memory is disabled on the physical GPU.

NVIDIA CUDA Toolkit Features Not Supported by NVIDIA vGPU

NVIDIA vGPU does not support the NVIDIA Nsight Graphics feature of NVIDIA CUDA Toolkit.

1.3.3. Additional vWS Features

In addition to the features of vPC and vApps, vWS provides the following features:

• Workstation-specific graphics features and accelerations
• Certified drivers for professional applications
• GPU pass through for workstation or professional 3D graphics

  In pass-through mode, vWS supports multiple virtual display heads at resolutions up to 8K and flexible virtual display resolutions based on the number of available pixels. For details, see Display Resolutions for Physical GPUs.

• 10-bit color for Windows users. (HDR/10-bit color is not currently supported on Linux, NvFBC capture is supported but deprecated.)

1.3.4. NVIDIA GPU Cloud (NGC) Containers Support on NVIDIA vGPU Software

NVIDIA vGPU software supports NGC containers in NVIDIA vGPU and GPU pass-through deployments on all supported hypervisors.

In NVIDIA vGPU deployments, Q-series vGPU types are supported only on GPUs based on NVIDIA GPU architectures after the Maxwell architecture.

In GPU pass-through deployments, all GPUs based on NVIDIA GPU architectures after the NVIDIA Maxwell™ architecture that support NVIDIA vGPU software are supported.

NVIDIA vGPU software supports NGC containers on any guest operating system listed in Supported Platforms - NVIDIA Container Toolkit that is also supported by NVIDIA vGPU software.

For more information about setting up NVIDIA vGPU software for use with NGC containers, see Using NGC with NVIDIA Virtual GPU Software Setup Guide.

1.3.5. NVIDIA GPU Operator Support

NVIDIA GPU Operator simplifies the deployment of NVIDIA vGPU software on software container platforms that are managed by the Kubernetes container orchestration engine. It automates the installation and update of NVIDIA vGPU software graphics drivers for container platforms running in guest VMs that are configured with NVIDIA vGPU.

Any drivers to be installed by NVIDIA GPU Operator must be downloaded from the NVIDIA Licensing Portal to a local computer. Automated access to the NVIDIA Licensing Portal by NVIDIA GPU Operator is not supported.

NVIDIA GPU Operator supports automated configuration of NVIDIA vGPU software and provides telemetry support through DCGM Exporter running in a guest VM.

NVIDIA GPU Operator is supported only on specific combinations of hypervisor software release, container platform, vGPU type, and guest OS release. To determine if your configuration supports NVIDIA GPU Operator with NVIDIA vGPU deployments, consult the release notes for your chosen hypervisor at NVIDIA Virtual GPU Software Documentation.

For more information, see NVIDIA GPU Operator Overview on the NVIDIA documentation portal.

1.4. How this Guide Is Organized

Virtual GPU Software User Guide is organized as follows:

• This chapter introduces the capabilities and features of NVIDIA vGPU software.
• Installing and Configuring NVIDIA Virtual GPU Manager provides a step-by-step guide to installing and configuring vGPU on supported hypervisors.
• Using GPU Pass-Through explains how to configure a GPU for pass-through on supported hypervisors.
• Installing the NVIDIA vGPU Software Graphics Driver explains how to install NVIDIA vGPU software graphics driver on Windows and Linux operating systems.
• Licensing an NVIDIA vGPU explains how to license NVIDIA vGPU licensed products on Windows and Linux operating systems.
• Modifying a VM’s NVIDIA vGPU Configuration explains how to remove a VM’s vGPU configuration and modify GPU assignments for vGPU-enabled VMs.
• Monitoring GPU Performance covers performance monitoring of physical GPUs and virtual GPUs from the hypervisor and from within individual guest VMs.
• Changing Scheduling Behavior for Time-Sliced vGPUs describes the scheduling behavior of NVIDIA vGPUs and how to change it.
• Troubleshooting provides guidance on troubleshooting.
• Virtual GPU Types Reference provides details of each vGPU available from each supported GPU and provides examples of mixed virtual display configurations for B-series and Q-series vGPUs.
• Configuring x11vnc for Checking the GPU in a Linux Server explains how to use x11vnc to confirm that the NVIDIA GPU in a Linux server to which no display devices are directly connected is working as expected.
• Disabling NVIDIA Notification Icon for Citrix Published Application User Sessions explains how to ensure that the NVIDIA Notification Icon application does not prevent the Citrix Published Application user session from being logged off even after the user has quit all ot
• Citrix Hypervisor Basics explains how to perform basic operations on Citrix Hypervisor to install and configure NVIDIA vGPU software and optimize Citrix Hypervisor operation with vGPU.
• Citrix Hypervisor vGPU Management covers vGPU management on Citrix Hypervisor.
• Citrix Hypervisor Performance Tuning covers vGPU performance optimization on Citrix Hypervisor.

The process for installing and configuring NVIDIA Virtual GPU Manager depends on the hypervisor that you are using. After you complete this process, you can install the display drivers for your guest OS and license any NVIDIA vGPU software licensed products that you are using.

2.1. About NVIDIA Virtual GPUs

2.1.1. NVIDIA vGPU Architecture

The high-level architecture of NVIDIA vGPU is illustrated in Figure 1. Under the control of the NVIDIA Virtual GPU Manager running under the hypervisor, NVIDIA physical GPUs are capable of supporting multiple virtual GPU devices (vGPUs) that can be assigned directly to guest VMs.

Guest VMs use NVIDIA vGPUs in the same manner as a physical GPU that has been passed through by the hypervisor: an NVIDIA driver loaded in the guest VM provides direct access to the GPU for performance-critical fast paths, and a paravirtualized interface to the NVIDIA Virtual GPU Manager is used for non-performant management operations.

Figure 1. NVIDIA vGPU System Architecture

Each NVIDIA vGPU is analogous to a conventional GPU, having a fixed amount of GPU framebuffer, and one or more virtual display outputs or “heads”. The vGPU’s framebuffer is allocated out of the physical GPU’s framebuffer at the time the vGPU is created, and the vGPU retains exclusive use of that framebuffer until it is destroyed. Depending on the physical GPU and the GPU virtualization software, NVIDIA Virtual GPU Manager supports different types of vGPU on a physical GPU:

• On all GPUs that support NVIDIA vGPU software, time-sliced vGPUs can be created.
• Additionally, on GPUs that support the Multi-Instance GPU (MIG) feature and NVIDIA AI Enterprise, MIG-backed vGPUs are supported. The MIG feature is introduced on GPUs that are based on the NVIDIA Ampere GPU architecture.
  Note:

  Although earlier releases of NVIDIA vGPU software supported GPUs that support the MIG feature, such GPUs are not supported on this release of NVIDIA vGPU software. GPUs that support the MIG feature are supported only on NVIDIA AI Enterprise.

2.1.1.1. Time-Sliced NVIDIA vGPU Internal Architecture

A time-sliced vGPU is a vGPU that resides on a physical GPU that is not partitioned into multiple GPU instances. All time-sliced vGPUs resident on a GPU share access to the GPU’s engines including the graphics (3D), video decode, and video encode engines.

In a time-sliced vGPU, processes that run on the vGPU are scheduled to run in series. Each vGPU waits while other processes run on other vGPUs. While processes are running on a vGPU, the vGPU has exclusive use of the GPU’s engines. You can change the default scheduling behavior as explained in Changing Scheduling Behavior for Time-Sliced vGPUs.

Figure 2. Time-Sliced NVIDIA vGPU Internal Architecture

2.1.2. About Virtual GPU Types

The number of physical GPUs that a board has depends on the board. Each physical GPU can support several different types of virtual GPU (vGPU). vGPU types have a fixed amount of frame buffer, number of supported display heads, and maximum resolutions¹. They are grouped into different series according to the different classes of workload for which they are optimized. Each series is identified by the last letter of the vGPU type name.

The number after the board type in the vGPU type name denotes the amount of frame buffer that is allocated to a vGPU of that type. For example, a vGPU of type A16-4Q is allocated 4096 Mbytes of frame buffer on an NVIDIA A16 board.

Due to their differing resource requirements, the maximum number of vGPUs that can be created simultaneously on a physical GPU varies according to the vGPU type. For example, an NVDIA A16 board can support up to 4 A16-4Q vGPUs on each of its two physical GPUs, for a total of 16 vGPUs, but only 2 A16-8Q vGPUs, for a total of 8 vGPUs. When enabled, the frame-rate limiter (FRL) limits the maximum frame rate in frames per second (FPS) for a vGPU as follows:

• For B-series vGPUs, the maximum frame rate is 45 FPS.
• For Q-series and A-series vGPUs, the maximum frame rate is 60 FPS.

By default, the FRL is enabled for all GPUs. The FRL is disabled when the vGPU scheduling behavior is changed from the default best-effort scheduler on GPUs that support alternative vGPU schedulers. For details, see Changing Scheduling Behavior for Time-Sliced vGPUs. On vGPUs that use the best-effort scheduler, the FRL can be disabled as explained in the release notes for your chosen hypervisor at NVIDIA Virtual GPU Software Documentation.

For details of the virtual GPU types available from each supported GPU, see Virtual GPU Types for Supported GPUs.

2.1.3. Virtual Display Resolutions for Q-series and B-series vGPUs

Instead of a fixed maximum resolution per display, Q-series and B-series vGPUs support a maximum combined resolution based on the number of available pixels, which is determined by their frame buffer size. You can choose between using a small number of high resolution displays or a larger number of lower resolution displays with these vGPUs.

The number of virtual displays that you can use depends on a combination of the following factors:

• Virtual GPU series
• GPU architecture
• vGPU frame buffer size
• Display resolution

Various factors affect the consumption of the GPU frame buffer, which can impact the user experience. These factors include and are not limited to the number of displays, display resolution, workload and applications deployed, remoting solution, and guest OS. The ability of a vGPU to drive a certain combination of displays does not guarantee that enough frame buffer remains free for all applications to run. If applications run out of frame buffer, consider changing your setup in one of the following ways:

• Switching to a vGPU type with more frame buffer
• Using fewer displays
• Using lower resolution displays

The maximum number of displays per vGPU listed in Virtual GPU Types for Supported GPUs is based on a configuration in which all displays have the same resolution. For examples of configurations with a mixture of display resolutions, see Mixed Display Configurations for B-Series and Q-Series vGPUs.

2.1.4. Valid Time-Sliced Virtual GPU Configurations on a Single GPU

NVIDIA vGPU software supports a mixture of different types of time-sliced vGPUs on the same physical GPU. Any combination of A-series, B-series, and Q-series vGPUs with any amount of frame buffer can reside on the same physical GPU simultaneously. The total amount of frame buffer allocated to the vGPUs on a physical GPU must not exceed the amount of frame buffer that the physical GPU has.

For example, the following combinations of vGPUs can reside on the same physical GPU simultaneously:

• A40-2B and A40-2Q
• A40-2Q and A40-4Q
• A40-2B and A40-4Q

By default, a GPU supports only vGPUs with the same amount of frame buffer and, therefore, is in equal-size mode. To support vGPUs with different amounts of frame buffer, the GPU must be put into mixed-size mode. When a GPU is in mixed-size mode, the maximum number of some types of vGPU allowed on a GPU is less than when the GPU is in equal-size mode. For more information, refer to the following topics:

• Putting a GPU Into Mixed-Size Mode
• Virtual GPU Types for Supported GPUs

Not all hypervisors and GPUs support a mixture of different types of time-sliced vGPUs on the same physical GPU. To determine if your chosen hypervisor supports this feature with your chosen GPU, consult the release notes for your hypervisor at NVIDIA Virtual GPU Software Documentation.

2.1.5. Guest VM Support

NVIDIA vGPU supports Windows and Linux guest VM operating systems. The supported vGPU types depend on the guest VM OS.

For details of the supported releases of Windows and Linux, and for further information on supported configurations, see the driver release notes for your hypervisor at NVIDIA Virtual GPU Software Documentation.

2.1.5.1. Windows Guest VM Support

Windows guest VMs are supported on all NVIDIA vGPU types, namely: Q-series, B-series, and A-series NVIDIA vGPU types.

2.1.5.2. Linux Guest VM support

Linux guest VMs are supported on all NVIDIA vGPU types, namely: Q-series, B-series, and A-series NVIDIA vGPU types.

2.2. Prerequisites for Using NVIDIA vGPU

Before proceeding, ensure that these prerequisites are met:

• You have a server platform that is capable of hosting your chosen hypervisor and NVIDIA GPUs that support NVIDIA vGPU software.
• One or more NVIDIA GPUs that support NVIDIA vGPU software is installed in your server platform.

• If you are using GPUs based on the NVIDIA Ampere architecture or later architectures, the following BIOS settings are enabled on your server platform:

  • VT-D/IOMMU
  • SR-IOV
  • Alternative Routing ID Interpretation (ARI)
• You have downloaded the NVIDIA vGPU software package for your chosen hypervisor, which consists of the following software:
  • NVIDIA Virtual GPU Manager for your hypervisor
  • NVIDIA vGPU software graphics drivers for supported guest operating systems
• The following software is installed according to the instructions in the software vendor’s documentation:
  • Your chosen hypervisor, for example, Citrix Hypervisor, Red Hat Enterprise Linux KVM, or VMware vSphere Hypervisor (ESXi)
  • The software for managing your chosen hypervisor, for example, Citrix XenCenter management GUI, or VMware vCenter Server
  • The virtual desktop software that you will use with virtual machines (VMs) running NVIDIA Virtual GPU, for example, Citrix Virtual Apps and Desktops, or VMware Horizon
  Note:

  If you are using VMware vSphere Hypervisor (ESXi), ensure that the ESXi host on which you will configure a VM with NVIDIA vGPU is not a member of a fully automated VMware Distributed Resource Scheduler (DRS) cluster. For more information, see Installing and Configuring the NVIDIA Virtual GPU Manager for VMware vSphere.

• A VM to be enabled with one or more virtual GPUs is created.
  Note:

  If the VM uses UEFI boot and you plan to install a Linux guest OS in the VM, ensure that secure boot is disabled.

• Your chosen guest OS is installed in the VM.

For information about supported hardware and software, and any known issues for this release of NVIDIA vGPU software, refer to the Release Notes for your chosen hypervisor:

• Virtual GPU Software for Citrix Hypervisor Release Notes
• Virtual GPU Software for Microsoft Azure Stack HCI Release Notes
• Virtual GPU Software for Red Hat Enterprise Linux with KVM Release Notes
• Virtual GPU Software for Ubuntu Release Notes
• Virtual GPU Software for VMware vSphere Release Notes

2.3. Switching the Mode of a GPU that Supports Multiple Display Modes

Some GPUs support display-off and display-enabled modes but must be used in NVIDIA vGPU software deployments in display-off mode.

The GPUs listed in the following table support multiple display modes. As shown in the table, some GPUs are supplied from the factory in display-off mode, but other GPUs are supplied in a display-enabled mode.

A GPU that is supplied from the factory in display-off mode, such as the NVIDIA A40 GPU, might be in a display-enabled mode if its mode has previously been changed.

To change the mode of a GPU that supports multiple display modes, use the displaymodeselector tool, which you can request from the NVIDIA Display Mode Selector Tool page on the NVIDIA Developer website.

2.4. Installing and Configuring the NVIDIA Virtual GPU Manager for Citrix Hypervisor

The following topics step you through the process of setting up a single Citrix Hypervisor VM to use NVIDIA vGPU. After the process is complete, you can install the graphics driver for your guest OS and license any NVIDIA vGPU software licensed products that you are using.

These setup steps assume familiarity with the Citrix Hypervisor skills covered in Citrix Hypervisor Basics.

2.4.1. Installing and Updating the NVIDIA Virtual GPU Manager for Citrix Hypervisor

The NVIDIA Virtual GPU Manager runs in the Citrix Hypervisor dom0 domain. The NVIDIA Virtual GPU Manager for Citrix Hypervisor is supplied as an RPM file and as a Supplemental Pack.

2.4.1.1. Installing the RPM package for Citrix Hypervisor

The RPM file must be copied to the Citrix Hypervisor dom0 domain prior to installation (see Copying files to dom0).

1. Use the rpm command to install the package:
   Copy

   Copied!

               
   
               
   [root@xenserver ~]# rpm -iv NVIDIA-vGPU-NVIDIA-vGPU-CitrixHypervisor-8.2-550.90.05.x86_64.rpm
   Preparing packages for installation...
   NVIDIA-vGPU-NVIDIA-vGPU-CitrixHypervisor-8.2-550.90.05
   [root@xenserver ~]#
           

2. Reboot the Citrix Hypervisor platform:
   Copy

   Copied!

               
   
               
   [root@xenserver ~]# shutdown –r now
   
   Broadcast message from root (pts/1) (Fri Jun 14 14:24:11 2024):
   
   The system is going down for reboot NOW! 
   [root@xenserver ~]#
           

2.4.1.2. Updating the RPM Package for Citrix Hypervisor

If an existing NVIDIA Virtual GPU Manager is already installed on the system and you want to upgrade, follow these steps:

1. Shut down any VMs that are using NVIDIA vGPU.
2. Install the new package using the –U option to the rpm command, to upgrade from the previously installed package:
   Copy

   Copied!

               
   
               
   [root@xenserver ~]# rpm -Uv NVIDIA-vGPU-NVIDIA-vGPU-CitrixHypervisor-8.2-550.90.05.x86_64.rpm
   Preparing packages for installation...
   NVIDIA-vGPU-NVIDIA-vGPU-CitrixHypervisor-8.2-550.90.05
   [root@xenserver ~]#
           

   Note:

   You can query the version of the current NVIDIA Virtual GPU Manager package using the rpm –q command:

   Copy

   Copied!

               
   
               
   [root@xenserver ~]# rpm –q NVIDIA-vGPU-NVIDIA-vGPU-CitrixHypervisor-8.2-550.90.05
   [root@xenserver ~]#
   If an existing NVIDIA GRID package is already installed and you don’t select the upgrade (-U) option when installing a newer GRID package, the rpm command will return many conflict errors.
   Preparing packages for installation...
           file /usr/bin/nvidia-smi from install of NVIDIA-vGPU-NVIDIA-vGPU-CitrixHypervisor-8.2-550.90.05.x86_64 conflicts with file from package NVIDIA-vGPU-xenserver-8.2-550.54.16.x86_64
           file /usr/lib/libnvidia-ml.so from install of NVIDIA-vGPU-NVIDIA-vGPU-CitrixHypervisor-8.2-550.90.05.x86_64 conflicts with file from package NVIDIA-vGPU-xenserver-8.2-550.54.16.x86_64
           ...
           

3. Reboot the Citrix Hypervisor platform:
   Copy

   Copied!

               
   
               
   [root@xenserver ~]# shutdown –r now
   Broadcast message from root (pts/1) (Fri Jun 14 14:24:11 2024):
   
   The system is going down for reboot NOW! 
   [root@xenserver ~]#
           

2.4.1.3. Installing or Updating the Supplemental Pack for Citrix Hypervisor

XenCenter can be used to install or update Supplemental Packs on Citrix Hypervisor hosts. The NVIDIA Virtual GPU Manager supplemental pack is provided as an ISO.

1. Select Install Update from the Tools menu.
2. Click Next after going through the instructions on the Before You Start section.
3. Click Select update or supplemental pack from disk on the Select Update section and open NVIDIA’s Citrix Hypervisor Supplemental Pack ISO.

   Figure 3. NVIDIA vGPU Manager supplemental pack selected in XenCenter

   

4. Click Next on the Select Update section.
5. In the Select Servers section select all the Citrix Hypervisor hosts on which the Supplemental Pack should be installed on and click Next.
6. Click Next on the Upload section once the Supplemental Pack has been uploaded to all the Citrix Hypervisor hosts.
7. Click Next on the Prechecks section.
8. Click Install Update on the Update Mode section.
9. Click Finish on the Install Update section.

Figure 4. Successful installation of NVIDIA vGPU Manager supplemental pack

2.4.1.4. Verifying the Installation of the NVIDIA vGPU Software for Citrix Hypervisor Package

After the Citrix Hypervisor platform has rebooted, verify the installation of the NVIDIA vGPU software package for Citrix Hypervisor.

1. Verify that the NVIDIA vGPU software package is installed and loaded correctly by checking for the NVIDIA kernel driver in the list of kernel loaded modules.
   Copy

   Copied!

               
   
               
   [root@xenserver ~]# lsmod | grep nvidia
   nvidia               9522927  0
   i2c_core               20294  2 nvidia,i2c_i801
   [root@xenserver ~]#
           

2. Verify that the NVIDIA kernel driver can successfully communicate with the NVIDIA physical GPUs in your system by running the nvidia-smi command. The nvidia-smi command is described in more detail in NVIDIA System Management Interface nvidia-smi.

Running the nvidia-smi command should produce a listing of the GPUs in your platform.

            

            
[root@xenserver ~]# nvidia-smi
Fri Jun 14 18:46:50 2024
+------------------------------------------------------+
| NVIDIA-SMI 550.90.05   Driver Version: 550.90.05   |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla M60           On   | 00000000:05:00.0 Off |                  Off |
| N/A   25C    P8    24W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla M60           On   | 00000000:06:00.0 Off |                  Off |
| N/A   24C    P8    24W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla M60           On   | 00000000:86:00.0 Off |                  Off |
| N/A   25C    P8    25W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla M60           On   | 00000000:87:00.0 Off |                  Off |
| N/A   28C    P8    24W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

[root@xenserver ~]#
        

If nvidia-smi fails to run or doesn’t produce the expected output for all the NVIDIA GPUs in your system, see Troubleshooting for troubleshooting steps.

2.4.2. Configuring a Citrix Hypervisor VM with Virtual GPU

To support applications and workloads that are compute or graphics intensive, you can add multiple vGPUs to a single VM.

For details about which Citrix Hypervisor versions and NVIDIA vGPUs support the assignment of multiple vGPUs to a VM, see Virtual GPU Software for Citrix Hypervisor Release Notes.

Citrix Hypervisor supports configuration and management of virtual GPUs using XenCenter, or the xe command line tool that is run in a Citrix Hypervisor dom0 shell. Basic configuration using XenCenter is described in the following sections. Command line management using xe is described in Citrix Hypervisor vGPU Management.

1. Ensure the VM is powered off.
2. Right-click the VM in XenCenter, select Properties to open the VM’s properties, and select the GPU property. The available GPU types are listed in the GPU type drop-down list:

   Figure 5. Using Citrix XenCenter to configure a VM with a vGPU

   

After you have configured a Citrix Hypervisor VM with a vGPU, start the VM, either from XenCenter or by using xe vm-start in a dom0 shell. You can view the VM’s console in XenCenter.

After the VM has booted, install the NVIDIA vGPU software graphics driver as explained in Installing the NVIDIA vGPU Software Graphics Driver.

2.4.3. Setting vGPU Plugin Parameters on Citrix Hypervisor

Plugin parameters for a vGPU control the behavior of the vGPU, such as the frame rate limiter (FRL) configuration in frames per second or whether console virtual network computing (VNC) for the vGPU is enabled. The VM to which the vGPU is assigned is started with these parameters. If parameters are set for multiple vGPUs assigned to the same VM, the VM is started with the parameters assigned to each vGPU.

For each vGPU for which you want to set plugin parameters, perform this task in a command shell in the Citrix Hypervisor dom0 domain.

1. Get the UUIDs of all VMs on the hypervisor host and use the output from the command to identify the VM to which the vGPU is assigned.
   Copy

   Copied!

               
   
               
   [root@xenserver ~] xe vm-list
   ...
   uuid ( RO)           : 7f6c855d-5635-2d57-9fbc-b1200172162f
        name-label ( RW): RHEL8.3
       power-state ( RO): running
   ...
           

2. Get the UUIDs of all vGPUs on the hypervisor host and from the UUID of the VM to which the vGPU is assigned, determine the UUID of the vGPU.
   Copy

   Copied!

               
   
               
   [root@xenserver ~] xe vgpu-list
   ...
   uuid ( RO)              : d15083f8-5c59-7474-d0cb-fbc3f7284f1b
              vm-uuid ( RO): 7f6c855d-5635-2d57-9fbc-b1200172162f
               device ( RO): 0
       gpu-group-uuid ( RO): 3a2fbc36-827d-a078-0b2f-9e869ae6fd93
   ...
           

3. Use the xe command to set each vGPU plugin parameter that you want to set.
   Copy

   Copied!

               
   
               
   [root@xenserver ~] xe vgpu-param-set uuid=vgpu-uuid extra_args='parameter=value'
           

   vgpu-uuid

   The UUID of the vGPU, which you obtained in the previous step.

   parameter

   The name of the vGPU plugin parameter that you want to set.

   value

   The value to which you want to set the vGPU plugin parameter.

   This example sets the enable_uvm vGPU plugin parameter to 1 for the vGPU that has the UUID d15083f8-5c59-7474-d0cb-fbc3f7284f1b. This parameter setting enables unified memory for the vGPU.

   Copy

   Copied!

               
   
               
   [root@xenserver ~] xe vgpu-param-set uuid=d15083f8-5c59-7474-d0cb-fbc3f7284f1b extra_args='enable_uvm=1'
           

2.5. Installing the Virtual GPU Manager Package for Linux KVM

NVIDIA vGPU software for Linux Kernel-based Virtual Machine (KVM) (Linux KVM) is intended only for use with supported versions of Linux KVM hypervisors. For details about which Linux KVM hypervisor versions are supported, see Virtual GPU Software for Generic Linux with KVM Release Notes.

Before installing the Virtual GPU Manager package for Linux KVM, ensure that the following prerequisites are met:

• The following packages are installed on the Linux KVM server:

  • The x86_64 build of the GNU Compiler Collection (GCC)
  • Linux kernel headers

• The package file is copied to a directory in the file system of the Linux KVM server.

If the Nouveau driver for NVIDIA graphics cards is present, disable it before installing the package.

1. Change to the directory on the Linux KVM server that contains the package file.
   Copy

   Copied!

               
   
               
   # cd package-file-directory
           

   package-file-directory

   The path to the directory that contains the package file.

2. Make the package file executable.
   Copy

   Copied!

               
   
               
   # chmod +x package-file-name
           

   package-file-name

   The name of the file that contains the Virtual GPU Manager package for Linux KVM, for example NVIDIA-Linux-x86_64-390.42-vgpu-kvm.run.

3. Run the package file as the root user.
   Copy

   Copied!

               
   
               
   # sudo sh./package-file-name
           

   The package file should launch and display the license agreement.
4. Accept the license agreement to continue with the installation.
5. When installation has completed, select OK to exit the installer.
6. Reboot the Linux KVM server.
   Copy

   Copied!

               
   
               
   # systemctl reboot
           

2.6. Installing and Configuring the NVIDIA Virtual GPU Manager for Microsoft Azure Stack HCI

Before you begin, ensure that the prerequisites in Prerequisites for Using NVIDIA vGPU are met and the Microsoft Azure Stack HCI host is configured as follows:

• The Microsoft Azure Stack HCI OS is installed as explained in Deploy the Azure Stack HCI operating system on the Microsoft documentation site.
• The following BIOS settings are enabled:
  • Virtualization support, for example, Intel Virtualization Technology (VT-D) or AMD Virtualization (AMD-V)
  • SR-IOV
  • Above 4G Decoding
  • For Supermicro servers: ASPM Support
  • For servers that have an AMD CPU:
    • Alternative Routing ID Interpretation (ARI)
    • Access Control Service (ACS)
    • Advanced Error Reporting (AER)

Follow this sequence of instructions to set up a single Microsoft Azure Stack HCI VM to use NVIDIA vGPU.

1. Installing the NVIDIA Virtual GPU Manager for Microsoft Azure Stack HCI
2. Setting the vGPU Series Allowed on a GPU
3. Adding a vGPU to a Microsoft Azure Stack HCI VM

These instructions assume familiarity with the Microsoft Windows PowerShell commands covered in Manage VMs on Azure Stack HCI using Windows PowerShell on the Microsoft documentation site.

After the set up is complete, you can install the graphics driver for your guest OS and license any NVIDIA vGPU software licensed products that you are using.

2.6.1. Installing the NVIDIA Virtual GPU Manager for Microsoft Azure Stack HCI

The driver package for the Virtual GPU Manager is distributed as an archive file. You must extract the contents of this archive file to enable the package to be added to the driver store from a setup information file.

Perform this task in a Windows PowerShell window as the Administrator user.

1. Download the archive file in which the driver package for the Virtual GPU Manager is distributed.
2. Extract the contents of the archive file to a directory that is accessible from the Microsoft Azure Stack HCI host.
3. Change to the GridSW-Azure-Stack-HCI directory that you extracted from the archive file.
4. Use the PnPUtil tool to add the driver package for the Virtual GPU Manager to the driver store from the nvgridswhci.inf setup information file. In the command for adding the driver package, also set the options to traverse subdirectories for driver packages and reboot the Microsoft Azure Stack HCI host if necessary to complete the operation.
   Copy

   Copied!

               
   
               
   PS C:> pnputil /add-driver nvgridswhci.inf /subdirs /install /reboot
           

5. After the host has rebooted, verify that the NVIDIA Virtual GPU Manager can successfully communicate with the NVIDIA physical GPUs in your system. Run the nvidia-smi command with no arguments for this purpose. Running the nvidia-smi command should produce a listing of the GPUs in your platform.
6. Confirm that the Microsoft Azure Stack HCI host has GPU adapters that can be partitioned by listing the GPUs that support GPU-P.
   Copy

   Copied!

               
   
               
   PS C:> Get-VMHostPartitionableGpu
           

   If the NVIDIA Virtual GPU Manager is correctly installed, each GPU in the host GPU is listed. The numbers of partitions that each GPU supports and the unique name for referencing each GPU are also listed.
7. For each GPU, set the number of partitions that the GPU should support to the maximum number of vGPUs that can be added to the GPU.
   Copy

   Copied!

               
   
               
   PS C:> Set-VMHostPartitionableGpu -Name "gpu-name" -PartitionCount partitions
           

   gpu-name

   The unique name for referencing the GPU that you obtained in the previous step.

   partitions

   The maximum number of vGPUs that can be added to the GPU. This number depends on the virtual GPU type. For example, the maximum number of each type of vGPU that can be added to the NVIDIA A16 GPU is as follows:

   Virtual GPU Type	Maximum vGPUs per GPU
   A16-16Q A16-16A	1
   A16-8Q A16-8A	2
   A16-4Q A16-4A	4
   A16-2Q A16-2B A16-2A	8
   A16-1Q A16-1B A16-1A	16

2.6.2. Setting the vGPU Series Allowed on a GPU

The Virtual GPU Manager allows virtual GPUs (vGPUs) to be created on a GPU from only one vGPU series. By default, only Q-series vGPUs may be created on a GPU. You can change the vGPU series allowed on a GPU by setting the GridGpupProfileType value for the GPU in the Windows registry.

This task requires administrator user privileges.

1. Use Windows PowerShell to get the driver key of the GPU on which you want to set the allowed vGPU series. You will need this information in the next step to identify the Windows registry key in which information about the GPU is stored.
   1. Get the InstanceID property of the GPU on which you want to set the allowed vGPU series.
      Copy

      Copied!

                  
      
                  
      PS C:\> Get-PnpDevice -PresentOnly |
      >> Where-Object {$_.InstanceId -like "PCI\VEN_10DE*" }  |
      >> Select-Object -Property FriendlyName,InstanceId |
      >> Format-List
      
      FriendlyName : NVIDIA A100
      InstanceId   : PCI\VEN_10DE&DEV_2236&SUBSYS_148210DE&REV_A1\6&17F903&0&00400000
              

   2. Get the DEVPKEY_Device_Driver property of the GPU from the InstanceID property that you got in the previous step.
      Copy

      Copied!

                  
      
                  
      PS C:\> Get-PnpDeviceProperty -InstanceId "instance-id" |
      >> where {$_.KeyName -eq "DEVPKEY_Device_Driver"} |
      >> Select-Object -Property Data
      
      Data
      ----
      {4d36e968-e325-11ce-bfc1-08002be10318}\0001
              

      instance-id

      The InstanceID property of the GPU that you got in the previous step, for example, PCI\VEN_10DE&DEV_2236&SUBSYS_148210DE&REV_A1\6&17F903&0&00400000.

2. Set the GridGpupProfileType DWord (REG_DWORD) registry value in the Windows registry key HKEY_LOCAL_MACHINE\SYSTEM\ControlSet001\Control\Class\driver-key.

   driver-key

   The driver key for the GPU that you got in the previous step, for example, {4d36e968-e325-11ce-bfc1-08002be10318}\0001.

   The value to set depends on the vGPU series that you want to be allowed on the GPU.

   vGPU Series	Value
   Q-series	1
   A-series	2
   B-series	3

2.6.3. Adding a vGPU to a Microsoft Azure Stack HCI VM

You add a vGPU to a Microsoft Azure Stack HCI VM by adding a GPU-P adapter to a VM.

Perform this task in a Windows PowerShell window as the Administrator user.

1. Set the variable $vm to the name of the virtual machine to which you are adding a vGPU.
   Copy

   Copied!

               
   
               
   PS C:> $vm = "vm-name"
           

   vm-name

   The name of the virtual machine to which you are adding a vGPU.

2. Allow the VM to control cache types for MMIO access.
   Copy

   Copied!

               
   
               
   PS C:> Set-VM -GuestControlledCacheTypes $true -VMName $vm
           

3. Set the lower MMIO space to 1 GB to allow sufficient MMIO space to be mapped.
   Copy

   Copied!

               
   
               
   PS C:> Set-VM -LowMemoryMappedIoSpace 1Gb -VMName $vm
           

   This amount is twice the amount that the device must allow for alignment. Lower MMIO space is the address space below 4 GB and is required for any device that has 32-bit BAR memory.

4. Set the upper MMIO space to 32 GB to allow sufficient MMIO space to be mapped.
   Copy

   Copied!

               
   
               
   PS C:> Set-VM –HighMemoryMappedIoSpace 32GB –VMName $vm
           

   This amount is twice the amount that the device must allow for alignment. Upper MMIO space is the address space above approximately 64 GB.

5. Confirm that the Microsoft Azure Stack HCI host has a GPU that supports the GPU-P adapter that you want to create.
   Copy

   Copied!

               
   
               
   PS C:> get-VMHostPartitionableGpu
           

   The maximum and minimum values that you can specify for the properties of the GPU that you want to create are also listed.
6. Add a GPU-P adapter to the VM.
   Copy

   Copied!

               
   
               
   PS C:> Add-VMGpuPartitionAdapter –VMName $vm `
   –MinPartitionVRAM min-ram `
   -MaxPartitionVRAM max-ram `
   -OptimalPartitionVRAM opt-ram `
   -MinPartitionEncode min-enc `
   -MaxPartitionEncode max-enc `
   -OptimalPartitionEncode opt-enc `
   -MinPartitionDecode min-dec `
   -MaxPartitionDecode max-dec `
   -OptimalPartitionDecode opt-dec `
   -MinPartitionCompute min-compute `
   -MaxPartitionCompute max-compute `
   -OptimalPartitionCompute opt-compute
           

   Note:

   Because partitions are resolved only when the VM is started, this command cannot validate that the Microsoft Azure Stack HCI host has a GPU that supports the GPU-P adapter that you want to create. The values that you specify must be within the maximum and minimum values that were listed in the previous step.

7. List the adapters assigned to the VM to confirm that the GPU-P adapter has been added to the VM.
   Copy

   Copied!

               
   
               
   PS C:> Get-VMGpuPartitionAdapter –VMName $vm
           

   This command also returns the adapter ID to use for reconfiguring or deleting a GPU partition.

8. Connect to and start the VM.

2.6.4. Uninstalling the NVIDIA Virtual GPU Manager for Microsoft Azure Stack HCI

If you no longer require the Virtual GPU Manager on your Microsoft Azure Stack HCI server, you can uninstall the driver package for the Virtual GPU Manager.

Perform this task in a Windows PowerShell window as the Administrator user.

1. Determine the published name of the driver package for the Virtual GPU Manager by enumerating all third-party driver packages in the driver store.
   Copy

   Copied!

               
   
               
   PS C:> pnputil /enum-drivers
           

   Information similar to the following example is displayed. In this example, the published name of the driver package for the Virtual GPU Manager is oem5.inf.
   Copy

   Copied!

               
   
               
   Microsoft PnP Utility
   ...
   
   Published name :            oem5.inf
   Driver package provider :   NVIDIA
   Class :                     Display adapters
   Driver date and version :   01/01/2023 31.0.15.2807
   Signer name :               Microsoft Windows Hardware Compatibility Publisher
   
   ...
           

2. Delete and uninstall the driver package for the Virtual GPU Manager.
   Copy

   Copied!

               
   
               
   PS C:> pnputil /delete-driver vgpu-manager-package-published-name /uninstall /reboot
           

   vgpu-manager-package-published-name

   The published name of the driver package for the Virtual GPU Manager that you obtained in the previous step, for example, oem5.inf.

   This example deletes and uninstalls the driver package for which the published name is oem5.inf.

   Copy

   Copied!

               
   
               
   PS C:> pnputil.exe /delete-driver oem5.inf /uninstall /reboot
   Microsoft PnP Utility
   
   Driver package uninstalled.
   Driver package deleted successfully.
           

   If necessary, the Microsoft Azure Stack HCI server is rebooted.

2.7. Installing and Configuring the NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM

The following topics step you through the process of setting up a single Red Hat Enterprise Linux Kernel-based Virtual Machine (KVM) VM to use NVIDIA vGPU.

Follow this sequence of instructions:

1. Installing the Virtual GPU Manager Package for Red Hat Enterprise Linux KVM
2. Verifying the Installation of the NVIDIA vGPU Software for Red Hat Enterprise Linux KVM
3. vGPUs that support SR-IOV only: Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor
4. Optional: Putting a GPU Into Mixed-Size Mode
5. Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor
6. Creating an NVIDIA vGPU on a Linux with KVM Hypervisor
7. Adding One or More vGPUs to a Linux with KVM Hypervisor VM
8. Optional: Placing a vGPU on a Physical GPU in Mixed-Size Mode
9. Setting vGPU Plugin Parameters on a Linux with KVM Hypervisor

After the process is complete, you can install the graphics driver for your guest OS and license any NVIDIA vGPU software licensed products that you are using.

2.7.1. Installing the Virtual GPU Manager Package for Red Hat Enterprise Linux KVM

The NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM is provided as a .rpm file.

Before installing the RPM package for Red Hat Enterprise Linux KVM, ensure that the sshd service on the Red Hat Enterprise Linux KVM server is configured to permit root login. If the Nouveau driver for NVIDIA graphics cards is present, disable it before installing the package. For instructions, see How to disable the Nouveau driver and install the Nvidia driver in RHEL 7 (Red Hat subscription required).

Some versions of Red Hat Enterprise Linux KVM have z-stream updates that break Kernel Application Binary Interface (kABI) compatibility with the previous kernel or the GA kernel. For these versions of Red Hat Enterprise Linux KVM, the following Virtual GPU Manager RPM packages are supplied:

• A package for the GA Linux KVM kernel
• A package for the updated z-stream kernel

To differentiate these packages, the name of each RPM package includes the kernel version. Ensure that you install the RPM package that is compatible with your Linux KVM kernel version.

1. Securely copy the RPM file from the system where you downloaded the file to the Red Hat Enterprise Linux KVM server.
   • From a Windows system, use a secure copy client such as WinSCP.
   • From a Linux system, use the scp command.
2. Use secure shell (SSH) to log in as root to the Red Hat Enterprise Linux KVM server.
   Copy

   Copied!

               
   
               
   # ssh root@kvm-server
           

   kvm-server

   The host name or IP address of the Red Hat Enterprise Linux KVM server.

3. Change to the directory on the Red Hat Enterprise Linux KVM server to which you copied the RPM file.
   Copy

   Copied!

               
   
               
   # cd rpm-file-directory
           

   rpm-file-directory

   The path to the directory to which you copied the RPM file.

4. Use the rpm command to install the package.
   Copy

   Copied!

               
   
               
   # rpm -iv NVIDIA-vGPU-rhel-8.9-550.90.05.x86_64.rpm
   Preparing packages for installation...
   NVIDIA-vGPU-rhel-8.9-550.90.05
   #
           

5. Reboot the Red Hat Enterprise Linux KVM server.
   Copy

   Copied!

               
   
               
   # systemctl reboot
           

2.7.2. Verifying the Installation of the NVIDIA vGPU Software for Red Hat Enterprise Linux KVM

After the Red Hat Enterprise Linux KVM server has rebooted, verify the installation of the NVIDIA vGPU software package for Red Hat Enterprise Linux KVM.

1. Verify that the NVIDIA vGPU software package is installed and loaded correctly by checking for the VFIO drivers in the list of kernel loaded modules.
   Copy

   Copied!

               
   
               
   # lsmod | grep vfio
   nvidia_vgpu_vfio       27099  0
   nvidia              12316924  1 nvidia_vgpu_vfio
   vfio_mdev              12841  0
   mdev                   20414  2 vfio_mdev,nvidia_vgpu_vfio
   vfio_iommu_type1       22342  0
   vfio                   32331  3 vfio_mdev,nvidia_vgpu_vfio,vfio_iommu_type1
   #
           

2. Verify that the libvirtd service is active and running.
   Copy

   Copied!

               
   
               
   # service libvirtd status
           

3. Verify that the NVIDIA kernel driver can successfully communicate with the NVIDIA physical GPUs in your system by running the nvidia-smi command. The nvidia-smi command is described in more detail in NVIDIA System Management Interface nvidia-smi.

Running the nvidia-smi command should produce a listing of the GPUs in your platform.

            

            
# nvidia-smi
Fri Jun 14 18:46:50 2024
+------------------------------------------------------+
| NVIDIA-SMI 550.90.05   Driver Version: 550.90.05   |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla M60           On   | 0000:85:00.0     Off |                  Off |
| N/A   23C    P8    23W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla M60           On   | 0000:86:00.0     Off |                  Off |
| N/A   29C    P8    23W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla P40           On   | 0000:87:00.0     Off |                  Off |
| N/A   21C    P8    18W / 250W |     53MiB / 24575MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
#
        

If nvidia-smi fails to run or doesn’t produce the expected output for all the NVIDIA GPUs in your system, see Troubleshooting for troubleshooting steps.

2.8. Installing and Configuring the NVIDIA Virtual GPU Manager for Ubuntu

Follow this sequence of instructions to set up a single Ubuntu VM to use NVIDIA vGPU.

1. Installing the NVIDIA Virtual GPU Manager for Ubuntu
2. Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor
3. vGPUs that support SR-IOV only: Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor
4. Optional: Putting a GPU Into Mixed-Size Mode
5. Creating an NVIDIA vGPU on a Linux with KVM Hypervisor
6. Adding One or More vGPUs to a Linux with KVM Hypervisor VM
7. Optional: Placing a vGPU on a Physical GPU in Mixed-Size Mode
8. Setting vGPU Plugin Parameters on a Linux with KVM Hypervisor

After the process is complete, you can install the graphics driver for your guest OS and license any NVIDIA vGPU software licensed products that you are using.

2.8.1. Installing the NVIDIA Virtual GPU Manager for Ubuntu

The NVIDIA Virtual GPU Manager for Ubuntu is provided as a Debian package (.deb) file.

2.8.1.1. Installing the Virtual GPU Manager Package for Ubuntu

Before installing the Debian package for Ubuntu, ensure that the sshd service on the Ubuntu server is configured to permit root login. If the Nouveau driver for NVIDIA graphics cards is present, disable it before installing the package.

1. Securely copy the Debian package file from the system where you downloaded the file to the Ubuntu server.
   • From a Windows system, use a secure copy client such as WinSCP.
   • From a Linux system, use the scp command.
2. Use secure shell (SSH) to log in as root to the Ubuntu server.
   Copy

   Copied!

               
   
               
   # ssh root@ubuntu-server
           

   ubuntu-server

   The host name or IP address of the Ubuntu server.

3. Change to the directory on the Ubuntu server to which you copied the Debian package file.
   Copy

   Copied!

               
   
               
   # cd deb-file-directory
           

   deb-file-directory

   The path to the directory to which you copied the Debian package file.

4. Use the apt command to install the package.
   Copy

   Copied!

               
   
               
   # apt install ./nvidia-vgpu-ubuntu-550.90.05_amd64.deb
           

5. Reboot the Ubuntu server.
   Copy

   Copied!

               
   
               
   # systemctl reboot
           

2.8.1.2. Verifying the Installation of the NVIDIA vGPU Software for Ubuntu

After the Ubuntu server has rebooted, verify the installation of the NVIDIA vGPU software package for Ubuntu.

1. Verify that the NVIDIA vGPU software package is installed and loaded correctly by checking for the VFIO drivers in the list of kernel loaded modules.
   Copy

   Copied!

               
   
               
   # lsmod | grep vfio
   nvidia_vgpu_vfio       27099  0
   nvidia              12316924  1 nvidia_vgpu_vfio
   vfio_mdev              12841  0
   mdev                   20414  2 vfio_mdev,nvidia_vgpu_vfio
   vfio_iommu_type1       22342  0
   vfio                   32331  3 vfio_mdev,nvidia_vgpu_vfio,vfio_iommu_type1
   #
           

2. Verify that the libvirtd service is active and running.
   Copy

   Copied!

               
   
               
   # service libvirtd status
           

3. Verify that the NVIDIA kernel driver can successfully communicate with the NVIDIA physical GPUs in your system by running the nvidia-smi command. The nvidia-smi command is described in more detail in NVIDIA System Management Interface nvidia-smi.

Running the nvidia-smi command should produce a listing of the GPUs in your platform.

            

            
# nvidia-smi
Fri Jun 14 18:46:50 2024
+------------------------------------------------------+
| NVIDIA-SMI 550.90.05   Driver Version: 550.90.05   |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla M60           On   | 0000:85:00.0     Off |                  Off |
| N/A   23C    P8    23W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla M60           On   | 0000:86:00.0     Off |                  Off |
| N/A   29C    P8    23W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla P40           On   | 0000:87:00.0     Off |                  Off |
| N/A   21C    P8    18W / 250W |     53MiB / 24575MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
#
        

If nvidia-smi fails to run or doesn’t produce the expected output for all the NVIDIA GPUs in your system, see Troubleshooting for troubleshooting steps.

2.9. Installing and Configuring the NVIDIA Virtual GPU Manager for VMware vSphere

You can use the NVIDIA Virtual GPU Manager for VMware vSphere to set up a VMware vSphere VM to use NVIDIA vGPU.

NVIDIA vGPU Instructions

To set up a VMware vSphere VM to use NVIDIA vGPU, follow this sequence of instructions:

1. Installing and Updating the NVIDIA Virtual GPU Manager for VMware vSphere
2. Configuring VMware vMotion with vGPU for VMware vSphere
3. Changing the Default Graphics Type in VMware vSphere
4. Configuring a vSphere VM with NVIDIA vGPU
5. Optional: Setting vGPU Plugin Parameters on VMware vSphere

After configuring a vSphere VM to use NVIDIA vGPU, you can install the NVIDIA vGPU software graphics driver for your guest OS and license any NVIDIA vGPU software licensed products that you are using.

Requirements for Configuring NVIDIA vGPU in a DRS Cluster

You can configure a VM with NVIDIA vGPU on an ESXi host in a VMware Distributed Resource Scheduler (DRS) cluster. However, to ensure that the automation level of the cluster supports VMs configured with NVIDIA vGPU, you must set the automation level to Partially Automated or Manual.

For more information about these settings, see Edit Cluster Settings in the VMware documentation.

2.9.1. Installing and Updating the NVIDIA Virtual GPU Manager for VMware vSphere

The NVIDIA Virtual GPU Manager runs on the ESXi host. It is distributed as a number of software components in a ZIP archive.

The NVIDIA Virtual GPU Manager software components are as follows:

• A software component for the NVIDIA vGPU hypervisor host driver
• A software component for the NVIDIA GPU Management daemon

You can install these software components in one of the following ways:

• By copying the software components to the ESXi host and then installing them as explained in Installing the NVIDIA Virtual GPU Manager on VMware vSphere
• By importing the software components manually as explained in Import Patches Manually in the VMware vSphere documentation

2.9.1.1. Installing the NVIDIA Virtual GPU Manager on VMware vSphere

To install the NVIDIA Virtual GPU Manager you need to access the ESXi host via the ESXi Shell or SSH. Refer to VMware’s documentation on how to enable ESXi Shell or SSH for an ESXi host.
Before you begin, ensure that the following prerequisites are met:

• The ZIP archive that contains NVIDIA vGPU software has been downloaded from the NVIDIA Licensing Portal.
• The software components for the NVIDIA Virtual GPU Manager have been extracted from the downloaded ZIP archive.

1. Copy the NVIDIA Virtual GPU Manager component files to the ESXi host.
2. Put the ESXi host into maintenance mode.
   Copy

   Copied!

               
   
               
   $ esxcli system maintenanceMode set –-enable true
           

3. Install the NVIDIA vGPU hypervisor host driver and the NVIDIA GPU Management daemon from their software component files.
   1. Run the esxcli command to install the NVIDIA vGPU hypervisor host driver from its software component file.
      Copy

      Copied!

                  
      
                  
      $ esxcli software vib install -d /vmfs/volumes/datastore/host-driver-component.zip
              

   2. Run the esxcli command to install the NVIDIA GPU Management daemon from its software component file.
      Copy

      Copied!

                  
      
                  
      $ esxcli software vib install -d /vmfs/volumes/datastore/gpu-management-daemon-component.zip
              

   datastore

   The name of the VMFS datastore to which you copied the software components.

   host-driver-component

   The name of the file that contains the NVIDIA vGPU hypervisor host driver in the form of a software component. Ensure that you specify the file that was extracted from the downloaded ZIP archive. For example, for VMware vSphere 7.0.2, host-driver-component is NVD-VMware-x86_64-550.90.05-1OEM.702.0.0.17630552-bundle-build-number.

   gpu-management-daemon-component

   The name of the file that contains the NVIDIA GPU Management daemon in the form of a software component. Ensure that you specify the file that was extracted from the downloaded ZIP archive. For example, for VMware vSphere 7.0.2, gpu-management-daemon-component is VMW-esx-7.0.2-nvd-gpu-mgmt-daemon-1.0-0.0.0001.

4. Exit maintenance mode.
   Copy

   Copied!

               
   
               
   $ esxcli system maintenanceMode set –-enable false
           

5. Reboot the ESXi host.
   Copy

   Copied!

               
   
               
   $ reboot
           

2.9.1.2. Updating the NVIDIA Virtual GPU Manager for VMware vSphere

Update the NVIDIA Virtual GPU Manager if you want to install a new version of NVIDIA Virtual GPU Manager on a system where an existing version is already installed.

To update the vGPU Manager VIB you need to access the ESXi host via the ESXi Shell or SSH. Refer to VMware’s documentation on how to enable ESXi Shell or SSH for an ESXi host.

1. Stop the NVIDIA GPU Management Daemon.
   Copy

   Copied!

               
   
               
   $ /etc/init.d/nvdGpuMgmtDaemon stop
           

2. Update the NVIDIA vGPU hypervisor host driver and the NVIDIA GPU Management daemon.
   1. Run the esxcli command to update the NVIDIA vGPU hypervisor host driver from its software component file.
      Copy

      Copied!

                  
      
                  
      $ esxcli software vib update -d /vmfs/volumes/datastore/host-driver-component.zip
              

   2. Run the esxcli command to update the NVIDIA GPU Management daemon from its software component file.
      Copy

      Copied!

                  
      
                  
      $ esxcli software vib update -d /vmfs/volumes/datastore/gpu-management-daemon-component.zip
              

   datastore

   The name of the VMFS datastore to which you copied the software components.

   host-driver-component

   The name of the file that contains the NVIDIA vGPU hypervisor host driver in the form of a software component. Ensure that you specify the file that was extracted from the downloaded ZIP archive. For example, for VMware vSphere 7.0.2, host-driver-component is NVD-VMware-x86_64-550.90.05-1OEM.702.0.0.17630552-bundle-build-number.

   gpu-management-daemon-component

   The name of the file that contains the NVIDIA GPU Management daemon in the form of a software component. Ensure that you specify the file that was extracted from the downloaded ZIP archive. For example, for VMware vSphere 7.0.2, gpu-management-daemon-component is VMW-esx-7.0.2-nvd-gpu-mgmt-daemon-1.0-0.0.0001.

3. Reboot the ESXi host and remove it from maintenance mode.

2.9.1.3. Verifying the Installation of the NVIDIA vGPU Software Package for vSphere

After the ESXi host has rebooted, verify the installation of the NVIDIA vGPU software package for vSphere.

1. Verify that the NVIDIA vGPU software package installed and loaded correctly by checking for the NVIDIA kernel driver in the list of kernel loaded modules.
   Copy

   Copied!

               
   
               
   [root@esxi:~] vmkload_mod -l | grep nvidia
   nvidia                   5    8420
           

2. If the NVIDIA driver is not listed in the output, check dmesg for any load-time errors reported by the driver.
3. Verify that the NVIDIA GPU Management daemon has started.
   Copy

   Copied!

               
   
               
   $ /etc/init.d/nvdGpuMgmtDaemon status
           

4. Verify that the NVIDIA kernel driver can successfully communicate with the NVIDIA physical GPUs in your system by running the nvidia-smi command. The nvidia-smi command is described in more detail in NVIDIA System Management Interface nvidia-smi.

Running the nvidia-smi command should produce a listing of the GPUs in your platform.

            

            
[root@esxi:~] nvidia-smi
Fri Jun 14 17:56:22 2024
+------------------------------------------------------+
| NVIDIA-SMI 550.90.05   Driver Version: 550.90.05   |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla M60           On   | 00000000:05:00.0 Off |                  Off |
| N/A   25C    P8    24W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla M60           On   | 00000000:06:00.0 Off |                  Off |
| N/A   24C    P8    24W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla M60           On   | 00000000:86:00.0 Off |                  Off |
| N/A   25C    P8    25W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla M60           On   | 00000000:87:00.0 Off |                  Off |
| N/A   28C    P8    24W / 150W |     13MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
        

If nvidia-smi fails to report the expected output for all the NVIDIA GPUs in your system, see Troubleshooting for troubleshooting steps.

2.9.1.4. Managing the NVIDIA GPU Management Daemon for VMware vSphere

The NVIDIA GPU Management Daemon for VMware vSphere is a service that is controlled through scripts in the /etc/init.d directory. You can use these scripts to start the daemon, stop the daemon, and get its status.

• To start the NVIDIA GPU Management Daemon, enter the following command:
  Copy

  Copied!

              
  
              
  $ /etc/init.d/nvdGpuMgmtDaemon start
          

• To stop the NVIDIA GPU Management Daemon, enter the following command:
  Copy

  Copied!

              
  
              
  $ /etc/init.d/nvdGpuMgmtDaemon stop
          

• To get the status of the NVIDIA GPU Management Daemon, enter the following command:
  Copy

  Copied!

              
  
              
  $ /etc/init.d/nvdGpuMgmtDaemon status
          

2.9.2. Configuring VMware vMotion with vGPU for VMware vSphere

NVIDIA vGPU software supports vGPU migration, which includes VMware vMotion and suspend-resume, for VMs that are configured with vGPU. To enable VMware vMotion with vGPU, an advanced vCenter Server setting must be enabled. However, suspend-resume for VMs that are configured with vGPU is enabled by default.

For details about which VMware vSphere versions, NVIDIA GPUs, and guest OS releases support vGPU migration, see Virtual GPU Software for VMware vSphere Release Notes.
Before configuring VMware vMotion with vGPU for an ESXi host, ensure that the current NVIDIA Virtual GPU Manager for VMware vSphere package is installed on the host.

1. Log in to vCenter Server by using the vSphere Web Client.
2. In the Hosts and Clusters view, select the vCenter Server instance.
   Note:

   Ensure that you select the vCenter Server instance, not the vCenter Server VM.

3. Click the Configure tab.
4. In the Settings section, select Advanced Settings and click Edit.
5. In the Edit Advanced vCenter Server Settings window that opens, type vGPU in the search field.
6. When the vgpu.hotmigrate.enabled setting appears, set the Enabled option and click OK.

   

2.9.3. Changing the Default Graphics Type in VMware vSphere

After the vGPU Manager VIB for VMware vSphere VIB is installed, the default graphics type is Shared. To enable vGPU support for VMs in VMware vSphere, you must change the default graphics type to Shared Direct.

If you do not change the default graphics type, VMs to which a vGPU is assigned fail to start and the following error message is displayed:

            

            
The amount of graphics resource available in the parent resource pool is insufficient for the operation.
        

Before changing the default graphics type, ensure that the ESXi host is running and that all VMs on the host are powered off.

1. Log in to vCenter Server by using the vSphere Web Client.
2. In the navigation tree, select your ESXi host and click the Configure tab.
3. From the menu, choose Graphics and then click the Host Graphics tab.
4. On the Host Graphics tab, click Edit.

   Figure 6. Shared default graphics type

   

5. In the Edit Host Graphics Settings dialog box that opens, select Shared Direct and click OK.

   Figure 7. Host graphics settings for vGPU

   

   Note:

   In this dialog box, you can also change the allocation scheme for vGPU-enabled VMs. For more information, see Modifying GPU Allocation Policy on VMware vSphere.

   After you click OK, the default graphics type changes to Shared Direct.

6. Click the Graphics Devices tab to verify the configured type of each physical GPU on which you want to configure vGPU. The configured type of each physical GPU must be Shared Direct. For any physical GPU for which the configured type is Shared, change the configured type as follows:
   1. On the Graphics Devices tab, select the physical GPU and click the Edit icon.

      Figure 8. Shared graphics type

      

   2. In the Edit Graphics Device Settings dialog box that opens, select Shared Direct and click OK.

      Figure 9. Graphics device settings for a physical GPU

      

7. Restart the ESXi host or stop and restart the Xorg service if necessary and nv-hostengine on the ESXi host.

   To stop and restart the Xorg service and nv-hostengine, perform these steps:

   1. VMware vSphere releases before 7.0 Update 1 only: Stop the Xorg service.

      The Xorg service is not required for graphics devices in NVIDIA vGPU mode.

   2. Stop nv-hostengine.
      Copy

      Copied!

                  
      
                  
      [root@esxi:~] nv-hostengine -t
              

   3. Wait for 1 second to allow nv-hostengine to stop.
   4. Start nv-hostengine.
      Copy

      Copied!

                  
      
                  
      [root@esxi:~] nv-hostengine -d
              

   5. VMware vSphere releases before 7.0 Update 1 only: Start the Xorg service.

      The Xorg service is not required for graphics devices in NVIDIA vGPU mode.

      Copy

      Copied!

                  
      
                  
      [root@esxi:~] /etc/init.d/xorg start
              

8. In the Graphics Devices tab of the VMware vCenter Web UI, confirm that the active type and the configured type of each physical GPU are Shared Direct.

   Figure 10. Shared direct graphics type

   

After changing the default graphics type, configure vGPU as explained in Configuring a vSphere VM with NVIDIA vGPU.

See also the following topics in the VMware vSphere documentation:

• Log in to vCenter Server by Using the vSphere Web Client
• Configuring Host Graphics

2.9.4. Configuring a vSphere VM with NVIDIA vGPU

To support applications and workloads that are compute or graphics intensive, you can add multiple vGPUs to a single VM.

For details about which VMware vSphere versions and NVIDIA vGPUs support the assignment of multiple vGPUs to a VM, see Virtual GPU Software for VMware vSphere Release Notes.

VM console in vSphere Web Client will become active again once the vGPU parameters are removed from the VM’s configuration.
How to configure a vSphere VM with a vGPU depends on your VMware vSphere version as explained in the following topics:

• Configuring a vSphere 8 VM with NVIDIA vGPU
• Configuring a vSphere 7 VM with NVIDIA vGPU

After you have configured a vSphere VM with a vGPU, start the VM. VM console in vSphere Web Client is not supported in this vGPU release. Therefore, use VMware Horizon or VNC to access the VM’s desktop.

After the VM has booted, install the NVIDIA vGPU software graphics driver as explained in Installing the NVIDIA vGPU Software Graphics Driver.

2.9.4.1. Configuring a vSphere 8 VM with NVIDIA vGPU

1. Open the vCenter Web UI.
2. In the vCenter Web UI, right-click the VM and choose Edit Settings.
3. In the Edit Settings window that opens, configure the vGPUs that you want to add to the VM. Add each vGPU that you want to add to the VM as follows:
   1. From the ADD NEW DEVICE menu, choose PCI Device.

      Figure 11. Command for Adding a PCI Device

      

   2. In the Device Selection window that opens, select the type of vGPU you want to configure and click SELECT.
      Note:

      NVIDIA vGPU software does not support vCS on VMware vSphere. Therefore, C-series vGPU types are not available for selection in the Device Selection window.

      Figure 12. VM Device Selections for vGPU

      

4. Back in the Edit Settings window, click OK.

2.9.4.2. Configuring a vSphere 7 VM with NVIDIA vGPU

If you are adding multiple vGPUs to a single VM, perform this task for each vGPU that you want to add to the VM.

1. Open the vCenter Web UI.
2. In the vCenter Web UI, right-click the VM and choose Edit Settings.
3. Click the Virtual Hardware tab.
4. In the New device list, select Shared PCI Device and click Add. The PCI device field should be auto-populated with NVIDIA GRID vGPU.

   Figure 13. VM settings for vGPU

   

5. From the GPU Profile drop-down menu, choose the type of vGPU you want to configure and click OK.
   Note:

   NVIDIA vGPU software does not support vCS on VMware vSphere. Therefore, C-series vGPU types are not available for selection from the GPU Profile drop-down menu.

6. Ensure that VMs running vGPU have all their memory reserved:
   1. Select Edit virtual machine settings from the vCenter Web UI.
   2. Expand the Memory section and click Reserve all guest memory (All locked).

2.9.5. Setting vGPU Plugin Parameters on VMware vSphere

Plugin parameters for a vGPU control the behavior of the vGPU, such as the frame rate limiter (FRL) configuration in frames per second or whether console virtual network computing (VNC) for the vGPU is enabled. The VM to which the vGPU is assigned is started with these parameters. If parameters are set for multiple vGPUs assigned to the same VM, the VM is started with the parameters assigned to each vGPU.

Ensure that the VM to which the vGPU is assigned is powered off.
For each vGPU for which you want to set plugin parameters, perform this task in the vSphere Client. vGPU plugin parameters are PCI pass through configuration parameters in advanced VM attributes.

1. In the vSphere Client, browse to the VM to which the vGPU is assigned.
2. Context-click the VM and choose Edit Settings.
3. In the Edit Settings window, click the VM Options tab.
4. From the Advanced drop-down list, select Edit Configuration.
5. In the Configuration Parameters dialog box, click Add Row.
6. In the Name field, type the parameter name pciPassthruvgpu-id.cfg.parameter, in the Value field type the parameter value, and click OK.

   vgpu-id

   A positive integer that identifies the vGPU assigned to a VM. For the first vGPU assigned to a VM, vgpu-id is 0. For example, if two vGPUs are assigned to a VM and you are setting a plugin parameter for both vGPUs, set the following parameters:

   • pciPassthru0.cfg.parameter
   • pciPassthru1.cfg.parameter

   parameter

   The name of the vGPU plugin parameter that you want to set. For example, the name of the vGPU plugin parameter for enabling unified memory is enable_uvm.

   To enable unified memory for two vGPUs that are assigned to a VM, set pciPassthru0.cfg.enable_uvm and pciPassthru1.cfg.enable_uvm to 1.

2.10. Configuring the vGPU Manager for a Linux with KVM Hypervisor

NVIDIA vGPU software supports the following Linux with KVM hypervisors: Red Hat Enterprise Linux with KVM and Ubuntu.

2.10.1. Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor

Sometimes when configuring a physical GPU for use with NVIDIA vGPU software, you must find out which directory in the sysfs file system represents the GPU. This directory is identified by the domain, bus, slot, and function of the GPU.

For more information about the directory in the sysfs file system that represents a physical GPU, see NVIDIA vGPU Information in the sysfs File System.

1. Obtain the PCI device bus/device/function (BDF) of the physical GPU.
   Copy

   Copied!

               
   
               
   # lspci | grep NVIDIA
           

   The NVIDIA GPUs listed in this example have the PCI device BDFs 06:00.0 and 07:00.0.

   Copy

   Copied!

               
   
               
   # lspci | grep NVIDIA
   06:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M10] (rev a1)
   07:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M10] (rev a1)
           

2. Obtain the full identifier of the GPU from its PCI device BDF.
   Copy

   Copied!

               
   
               
   # virsh nodedev-list --cap pci| grep transformed-bdf
           

   transformed-bdf

   The PCI device BDF of the GPU with the colon and the period replaced with underscores, for example, 06_00_0.

   This example obtains the full identifier of the GPU with the PCI device BDF 06:00.0.

   Copy

   Copied!

               
   
               
   # virsh nodedev-list --cap pci| grep 06_00_0
   pci_0000_06_00_0
           

3. Obtain the domain, bus, slot, and function of the GPU from the full identifier of the GPU.
   Copy

   Copied!

               
   
               
   virsh nodedev-dumpxml full-identifier| egrep 'domain|bus|slot|function'
           

   full-identifier

   The full identifier of the GPU that you obtained in the previous step, for example, pci_0000_06_00_0.

   This example obtains the domain, bus, slot, and function of the GPU with the PCI device BDF 06:00.0.

   Copy

   Copied!

               
   
               
   # virsh nodedev-dumpxml pci_0000_06_00_0| egrep 'domain|bus|slot|function'
       <domain>0x0000</domain>
       <bus>0x06</bus>
       <slot>0x00</slot>
       <function>0x0</function>
         <address domain='0x0000' bus='0x06' slot='0x00' function='0x0'/>
           

2.10.2. Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor

An NVIDIA vGPU that supports SR-IOV resides on a physical GPU that supports SR-IOV, such as a GPU based on the NVIDIA Ampere architecture. Before creating an NVIDIA vGPU on a GPUthat supports SR-IOV, you must enable the virtual functions of the GPU and obtain the domain, bus, slot, and function of the specific virtual function on which you want to create the vGPU.

Before performing this task, ensure that the GPU is not being used by any other processes, such as CUDA applications, monitoring applications, or the nvidia-smi command.

1. Enable the virtual functions for the physical GPU in the sysfs file system.
   Note:

   The virtual functions for the physical GPU in the sysfs file system are disabled after the hypervisor host is rebooted or if the driver is reloaded or upgraded.

   Use only the custom script sriov-manage provided by NVIDIA vGPU software for this purpose. Do not try to enable the virtual function for the GPU by any other means.

   Copy

   Copied!

               
   
               
   # /usr/lib/nvidia/sriov-manage -e domain:bus:slot.function
           

   domain

   bus

   slot

   function

   The domain, bus, slot, and function of the GPU, without the 0x prefix.

   Note:

   Only one mdev device file can be created on a virtual function.

   This example enables the virtual functions for the GPU with the domain 00, bus 41, slot 0000, and function 0.

   Copy

   Copied!

               
   
               
   # /usr/lib/nvidia/sriov-manage -e 00:41:0000.0
           

2. Obtain the domain, bus, slot, and function of the available virtual functions on the GPU.
   Copy

   Copied!

               
   
               
   # ls -l /sys/bus/pci/devices/domain\:bus\:slot.function/ | grep virtfn
           

   domain

   bus

   slot

   function

   The domain, bus, slot, and function of the GPU, without the 0x prefix.

   This example shows the output of this command for a physical GPU with slot 00, bus 41, domain 0000, and function 0.

   Copy

   Copied!

               
   
               
   # ls -l /sys/bus/pci/devices/0000:41:00.0/ | grep virtfn
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn0 -> ../0000:41:00.4
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn1 -> ../0000:41:00.5
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn10 -> ../0000:41:01.6
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn11 -> ../0000:41:01.7
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn12 -> ../0000:41:02.0
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn13 -> ../0000:41:02.1
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn14 -> ../0000:41:02.2
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn15 -> ../0000:41:02.3
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn16 -> ../0000:41:02.4
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn17 -> ../0000:41:02.5
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn18 -> ../0000:41:02.6
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn19 -> ../0000:41:02.7
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn2 -> ../0000:41:00.6
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn20 -> ../0000:41:03.0
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn21 -> ../0000:41:03.1
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn22 -> ../0000:41:03.2
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn23 -> ../0000:41:03.3
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn24 -> ../0000:41:03.4
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn25 -> ../0000:41:03.5
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn26 -> ../0000:41:03.6
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn27 -> ../0000:41:03.7
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn28 -> ../0000:41:04.0
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn29 -> ../0000:41:04.1
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn3 -> ../0000:41:00.7
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn30 -> ../0000:41:04.2
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn31 -> ../0000:41:04.3
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn4 -> ../0000:41:01.0
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn5 -> ../0000:41:01.1
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn6 -> ../0000:41:01.2
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn7 -> ../0000:41:01.3
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn8 -> ../0000:41:01.4
   lrwxrwxrwx. 1 root root           0 Jul 16 04:42 virtfn9 -> ../0000:41:01.5
           

3. Choose the available virtual function on which you want to create the vGPU and note its domain, bus, slot, and function.

2.10.3. Creating an NVIDIA vGPU on a Linux with KVM Hypervisor

For each vGPU that you want to create, perform this task in a Linux command shell on the a Linux with KVM hypervisor host.

Before you begin, ensure that you have the domain, bus, slot, and function of the GPU on which you are creating the vGPU. For instructions, see Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor.
How to create an NVIDIA vGPU on a Linux with KVM hypervisor depends on the following factors:

• Whether the NVIDIA vGPU supports single root I/O virtualization (SR-IOV)
• Whether the hypervisor uses a vendor-specific Virtual Function I/O (VFIO) framework for an NVIDIA vGPU that supports SR-IOV
  Note:

  A hypervisor that uses a vendor-specific VFIO framework for an NVIDIA vGPU that supports SR-IOV uses the standard VFIO framework for a legacy NVIDIA vGPU.

  A vendor-specific VFIO framework does not support the mediated VFIO mdev driver framework.

For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04.

To determine which instructions to follow for the NVIDIA vGPU that you are creating, refer to the following table.

2.10.3.1. Creating a Legacy NVIDIA vGPU on a Linux with KVM Hypervisor

A legacy NVIDIA vGPU does not support SR-IOV.

1. Change to the mdev_supported_types directory for the physical GPU.
   Copy

   Copied!

               
   
               
   # cd /sys/class/mdev_bus/domain\:bus\:slot.function/mdev_supported_types/
           

   domain

   bus

   slot

   function

   The domain, bus, slot, and function of the GPU, without the 0x prefix.

   This example changes to the mdev_supported_types directory for the GPU with the domain 0000 and PCI device BDF 06:00.0.

   Copy

   Copied!

               
   
               
   # cd /sys/bus/pci/devices/0000\:06\:00.0/mdev_supported_types/
           

2. Find out which subdirectory of mdev_supported_types contains registration information for the vGPU type that you want to create.
   Copy

   Copied!

               
   
               
   # grep -l "vgpu-type" nvidia-*/name
           

   vgpu-type

   The vGPU type, for example, M10-2Q.

   This example shows that the registration information for the M10-2Q vGPU type is contained in the nvidia-41 subdirectory of mdev_supported_types.

   Copy

   Copied!

               
   
               
   # grep -l "M10-2Q" nvidia-*/name
   nvidia-41/name
           

3. Confirm that you can create an instance of the vGPU type on the physical GPU.
   Copy

   Copied!

               
   
               
   # cat subdirectory/available_instances
           

   subdirectory

   The subdirectory that you found in the previous step, for example, nvidia-41.

   The number of available instances must be at least 1. If the number is 0, either an instance of another vGPU type already exists on the physical GPU, or the maximum number of allowed instances has already been created.

   This example shows that four more instances of the M10-2Q vGPU type can be created on the physical GPU.

   Copy

   Copied!

               
   
               
   # cat nvidia-41/available_instances
   4
           

4. Generate a correctly formatted universally unique identifier (UUID) for the vGPU.
   Copy

   Copied!

               
   
               
   # uuidgen
   aa618089-8b16-4d01-a136-25a0f3c73123
           

5. Write the UUID that you obtained in the previous step to the create file in the registration information directory for the vGPU type that you want to create.
   Copy

   Copied!

               
   
               
   # echo "uuid"> subdirectory/create
           

   uuid

   The UUID that you generated in the previous step, which will become the UUID of the vGPU that you want to create.

   subdirectory

   The registration information directory for the vGPU type that you want to create, for example, nvidia-41.

   This example creates an instance of the M10-2Q vGPU type with the UUID aa618089-8b16-4d01-a136-25a0f3c73123.

   Copy

   Copied!

               
   
               
   # echo "aa618089-8b16-4d01-a136-25a0f3c73123" > nvidia-41/create
           

   An mdev device file for the vGPU is added to the parent physical device directory of the vGPU. The vGPU is identified by its UUID.

   The /sys/bus/mdev/devices/ directory contains a symbolic link to the mdev device file.

6. Make the mdev device file that you created to represent the vGPU persistent.
   Copy

   Copied!

               
   
               
   # mdevctl define --auto --uuid uuid
           

   uuid

   The UUID that you specified in the previous step for the vGPU that you are creating.

   Note:

   Not all Linux with KVM hypervisor releases include the mdevctl command. If your release does not include the mdevctl command, you can use standard features of the operating system to automate the re-creation of this device file when the host is booted. For example, you can write a custom script that is executed when the host is rebooted.

7. Confirm that the vGPU was created.
   1. Confirm that the /sys/bus/mdev/devices/ directory contains the mdev device file for the vGPU.
      Copy

      Copied!

                  
      
                  
      # ls -l /sys/bus/mdev/devices/
      total 0
      lrwxrwxrwx. 1 root root 0 Nov 24 13:33 aa618089-8b16-4d01-a136-25a0f3c73123 -> ../../../devices/pci0000:00/0000:00:03.0/0000:03:00.0/0000:04:09.0/0000:06:00.0/aa618089-8b16-4d01-a136-25a0f3c73123
              

   2. If your release includes the mdevctl command, list the active mediated devices on the hypervisor host.
      Copy

      Copied!

                  
      
                  
      # mdevctl list
      aa618089-8b16-4d01-a136-25a0f3c73123 0000:06:00.0 nvidia-41
              

2.10.3.2. Creating an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor

An NVIDIA vGPU that supports SR-IOV resides on a physical GPU that supports SR-IOV, such as a GPU based on the NVIDIA Ampere architecture.

Before performing this task, ensure that the virtual function on which you want to create the vGPU has been prepared as explained in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

If you want to support vGPUs with different amounts of frame buffer, also ensure that the GPU has been put into mixed-size mode as explained in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

1. Change to the mdev_supported_types directory for the virtual function on which you want to create the vGPU.
   Copy

   Copied!

               
   
               
   # cd /sys/class/mdev_bus/domain\:bus\:vf-slot.v-function/mdev_supported_types/
           

   domain

   bus

   The domain and bus of the GPU, without the 0x prefix.

   vf-slot

   v-function

   The slot and function of the virtual function that you noted in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

   This example changes to the mdev_supported_types directory for the first virtual function (virtfn0) for the GPU with the domain 0000 and bus 41. The first virtual function (virtfn0) has slot 00 and function 4.

   Copy

   Copied!

               
   
               
   # cd /sys/class/mdev_bus/0000\:41\:00.4/mdev_supported_types
           

2. Find out which subdirectory of mdev_supported_types contains registration information for the vGPU type that you want to create.
   Copy

   Copied!

               
   
               
   # grep -l "vgpu-type" nvidia-*/name
           

   vgpu-type

   The vGPU type, for example, A40-2Q.

   This example shows that the registration information for the A40-2Q vGPU type is contained in the nvidia-558 subdirectory of mdev_supported_types.

   Copy

   Copied!

               
   
               
   # grep -l "A40-2Q" nvidia-*/name
   nvidia-558/name
           

3. Confirm that you can create an instance of the vGPU type on the virtual function.
   Copy

   Copied!

               
   
               
   # cat subdirectory/available_instances
           

   subdirectory

   The subdirectory that you found in the previous step, for example, nvidia-558.

   The number of available instances must be 1. If the number is 0, a vGPU has already been created on the virtual function. Only one instance of any vGPU type can be created on a virtual function.

   This example shows that an instance of the A40-2Q vGPU type can be created on the virtual function.

   Copy

   Copied!

               
   
               
   # cat nvidia-558/available_instances
   1
           

4. Generate a correctly formatted universally unique identifier (UUID) for the vGPU.
   Copy

   Copied!

               
   
               
   # uuidgen
   aa618089-8b16-4d01-a136-25a0f3c73123
           

5. Write the UUID that you obtained in the previous step to the create file in the registration information directory for the vGPU type that you want to create.
   Copy

   Copied!

               
   
               
   # echo "uuid"> subdirectory/create
           

   uuid

   The UUID that you generated in the previous step, which will become the UUID of the vGPU that you want to create.

   subdirectory

   The registration information directory for the vGPU type that you want to create, for example, nvidia-558.

   This example creates an instance of the A40-2Q vGPU type with the UUID aa618089-8b16-4d01-a136-25a0f3c73123.

   Copy

   Copied!

               
   
               
   # echo "aa618089-8b16-4d01-a136-25a0f3c73123" > nvidia-558/create
           

   An mdev device file for the vGPU is added to the parent virtual function directory of the vGPU. The vGPU is identified by its UUID.

6. Time-sliced vGPUs only: Make the mdev device file that you created to represent the vGPU persistent.
   Copy

   Copied!

               
   
               
   # mdevctl define --auto --uuid uuid
           

   uuid

   The UUID that you specified in the previous step for the vGPU that you are creating.

   Note:

   • If you are using a GPU that supports SR-IOV, the mdev device file persists after a host reboot only if you enable the virtual functions for the GPU as explained in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor before rebooting any VM that is configured with a vGPU on the GPU.
   • You cannot use the mdevctl command to make the mdev device file for a MIG-backed vGPU persistent. The mdev device file for a MIG-backed vGPU is not retained after the host is rebooted because MIG instances are no longer available.
   • Not all Linux with KVM hypervisor releases include the mdevctl command. If your release does not include the mdevctl command, you can use standard features of the operating system to automate the re-creation of this device file when the host is booted. For example, you can write a custom script that is executed when the host is rebooted.

7. Confirm that the vGPU was created.
   1. Confirm that the /sys/bus/mdev/devices/ directory contains a symbolic link to the mdev device file.
      Copy

      Copied!

                  
      
                  
      # ls -l /sys/bus/mdev/devices/
      total 0
      lrwxrwxrwx. 1 root root 0 Jul 16 05:57 aa618089-8b16-4d01-a136-25a0f3c73123 -> ../../../devices/pci0000:40/0000:40:01.1/0000:41:00.4/aa618089-8b16-4d01-a136-25a0f3c73123
              

   2. If your release includes the mdevctl command, list the active mediated devices on the hypervisor host.
      Copy

      Copied!

                  
      
                  
      # mdevctl list
      aa618089-8b16-4d01-a136-25a0f3c73123 0000:06:00.0 nvidia-558
              

2.10.3.3. Creating an NVIDIA vGPU on a Linux with KVM Hypervisor that Uses a Vendor-Specific VFIO Framework

A hypervisor uses a vendor-specific VFIO framework only for an NVIDIA vGPU that supports SR-IOV. For a legacy NVIDIA vGPU, the hypervisor uses the standard VFIO framework. A vendor-specific VFIO framework does not support the mediated VFIO mdev driver framework.

For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04.

Before performing this task, ensure that the virtual function on which you want to create the vGPU has been prepared as explained in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

If you want to support vGPUs with different amounts of frame buffer, also ensure that the GPU has been put into mixed-size mode as explained in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

1. Change to the directory in the sysfs file system that contains the files for vGPU management on the virtual function on which you want to create the vGPU.
   Copy

   Copied!

               
   
               
   # cd /sys/bus/pci/devices/domain\:bus\:vf-slot.v-function/nvidia
           

   domain

   bus

   The domain and bus of the GPU, without the 0x prefix.

   vf-slot

   v-function

   The slot and function of the virtual function that you noted in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

   This example changes to the nvidia directory for the first virtual function (virtfn0) for the GPU with the domain 0000 and bus 3d. The first virtual function (virtfn0) has slot 00 and function 4.

   Copy

   Copied!

               
   
               
   # cd /sys/bus/pci/devices/0000\:3d\:00.4/nvidia
           

2. Confirm that the directory contains the files for vGPU management on the virtual function, namely creatable_vgpu_types and current_vgpu_type.
   Copy

   Copied!

               
   
               
   # ll
   -r--r--r-- 1 root root       4096 Aug  3 00:39 creatable_vgpu_types
   -rw-r--r-- 1 root root       4096 Aug  3 00:39 current_vgpu_type
   ...
           

3. Confirm that a vGPU can be created on the virtual function.
   Copy

   Copied!

               
   
               
   # cat current_vgpu_type
   0
           

   If the current vGPU type is 0, a vGPU can be created on the virtual function.

   Note:

   If the current vGPU type is not zero, a vGPU cannot be created on the virtual function because a vGPU has already been created on it and only one vGPU can be created on a virtual function.

4. Determine the NVIDIA vGPU types that can be created on the virtual function and the integer ID that represents each vGPU type in the sysfs file system.
   Copy

   Copied!

               
   
               
   # cat creatable_vgpu_types
   NVIDIA A40-1Q           557
   NVIDIA A40-2Q           558
   NVIDIA A40-3Q           559
   NVIDIA A40-4Q           560
   NVIDIA A40-6Q           561
           

5. Write the ID that represents the type of the NVIDIA vGPU that you want to create to the current_vgpu_type file.
   Copy

   Copied!

               
   
               
   # echo vgpu-type-id > current_vgpu_type
           

   vgpu-type-id

   The ID that represents the type of the NVIDIA vGPU that you want to create in the sysfs file system.

   Note:

   You must specify an valid ID. If you specify an invalid ID, the write operation fails and current vGPU type is set to 0.

   This example creates an instance of the A40-4Q vGPU type.

   Copy

   Copied!

               
   
               
   # echo 560 > current_vgpu_type
           

6. Confirm that current vGPU type on the virtual function matches the type of the vGPU that you created in the previous step.
   Copy

   Copied!

               
   
               
   # cat current_vgpu_type
   560
           

7. Confirm that the creatable_vgpu_types file is empty, signifying that no vGPUs can be created on the virtual function.
   Copy

   Copied!

               
   
               
   # cat creatable_vgpu_types
           

2.10.4. Adding One or More vGPUs to a Linux with KVM Hypervisor VM

To support applications and workloads that are compute or graphics intensive, you can add multiple vGPUs to a single VM.

For details about which hypervisor versions and NVIDIA vGPUs support the assignment of multiple vGPUs to a VM, see Virtual GPU Software for Red Hat Enterprise Linux with KVM Release Notes and Virtual GPU Software for Ubuntu Release Notes.
Ensure that the following prerequisites are met:

• The VM to which you want to add the vGPUs is shut down.
• The vGPUs that you want to add have been created as explained in Creating an NVIDIA vGPU on a Linux with KVM Hypervisor.

You can add vGPUs to a Linux with KVM hypervisor VM by using any of the following tools:

• The virsh command
• The QEMU command line

After adding vGPUs to a Linux with KVM hypervisor VM, start the VM.

            

            
# virsh start vm-name
        

vm-name

The name of the VM that you added the vGPUs to.

After the VM has booted, install the NVIDIA vGPU software graphics driver as explained in Installing the NVIDIA vGPU Software Graphics Driver.

2.10.4.1. Adding One or More vGPUs to a Linux with KVM Hypervisor VM by Using virsh

1. In virsh, open for editing the XML file of the VM that you want to add the vGPU to.
   Copy

   Copied!

               
   
               
   # virsh edit vm-name
           

   vm-name

   The name of the VM to that you want to add the vGPUs to.

2. For each vGPU that you want to add to the VM, add a device entry in the form of an address element inside the source element to add the vGPU to the guest VM.

   The content of the device entry depends on whether the hypervisor uses a vendor-specific VFIO framework for an NVIDIA vGPU that supports SR-IOV.

   For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04.

   • For a hypervisor that uses the standard VFIO framework, add a device entry that identifies the vGPU through its UUID as follows:

     Copy

     Copied!

                 
     
                 
     <device>
     ...
       <hostdev mode='subsystem' type='mdev' model='vfio-pci'>
         <source>
           <address uuid='uuid'/>
         </source>
       </hostdev>
     </device>
             

     uuid

     The UUID that was assigned to the vGPU when the vGPU was created.

     This example adds a device entry for the vGPU with the UUID a618089-8b16-4d01-a136-25a0f3c73123.

     Copy

     Copied!

                 
     
                 
     <device>
     ...
       <hostdev mode='subsystem' type='mdev' model='vfio-pci'>
         <source>
           <address uuid='a618089-8b16-4d01-a136-25a0f3c73123'/>
         </source>
       </hostdev>
     </device>
             

     This example adds device entries for two vGPUs with the following UUIDs:

     • c73f1fa6-489e-4834-9476-d70dabd98c40
     • 3b356d38-854e-48be-b376-00c72c7d119c
     Copy

     Copied!

                 
     
                 
     <device>
     ...
       <hostdev mode='subsystem' type='mdev' model='vfio-pci'>
         <source>
           <address uuid='c73f1fa6-489e-4834-9476-d70dabd98c40'/>
         </source>
       </hostdev>
       <hostdev mode='subsystem' type='mdev' model='vfio-pci'>
         <source>
           <address uuid='3b356d38-854e-48be-b376-00c72c7d119c'/>
         </source>
       </hostdev>
     </device>
             

   • For a hypervisor that uses a vendor-specific VFIO framework, add a device entry that identifies the vGPU through the virtual function on which the vGPU is created as follows:

     Copy

     Copied!

                 
     
                 
     <hostdev mode='subsystem' type='pci' managed='no'>
       <source>
         <address domain='domain' bus='bus' slot='vf-slot' function='v-function'/>
       </source>
     </hostdev>
             

     domain

     bus

     The domain and bus of the GPU, including the 0x prefix.

     vf-slot

     v-function

     The slot and function of the virtual function that you noted in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

     Note:

     A vGPU is supported only in unmanaged libvirt mode. Therefore, ensure that in the hostdev element, the managed attribute is set to no.

     This example adds a device entry for the vGPU that is created on the virtual function 0000:3d:00.4.

     Copy

     Copied!

                 
     
                 
     <device>
     ...
       <hostdev mode='subsystem' type='pci' managed='no'>
         <source>
           <address domain='0x0000' bus='0x3d' slot='0x00' function='0x4'/>
         </source>
       </hostdev>
     </device>
             

     This example adds device entries for two vGPUs that are created on the following virtual functions:

     • 0000:3d:00.4
     • 0000:3d:00.5
     Copy

     Copied!

                 
     
                 
     <device>
     ...
       <hostdev mode='subsystem' type='pci' managed='no'>
         <source>
           <address domain='0x0000' bus='0x3d' slot='0x00' function='0x4'/>
         </source>
       </hostdev>
       <hostdev mode='subsystem' type='pci' managed='no'>
         <source>
           <address domain='0x0000' bus='0x3d' slot='0x00' function='0x5'/>
         </source>
       </hostdev>
     </device>
             

3. Optional: Add a video element that contains a model element in which the type attribute is set to none.
   Copy

   Copied!

               
   
               
   <video>
   <model type='none'/>
   </video>
           

   Adding this video element prevents the default video device that libvirt adds from being loaded into the VM. If you don’t add this video element, you must configure the Xorg server or your remoting solution to load only the vGPU devices you added and not the default video device.

2.10.4.2. Adding One or More vGPUs to a Linux with KVM Hypervisor VM by Using the QEMU Command Line

This task involves adding options to the QEMU command line that identify the vGPUs that you want to add and the VM to which you want to add them.

1. For each vGPU that you want to add to the VM, add one -device option that identifies the vGPU.

   The format of each -device option depends on whether the hypervisor uses a vendor-specific VFIO framework for an NVIDIA vGPU that supports SR-IOV.

   For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04.

   • For each vGPU on a hypervisor that uses the standard VFIO framework, add a -device option that identifies the vGPU through its UUID.

     Copy

     Copied!

                 
     
                 
     -device vfio-pci,sysfsdev=/sys/bus/mdev/devices/vgpu-uuid
             

     vgpu-uuid

     The UUID that was assigned to the vGPU when the vGPU was created.

   • For each vGPU on a hypervisor that uses a vendor-specific VFIO framework, add a -device option that identifies the vGPU through the virtual function on which the vGPU is created.

     Copy

     Copied!

                 
     
                 
     -device vfio-pci,sysfsdev=/sys/bus/pci/devices/domain\:bus\:vf-slot.v-function/
             

     domain

     bus

     The domain and bus of the GPU, without the 0x prefix.

     vf-slot

     v-function

     The slot and function of the virtual function that you noted in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

2. Add a -uuid option to specify the VM to which you want to add the vGPUs.
   Copy

   Copied!

               
   
               
   -uuid vm-uuid
           

   vm-uuid

   The UUID that was assigned to the VM when the VM was created.

Adding One vGPU to a VM on a Hypervisor that Uses the Standard VFIO Framework

This example adds the vGPU with the UUID aa618089-8b16-4d01-a136-25a0f3c73123 to the VM with the UUID ebb10a6e-7ac9-49aa-af92-f56bb8c65893.

            

            
-device vfio-pci,sysfsdev=/sys/bus/mdev/devices/aa618089-8b16-4d01-a136-25a0f3c73123 \
-uuid ebb10a6e-7ac9-49aa-af92-f56bb8c65893
        

Adding Two vGPUs to a VM on a Hypervisor that Uses the Standard VFIO Framework

This example adds device entries for two vGPUs with the following UUIDs:

• 676428a0-2445-499f-9bfd-65cd4a9bd18f
• 6c5954b8-5bc1-4769-b820-8099fe50aaba

The entries are added to the VM with the UUID ec5e8ee0-657c-4db6-8775-da70e332c67e.

            

            
-device vfio-pci,sysfsdev=/sys/bus/mdev/devices/676428a0-2445-499f-9bfd-65cd4a9bd18f \
-device vfio-pci,sysfsdev=/sys/bus/mdev/devices/6c5954b8-5bc1-4769-b820-8099fe50aaba \
-uuid ec5e8ee0-657c-4db6-8775-da70e332c67e
        

Adding One vGPU to a VM on a Hypervisor that Uses a Vendor-Specific VFIO Framework

This example adds the vGPU that is created on the virtual function 0000:3d:00.4 to the VM with the UUID ebb10a6e-7ac9-49aa-af92-f56bb8c65893.

            

            
-device vfio-pci,sysfsdev=/sys/bus/pci/devices/0000\:3d\:00.4 \
-uuid ebb10a6e-7ac9-49aa-af92-f56bb8c65893
        

Adding Two vGPUs to a VM on a Hypervisor that Uses a Vendor-Specific VFIO Framework

This example adds device entries for two vGPUs that are created on the following virtual functions:

• 0000:3d:00.4
• 0000:3d:00.5

The entries are added to the VM with the UUID ec5e8ee0-657c-4db6-8775-da70e332c67e.

            

            
-device vfio-pci,sysfsdev=/sys/bus/pci/devices/0000\:3d\:00.4 \
-device vfio-pci,sysfsdev=/sys/bus/pci/devices/0000\:3d\:00.5 \
-uuid ec5e8ee0-657c-4db6-8775-da70e332c67e
        

2.10.5. Setting vGPU Plugin Parameters on a Linux with KVM Hypervisor

Plugin parameters for a vGPU control the behavior of the vGPU, such as the frame rate limiter (FRL) configuration in frames per second or whether console virtual network computing (VNC) for the vGPU is enabled. The VM to which the vGPU is assigned is started with these parameters. If parameters are set for multiple vGPUs assigned to the same VM, the VM is started with the parameters assigned to each vGPU.

For each vGPU for which you want to set plugin parameters, perform this task in a Linux command shell on the Linux with KVM hypervisor host.

1. Change to the directory in the sysfs file system that contains the vgpu_params file for the vGPU for which you want to set vGPU plugin parameters.

   The directory depends on whether the hypervisor uses a vendor-specific VFIO framework for an NVIDIA vGPU that supports SR-IOV.

   For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04.

   • For a hypervisor that uses the standard VFIO framework, change to the nvidia subdirectory of the mdev device directory that represents the vGPU.

     Copy

     Copied!

                 
     
                 
     # cd /sys/bus/mdev/devices/uuid/nvidia
             

     uuid

     The UUID of the vGPU, for example, aa618089-8b16-4d01-a136-25a0f3c73123.

   • For a hypervisor that uses a vendor-specific VFIO framework, change to the directory in the sysfs file system that contains the files for vGPU management on the virtual function on which the vGPU was created.

     Copy

     Copied!

                 
     
                 
     # cd /sys/bus/pci/devices/domain\:bus\:vf-slot.v-function/nvidia
             

     domain

     bus

     The domain and bus of the GPU, without the 0x prefix.

     vf-slot

     v-function

     The slot and function of the virtual function that you noted in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

     This example changes to the nvidia directory for the first virtual function (virtfn0) for the GPU with the domain 0000 and bus 3d. The first virtual function (virtfn0) has slot 00 and function 4.

     Copy

     Copied!

                 
     
                 
     # cd /sys/bus/pci/devices/0000\:3d\:00.4/nvidia
             

2. Write the plugin parameters that you want to set to the vgpu_params file in the directory that you changed to in the previous step.
   Copy

   Copied!

               
   
               
   # echo "plugin-config-params" > vgpu_params
           

   plugin-config-params

   A comma-separated list of parameter-value pairs, where each pair is of the form parameter-name=value.

   This example disables frame rate limiting and console VNC for a vGPU.

   Copy

   Copied!

               
   
               
   # echo "frame_rate_limiter=0, disable_vnc=1" > vgpu_params
           

   This example enables unified memory for a vGPU.

   Copy

   Copied!

               
   
               
   # echo "enable_uvm=1"  > vgpu_params
           

   This example enables NVIDIA CUDA Toolkit debuggers for a vGPU.

   Copy

   Copied!

               
   
               
   # echo "enable_debugging=1"  > vgpu_params
           

   This example enables NVIDIA CUDA Toolkit profilers for a vGPU.

   Copy

   Copied!

               
   
               
   # echo "enable_profiling=1"  > vgpu_params
           

To clear any vGPU plugin parameters that were set previously, write a space to the vgpu_params file for the vGPU.

            

            
# echo " " > vgpu_params
        

2.10.6. Deleting a vGPU on a Linux with KVM Hypervisor

How to delete a vGPU on a Linux with KVM hypervisor depends on whether the hypervisor uses a vendor-specific VFIO framework for an NVIDIA vGPU that supports SR-IOV.

For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04.

To determine which instructions to follow for the NVIDIA vGPU that you are deleting, refer to the following table.

2.10.6.1. Deleting a vGPU on a Linux with KVM Hypervisor that Uses the Standard VFIO Framework

For each vGPU that you want to delete, perform this task in a Linux command shell on the Linux with KVM hypervisor host.
Before you begin, ensure that the following prerequisites are met:

• You have the domain, bus, slot, and function of the GPU where the vGPU that you want to delete resides. For instructions, see Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor.
• The VM to which the vGPU is assigned is shut down.

1. Change to the mdev_supported_types directory for the physical GPU.
   Copy

   Copied!

               
   
               
   # cd /sys/class/mdev_bus/domain\:bus\:slot.function/mdev_supported_types/
           

   domain

   bus

   slot

   function

   The domain, bus, slot, and function of the GPU, without the 0x prefix.

   This example changes to the mdev_supported_types directory for the GPU with the PCI device BDF 06:00.0.

   Copy

   Copied!

               
   
               
   # cd /sys/bus/pci/devices/0000\:06\:00.0/mdev_supported_types/
           

2. Change to the subdirectory of mdev_supported_types that contains registration information for the vGPU.
   Copy

   Copied!

               
   
               
   # cd `find . -type d -name uuid`
           

   uuid

   The UUID of the vGPU, for example, aa618089-8b16-4d01-a136-25a0f3c73123.

3. Write the value 1 to the remove file in the registration information directory for the vGPU that you want to delete.
   Copy

   Copied!

               
   
               
   # echo "1" > remove
           

2.10.6.2. Deleting a vGPU on a Linux with KVM Hypervisor that Uses a Vendor-Specific VFIO Framework

A hypervisor uses a vendor-specific VFIO framework only for an NVIDIA vGPU that supports SR-IOV. For a legacy NVIDIA vGPU, the hypervisor uses the standard VFIO framework. A vendor-specific VFIO framework does not support the mediated VFIO mdev driver framework.

For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04.
Before you begin, ensure that the following prerequisites are met:

• You have the following information:
  • The domain and bus of the GPU where the vGPU that you want to delete resides. For instructions, see Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor.
  • The slot and function of the virtual function on which the vGPU that you want to delete was created.
• The VM to which the vGPU is assigned is shut down.

1. Change to the directory in the sysfs file system that contains the files for vGPU management on the virtual function on which the vGPU was created.
   Copy

   Copied!

               
   
               
   # cd /sys/bus/pci/devices/domain\:bus\:vf-slot.v-function/nvidia
           

   domain

   bus

   The domain and bus of the GPU, without the 0x prefix.

   vf-slot

   v-function

   The slot and function of the virtual function that you noted in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

   This example changes to the nvidia directory for the first virtual function (virtfn0) for the GPU with the domain 0000 and bus 3d. The first virtual function (virtfn0) has slot 00 and function 4.

   Copy

   Copied!

               
   
               
   # cd /sys/bus/pci/devices/0000\:3d\:00.4/nvidia
           

2. Confirm that the directory contains the files for vGPU management on the virtual function, namely creatable_vgpu_types and current_vgpu_type.
   Copy

   Copied!

               
   
               
   # ll
   -r--r--r-- 1 root root       4096 Aug  3 00:39 creatable_vgpu_types
   -rw-r--r-- 1 root root       4096 Aug  3 00:39 current_vgpu_type
   ...
           

3. Confirm that the current vGPU type on the virtual function is the ID that represents the type of the vGPU that you want to delete.
   Copy

   Copied!

               
   
               
   # cat current_vgpu_type
   560
           

4. Write 0 to the current_vgpu_type file.
   Copy

   Copied!

               
   
               
   # echo 0 > current_vgpu_type
           

5. Confirm that current vGPU type on the virtual function is 0, signifying that the vGPU has been deleted.
   Copy

   Copied!

               
   
               
   # cat current_vgpu_type
   0
           

6. Confirm that the creatable_vgpu_types file is no longer empty, signifying that the vGPU has been deleted and that a vGPU can again be created on the virtual function.
   Copy

   Copied!

               
   
               
   # cat creatable_vgpu_types
   NVIDIA A40-1Q           557
   NVIDIA A40-2Q           558
   NVIDIA A40-3Q           559
   NVIDIA A40-4Q           560
   NVIDIA A40-6Q           561
           

2.10.7. Preparing a GPU Configured for Pass-Through for Use with vGPU

The mode in which a physical GPU is being used determines the Linux kernel module to which the GPU is bound. If you want to switch the mode in which a GPU is being used, you must unbind the GPU from its current kernel module and bind it to the kernel module for the new mode. After binding the GPU to the correct kernel module, you can then configure it for vGPU.

A physical GPU that is passed through to a VM is bound to the vfio-pci kernel module. A physical GPU that is bound to the vfio-pci kernel module can be used only for pass-through. To enable the GPU to be used for vGPU, the GPU must be unbound from vfio-pci kernel module and bound to the nvidia kernel module.
Before you begin, ensure that you have the domain, bus, slot, and function of the GPU that you are preparing for use with vGPU. For instructions, see Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor.

1. Determine the kernel module to which the GPU is bound by running the lspci command with the -k option on the NVIDIA GPUs on your host.
   Copy

   Copied!

               
   
               
   # lspci -d 10de: -k
           

   The Kernel driver in use: field indicates the kernel module to which the GPU is bound.

   The following example shows that the NVIDIA Tesla M60 GPU with BDF06:00.0 is bound to the vfio-pci kernel module and is being used for GPU pass through.

   Copy

   Copied!

               
   
               
   06:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
            Subsystem: NVIDIA Corporation Device 115e
            Kernel driver in use: vfio-pci
           

2. Unbind the GPU from vfio-pci kernel module.
   1. Change to the sysfs directory that represents the vfio-pci kernel module.
      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/drivers/vfio-pci
              

   2. Write the domain, bus, slot, and function of the GPU to the unbind file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo domain:bus:slot.function > unbind
              

      domain

      bus

      slot

      function

      The domain, bus, slot, and function of the GPU, without a 0x prefix.

      This example writes the domain, bus, slot, and function of the GPU with the domain 0000 and PCI device BDF 06:00.0.

      Copy

      Copied!

                  
      
                  
      # echo 0000:06:00.0 > unbind
              

3. Bind the GPU to the nvidia kernel module.
   1. Change to the sysfs directory that contains the PCI device information for the physical GPU.
      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/devices/domain\:bus\:slot.function
              

      domain

      bus

      slot

      function

      The domain, bus, slot, and function of the GPU, without a 0x prefix.

      This example changes to the sysfs directory that contains the PCI device information for the GPU with the domain 0000 and PCI device BDF 06:00.0.

      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/devices/0000\:06\:00.0
              

   2. Write the kernel module name nvidia to the driver_override file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo nvidia > driver_override
              

   3. Change to the sysfs directory that represents the nvidia kernel module.
      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/drivers/nvidia
              

   4. Write the domain, bus, slot, and function of the GPU to the bind file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo domain:bus:slot.function > bind
              

      domain

      bus

      slot

      function

      The domain, bus, slot, and function of the GPU, without a 0x prefix.

      This example writes the domain, bus, slot, and function of the GPU with the domain 0000 and PCI device BDF 06:00.0.

      Copy

      Copied!

                  
      
                  
      # echo 0000:06:00.0 > bind
              

You can now configure the GPU with vGPU as explained in Installing and Configuring the NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM.

2.10.8. NVIDIA vGPU Information in the sysfs File System

Information about the NVIDIA vGPU types supported by each physical GPU in a Linux with KVM hypervisor host is stored in the sysfs file system.

How NVIDIA vGPU information is stored in the sysfs file system depends on whether the hypervisor uses a vendor-specific VFIO framework for an NVIDIA vGPU that supports SR-IOV.

For GPUs that support SR-IOV, use of a vendor-specific VFIO framework is introduced in Ubuntu release 24.04. For more detailed information about how NVIDIA vGPU information is stored in the sysfs file system, refer to the following topics:

• NVIDIA vGPU Information in the sysfs File System for Hypervisors that Use the Standard VFIO Framework
• NVIDIA vGPU Information in the sysfs File System for Hypervisors that Use a Vendor-Specific VFIO Framework

2.10.8.1. NVIDIA vGPU Information in the sysfs File System for Hypervisors that Use the Standard VFIO Framework

All physical GPUs on the host are registered with the mdev kernel module. Information about the physical GPUs and the vGPU types that can be created on each physical GPU is stored in directories and files under the /sys/class/mdev_bus/ directory.

The sysfs directory for each physical GPU is at the following locations:

• /sys/bus/pci/devices/
• /sys/class/mdev_bus/

Both directories are a symbolic link to the real directory for PCI devices in the sysfs file system.

The organization of the sysfs directory for each physical GPU is as follows:

            

            
/sys/class/mdev_bus/
           |-parent-physical-device
             |-mdev_supported_types
               |-nvidia-vgputype-id
                 |-available_instances
                 |-create
                 |-description
                 |-device_api
                 |-devices
                 |-name
        

parent-physical-device

Each physical GPU on the host is represented by a subdirectory of the /sys/class/mdev_bus/ directory.

The name of each subdirectory is as follows:

domain\:bus\:slot.function

domain, bus, slot, function are the domain, bus, slot, and function of the GPU, for example, 0000\:06\:00.0.

Each directory is a symbolic link to the real directory for PCI devices in the sysfs file system. For example:

Copy

Copied!

            

            
# ll /sys/class/mdev_bus/
total 0
lrwxrwxrwx. 1 root root 0 Dec 12 03:20 0000:05:00.0 -> ../../devices/pci0000:00/0000:00:03.0/0000:03:00.0/0000:04:08.0/0000:05:00.0
lrwxrwxrwx. 1 root root 0 Dec 12 03:20 0000:06:00.0 -> ../../devices/pci0000:00/0000:00:03.0/0000:03:00.0/0000:04:09.0/0000:06:00.0
lrwxrwxrwx. 1 root root 0 Dec 12 03:20 0000:07:00.0 -> ../../devices/pci0000:00/0000:00:03.0/0000:03:00.0/0000:04:10.0/0000:07:00.0
lrwxrwxrwx. 1 root root 0 Dec 12 03:20 0000:08:00.0 -> ../../devices/pci0000:00/0000:00:03.0/0000:03:00.0/0000:04:11.0/0000:08:00.0
        

mdev_supported_types

A directory named mdev_supported_types is required under the sysfs directory for each physical GPU that will be configured with NVIDIA vGPU. How this directory is created for a GPU depends on whether the GPU supports SR-IOV.

• For a GPU that does not support SR-IOV, this directory is created automatically after the Virtual GPU Manager is installed on the host and the host has been rebooted.
• For a GPU that supports SR-IOV, such as a GPU based on the NVIDIA Ampere architecture, you must create this directory by enabling the virtual function for the GPU as explained in Creating an NVIDIA vGPU on a Linux with KVM Hypervisor. The mdev_supported_types directory itself is never visible on the physical function.

The mdev_supported_types directory contains a subdirectory for each vGPU type that the physical GPU supports. The name of each subdirectory is nvidia-vgputype-id, where vgputype-id is an unsigned integer serial number. For example:

Copy

Copied!

            

            
# ll mdev_supported_types/
total 0
drwxr-xr-x 3 root root 0 Dec  6 01:37 nvidia-35
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-36
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-37
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-38
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-39
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-40
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-41
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-42
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-43
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-44
drwxr-xr-x 3 root root 0 Dec  5 10:43 nvidia-45
        

nvidia-vgputype-id

Each directory represents an individual vGPU type and contains the following files and directories:

available_instances

This file contains the number of instances of this vGPU type that can still be created. This file is updated any time a vGPU of this type is created on or removed from the physical GPU.

Note:

When a time-sliced vGPU is created, the content of the available_instances for all other time-sliced vGPU types on the physical GPU is set to 0. This behavior enforces the requirement that all time-sliced vGPUs on a physical GPU must be of the same type. However, this requirement does not apply to MIG-backed vGPUs. Therefore, when a MIG-backed vGPU is created, available_instances for all other MIG-backed vGPU types on the physical GPU is not set to 0

create

This file is used for creating a vGPU instance. A vGPU instance is created by writing the UUID of the vGPU to this file. The file is write only.

description

This file contains the following details of the vGPU type:

• The maximum number of virtual display heads that the vGPU type supports
• The frame rate limiter (FRL) configuration in frames per second
• The frame buffer size in Mbytes
• The maximum resolution per display head
• The maximum number of vGPU instances per physical GPU

For example:

Copy

Copied!

            

            
# cat description
num_heads=4, frl_config=60, framebuffer=2048M, max_resolution=4096x2160, max_instance=4
        

device_api

This file contains the string vfio_pci to indicate that a vGPU is a PCI device.

devices

This directory contains all the mdev devices that are created for the vGPU type. For example:

Copy

Copied!

            

            
# ll devices
total 0
lrwxrwxrwx 1 root root 0 Dec  6 01:52 aa618089-8b16-4d01-a136-25a0f3c73123 -> ../../../aa618089-8b16-4d01-a136-25a0f3c73123
        

name

This file contains the name of the vGPU type. For example:

Copy

Copied!

            

            
# cat name
GRID M10-2Q
        

2.10.8.2. NVIDIA vGPU Information in the sysfs File System for Hypervisors that Use a Vendor-Specific VFIO Framework

A vendor-specific VFIO framework does not support the mediated VFIO mdev driver framework. Information about the physical GPUs and the vGPU types that can be created on each physical GPU is stored in directories and files under the /sys/bus/pci/devices/ directory.

The organization of the sysfs directory for each virtual function on a physical GPU is as follows:

            

            
/sys/bus/pci/devices/
           |-virtual-function
             |-nvidia
               |-creatable_vgpu_types
               |-current_vgpu_type
               |-vgpu_params
        

virtual-function

Each virtual function on each physical GPU on the host is represented by a subdirectory of the /sys/bus/pci/devices/ directory.

The name of each subdirectory is as follows:

domain\:bus\:vf-slot.v-function

domain and bus are the domain and bus of the GPU. vf-slot and v-function are the slot and function of the virtual function. For example: 0000\:3d\:00.4.

You must create this directory by enabling the virtual function for the GPU as explained in Creating an NVIDIA vGPU on a Linux with KVM Hypervisor. This directory is not created automatically.

nvidia

The nvidia directory contains the files for vGPU management on the virtual function. These files are as follows:

creatable_vgpu_types

This file contains the NVIDIA vGPU types that can be created on the virtual function and the integer ID that represents each vGPU type in the sysfs file system. For example:

Copy

Copied!

            

            
# cat creatable_vgpu_types
NVIDIA A40-1Q           557
NVIDIA A40-2Q           558
NVIDIA A40-3Q           559
NVIDIA A40-4Q           560
NVIDIA A40-6Q           561
        

This file is not a static list of all the NVIDIA vGPU types that the GPU supports. It is updated dynamically in response to changes to the current_vgpu_type file for this virtual function and for other virtual functions on the same GPU.

• If a vGPU has been created on this virtual function, this file is empty.
• If a vGPU has been created on another virtual function on the same GPU, this file contains only the vGPU types that can reside on the same GPU as the existing vGPU.
• If the maximum number of vGPUs that the GPU supports has been created on other virtual functions for the GPU, this file is empty.

Note:

When a time-sliced vGPU is created on a GPU in equal-size mode, the content of the creatable_vgpu_types for all virtual functions on the physical GPU is set to only the vGPU types with the same amount of frame buffer as the vGPU that was created. This behavior enforces the requirement that all time-sliced vGPUs on the physical GPU must have the same amount of frame buffer. However, this requirement does not apply to time-sliced vGPUs created on a GPU in mixed-size mode or to MIG-backed vGPUs.

current_vgpu_type

This file contains the integer ID that represents the vGPU type in the sysfs file system of the vGPU that is created on this virtual function. For example, if an NVIDIA A40-4Q vGPU has been created on this virtual function, this file contains the integer 560:

Copy

Copied!

            

            
# cat current_vgpu_type
560
        

If no vGPU is created on the virtual function, this file contains the integer 0. When this file is created, its contents are set to the default value of 0.

This file is used for creating and deleting a vGPU on the virtual function.

• A vGPU is created by writing the integer ID that represents the vGPU type in the sysfs file system to this file.
• A vGPU is deleted by writing 0 to this file.

vgpu_params

This file is used for setting plugin parameters for the vGPU on the virtual function to control its behavior. Plugin parameters are set by writing a list of parameter-value pairs to this file. For more information, refer to Setting vGPU Plugin Parameters on a Linux with KVM Hypervisor.

2.11. Putting a GPU Into Mixed-Size Mode

By default, a GPU supports only vGPUs with the same amount of frame buffer and, therefore, is in equal-size mode. To support vGPUs with different amounts of frame buffer, the GPU must be put into mixed-size mode. When a GPU is in mixed-size mode, the maximum number of some types of vGPU allowed on a GPU is less than when the GPU is in equal-size mode.

Before performing this task, ensure that no vGPUs are running on the GPU and that the GPU is not being used by any other processes, such as CUDA applications, monitoring applications, or the nvidia-smi command.

If you are using a GPU that supports SR-IOV on a Linux with KVM hypervisor, also ensure that the virtual functions for the physical GPU in the sysfs file system are enabled as explained in Preparing the Virtual Function for an NVIDIA vGPU that Supports SR-IOV on a Linux with KVM Hypervisor.

1. Use nvidia-smi to list the status of all physical GPUs, and check that heterogeneous time-sliced vGPU sizes are noted as supported.
   Copy

   Copied!

               
   
               
   # nvidia-smi -q
   ...
   Attached GPUs                       : 1
   GPU 00000000:41:00.0
   ...
           Heterogeneous Time-Slice Sizes : Supported
   ...
           

2. Put each GPU that you want to support vGPUs with different amounts of frame buffer into mixed-size mode.
   Copy

   Copied!

               
   
               
   # nvidia-smi vgpu -i id -shm 1
           

   id

   The index of the GPU as reported by nvidia-smi.

   This example puts the GPU with index 00000000:41:00.0 into mixed-size mode.

   Copy

   Copied!

               
   
               
   # nvidia-smi vgpu -i 0 -shm 1
   Enabled vGPU heterogeneous mode for GPU 00000000:41:00.0
           

3. Confirm that the GPU is now in mixed-size mode by using nvidia-smi to check that vGPU heterogeneous mode is enabled.
   Copy

   Copied!

               
   
               
   # nvidia-smi -q
           ...
           vGPU Heterogeneous Mode           : Enabled
           ...
           

2.12. Placing a vGPU on a Physical GPU in Mixed-Size Mode

By default, the Virtual GPU Manager determines where a vGPU is placed on a GPU. To fit as many vGPUs as possible on the GPU, you can control the placement of vGPUs on a GPU in mixed-size mode. By controlling the placement of vGPUs on the GPU, you can ensure that no gaps that cannot be occupied by a vGPU are left in the placement region on the GPU.

The vGPU placements that a GPU in mixed-size mode supports depend on the total amount of frame buffer that the GPU has. For details, refer to vGPU Placements for GPUs in Mixed-Size Mode.

Before performing this task, ensure that following prerequisites are met:

• The GPU has been put into mixed-size mode as explained in Putting a GPU Into Mixed-Size Mode.
• The vGPU that you want to place on the physical GPU has been created as explained in Creating an NVIDIA vGPU on a Linux with KVM Hypervisor.

Perform this task in a command shell on the hypervisor host.

1. Use nvidia-smi to list the placement size and available placement IDs for the type of the vGPU.
   Copy

   Copied!

               
   
               
   # nvidia-smi vgpu -c -v
   ...
       vGPU Type ID                          : 0x392
           Name                              : NVIDIA L4-6Q
   ...
           Placement Size                    : 6
           Creatable Placement IDs           : 6 18
   ...
           

   Note:

   Some supported placement IDs for the vGPU type might be unavailable because they are already in use by another vGPU. To list the placement size and all supported placement IDs for the type of the vGPU, run the following command:

   Copy

   Copied!

               
   
               
   # nvidia-smi vgpu -s -v
   ...
       vGPU Type ID                          : 0x392
           Name                              : NVIDIA L4-6Q
   ...
           Placement Size                    : 6
           Supported Placement IDs           : 0 6 12 18
   ...
           

   The number of supported placement IDs is the maximum number of vGPUs of the type that are allowed on the GPU in mixed-size mode.

2. Set the vgpu-placement-id vGPU plugin parameter for the vGPU to the placement ID that you want.

   For a Linux with KVM hypervisor, write the parameter to the vgpu_params file in the nvidia subdirectory of the mdev device directory that represents the vGPU.

   Copy

   Copied!

               
   
               
   # echo "vgpu-placement-id=placement-id" > /sys/bus/mdev/devices/uuid/nvidia/vgpu_params
           

   placement-id

   The placement ID that you want to set for the vGPU.

   uuid

   The UUID of the vGPU, for example, aa618089-8b16-4d01-a136-25a0f3c73123.

   This example sets the placement ID for the vGPU that has the UUID aa618089-8b16-4d01-a136-25a0f3c73123 to 6.

   Copy

   Copied!

               
   
               
   # echo "vgpu-placement-id=6" > \
   /sys/bus/mdev/devices/aa618089-8b16-4d01-a136-25a0f3c73123/nvidia/vgpu_params
           

When the VM to which the vGPU is assigned is rebooted, the Virtual GPU Manager validates the placement ID that you assigned to the vGPU. If the placement ID is invalid or unavailable, the VM fails to boot.

After the VM to which the vGPU is assigned has been rebooted, you can confirm that the vGPU has been assigned the correct placement ID.

            

            
# nvidia-smi vgpu -q
GPU 00000000:41:00.0
    Active vGPUs                          : 1
    vGPU ID                               : 3251719533
        VM ID                             : 2150987
        ...
        Placement ID                      : 6
        ...
        

2.13. Disabling and Enabling ECC Memory

Some GPUs that support NVIDIA vGPU software support error correcting code (ECC) memory with NVIDIA vGPU. ECC memory improves data integrity by detecting and handling double-bit errors. However, not all GPUs, vGPU types, and hypervisor software versions support ECC memory with NVIDIA vGPU.

On GPUs that support ECC memory with NVIDIA vGPU, ECC memory is supported with C-series and Q-series vGPUs, but not with A-series and B-series vGPUs. Although A-series and B-series vGPUs start on physical GPUs on which ECC memory is enabled, enabling ECC with vGPUs that do not support it might incur some costs.

On physical GPUs that do not have HBM2 memory, the amount of frame buffer that is usable by vGPUs is reduced. All types of vGPU are affected, not just vGPUs that support ECC memory.

The effects of enabling ECC memory on a physical GPU are as follows:

• ECC memory is exposed as a feature on all supported vGPUs on the physical GPU.
• In VMs that support ECC memory, ECC memory is enabled, with the option to disable ECC in the VM.
• ECC memory can be enabled or disabled for individual VMs. Enabling or disabling ECC memory in a VM does not affect the amount of frame buffer that is usable by vGPUs.

GPUs based on the Pascal GPU architecture and later GPU architectures support ECC memory with NVIDIA vGPU. To determine whether ECC memory is enabled for a GPU, run nvidia-smi -q for the GPU.

Tesla M60 and M6 GPUs support ECC memory when used without GPU virtualization, but NVIDIA vGPU does not support ECC memory with these GPUs. In graphics mode, these GPUs are supplied with ECC memory disabled by default.

Some hypervisor software versions do not support ECC memory with NVIDIA vGPU.

If you are using a hypervisor software version or GPU that does not support ECC memory with NVIDIA vGPU and ECC memory is enabled, NVIDIA vGPU fails to start. In this situation, you must ensure that ECC memory is disabled on all GPUs if you are using NVIDIA vGPU.

2.13.1. Disabling ECC Memory

If ECC memory is unsuitable for your workloads but is enabled on your GPUs, disable it. You must also ensure that ECC memory is disabled on all GPUs if you are using NVIDIA vGPU with a hypervisor software version or a GPU that does not support ECC memory with NVIDIA vGPU. If your hypervisor software version or GPU does not support ECC memory and ECC memory is enabled, NVIDIA vGPU fails to start.

Where to perform this task depends on whether you are changing ECC memory settings for a physical GPU or a vGPU.

• For a physical GPU, perform this task from the hypervisor host.
• For a vGPU, perform this task from the VM to which the vGPU is assigned.
  Note:

  ECC memory must be enabled on the physical GPU on which the vGPUs reside.

Before you begin, ensure that NVIDIA Virtual GPU Manager is installed on your hypervisor. If you are changing ECC memory settings for a vGPU, also ensure that the NVIDIA vGPU software graphics driver is installed in the VM to which the vGPU is assigned.

1. Use nvidia-smi to list the status of all physical GPUs or vGPUs, and check for ECC noted as enabled.
   Copy

   Copied!

               
   
               
   # nvidia-smi -q
   
   ==============NVSMI LOG==============
   
   Timestamp                           : Mon Jun 17 18:36:45 2024
   Driver Version                      : 550.90.05 
   
   Attached GPUs                       : 1
   GPU 0000:02:00.0
   
   [...]
   
       Ecc Mode
           Current                     : Enabled
           Pending                     : Enabled
   
   [...]
           

2. Change the ECC status to off for each GPU for which ECC is enabled.
   • If you want to change the ECC status to off for all GPUs on your host machine or vGPUs assigned to the VM, run this command:
     Copy

     Copied!

                 
     
                 
     # nvidia-smi -e 0
             

   • If you want to change the ECC status to off for a specific GPU or vGPU, run this command:
     Copy

     Copied!

                 
     
                 
     # nvidia-smi -i id -e 0
             

     id is the index of the GPU or vGPU as reported by nvidia-smi.

     This example disables ECC for the GPU with index 0000:02:00.0.

     Copy

     Copied!

                 
     
                 
     # nvidia-smi -i 0000:02:00.0 -e 0
             

3. Reboot the host or restart the VM.
4. Confirm that ECC is now disabled for the GPU or vGPU.
   Copy

   Copied!

               
   
               
   # nvidia—smi —q
   
   ==============NVSMI LOG==============
   
   Timestamp                           : Mon Jun 17 18:37:53 2024
   Driver Version                      : 550.90.05 
   
   Attached GPUs                       : 1
   GPU 0000:02:00.0
   [...]
   
       Ecc Mode
           Current                     : Disabled
           Pending                     : Disabled
   
   [...]
           

If you later need to enable ECC on your GPUs or vGPUs, follow the instructions in Enabling ECC Memory.

2.13.2. Enabling ECC Memory

If ECC memory is suitable for your workloads and is supported by your hypervisor software and GPUs, but is disabled on your GPUs or vGPUs, enable it.

Where to perform this task depends on whether you are changing ECC memory settings for a physical GPU or a vGPU.

• For a physical GPU, perform this task from the hypervisor host.
• For a vGPU, perform this task from the VM to which the vGPU is assigned.
  Note:

  ECC memory must be enabled on the physical GPU on which the vGPUs reside.

Before you begin, ensure that NVIDIA Virtual GPU Manager is installed on your hypervisor. If you are changing ECC memory settings for a vGPU, also ensure that the NVIDIA vGPU software graphics driver is installed in the VM to which the vGPU is assigned.

1. Use nvidia-smi to list the status of all physical GPUs or vGPUs, and check for ECC noted as disabled.
   Copy

   Copied!

               
   
               
   # nvidia-smi -q
   
   ==============NVSMI LOG==============
   
   Timestamp                           : Mon Jun 17 18:36:45 2024
   Driver Version                      : 550.90.05 
   
   Attached GPUs                       : 1
   GPU 0000:02:00.0
   
   [...]
   
       Ecc Mode
           Current                     : Disabled
           Pending                     : Disabled
   
   [...]
           

2. Change the ECC status to on for each GPU or vGPU for which ECC is enabled.
   • If you want to change the ECC status to on for all GPUs on your host machine or vGPUs assigned to the VM, run this command:
     Copy

     Copied!

                 
     
                 
     # nvidia-smi -e 1
             

   • If you want to change the ECC status to on for a specific GPU or vGPU, run this command:
     Copy

     Copied!

                 
     
                 
     # nvidia-smi -i id -e 1
             

     id is the index of the GPU or vGPU as reported by nvidia-smi.

     This example enables ECC for the GPU with index 0000:02:00.0.

     Copy

     Copied!

                 
     
                 
     # nvidia-smi -i 0000:02:00.0 -e 1
             

3. Reboot the host or restart the VM.
4. Confirm that ECC is now enabled for the GPU or vGPU.
   Copy

   Copied!

               
   
               
   # nvidia—smi —q
   
   ==============NVSMI LOG==============
   
   Timestamp                           : Mon Jun 17 18:37:53 2024
   Driver Version                      : 550.90.05 
   
   Attached GPUs                       : 1
   GPU 0000:02:00.0
   [...]
   
       Ecc Mode
           Current                     : Enabled
           Pending                     : Enabled
   
   [...]
           

If you later need to disable ECC on your GPUs or vGPUs, follow the instructions in Disabling ECC Memory.

2.14. Configuring a vGPU VM for Use with NVIDIA GPUDirect Storage Technology

To use NVIDIA^® GPUDirect Storage^® technology with NVIDIA vGPU, you must install all the required software in the VM that is configured with NVIDIA vGPU.

Ensure that the prerequisites in Prerequisites for Using NVIDIA vGPU are met.

1. Install and configure the NVIDIA Virtual GPU Manager as explained in Installing and Configuring the NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM.
2. As root, log in to the VM that you configured with NVIDIA vGPU in the previous step.
3. Install the Mellanox OpenFabrics Enterprise Distribution for Linux (MLNX_OFED) in the VM as explained in Installation Procedure in Installing Mellanox OFED.

   In the command to run the installation script, specify the following options:

   • --with-nvmf
   • --with-nfsrdma
   • --enable-gds
   • --add-kernel-support
4. Install the NVIDIA vGPU software graphics driver for Linux in the VM from a distribution-specific package.
   Note:

   GPUDirect Storage technology does not support installation of the NVIDIA vGPU software graphics driver for Linux from a .run file.

   Follow the instructions for the Linux distribution that is installed in the VM:

   • Installing the NVIDIA vGPU Software Graphics Driver on Ubuntu from a Debian Package
   • Installing the NVIDIA vGPU Software Graphics Driver on Red Hat Distributions from an RPM Package
5. Install NVIDIA CUDA Toolkit from a .run file, deselecting the CUDA driver when selecting the CUDA components to install.
   Note:

   To avoid overwriting the NVIDIA vGPU software graphics driver that you installed in the previous step, do not install NVIDIA CUDA Toolkit from a distribution-specific package.

   For instructions, refer to Runfile Installation in NVIDIA CUDA Installation Guide for Linux.

6. Use the package manager of the Linux distribution that is installed in the VM to install the GPUDirect Storage technology packages, omitting the installation of the NVIDIA CUDA Toolkit packages.

   Follow the instructions in NVIDIA CUDA Installation Guide for Linux for the Linux distribution that is installed in the VM:

   • RHEL8/Rocky 8

     In the step to install CUDA, execute only the command to include all GPUDirect Storage technology packages:

     Copy

     Copied!

                 
     
                 
     sudo dnf install nvidia-gds
             

     
     

   • Ubuntu In the step to install CUDA, execute only the command to include all GPUDirect Storage technology packages:
     Copy

     Copied!

                 
     
                 
     sudo apt-get install nvidia-gds
             

     
     

After you configure a vGPU VM for use with NVIDIA GPUDirect Storage technology, you can license the NVIDIA vGPU software licensed products that you are using. For instructions, refer to Virtual GPU Client Licensing User Guide.

GPU pass-through is used to directly assign an entire physical GPU to one VM, bypassing the NVIDIA Virtual GPU Manager. In this mode of operation, the GPU is accessed exclusively by the NVIDIA driver running in the VM to which it is assigned; the GPU is not shared among VMs.

In pass-through mode, GPUs based on NVIDIA GPU architectures after the Maxwell architecture support error-correcting code (ECC).

GPU pass-through can be used in a server platform alongside NVIDIA vGPU, with some restrictions:

• A physical GPU can host NVIDIA vGPUs, or can be used for pass-through, but cannot do both at the same time. Some hypervisors, for example VMware vSphere ESXi, require a host reboot to change a GPU from pass-through mode to vGPU mode.
• A single VM cannot be configured for both vGPU and GPU pass-through at the same time.
• The performance of a physical GPU passed through to a VM can be monitored only from within the VM itself. Such a GPU cannot be monitored by tools that operate through the hypervisor, such as XenCenter or nvidia-smi (see Monitoring GPU Performance).

• The following BIOS settings must be enabled on your server platform:

  • VT-D/IOMMU
  • SR-IOV in Advanced Options
• All GPUs directly connected to each other through NVLink must be assigned to the same VM.

You can assign multiple physical GPUs to one VM. The maximum number of physical GPUs that you can assign to a VM depends on the maximum number of PCIe pass-through devices per VM that your chosen hypervisor can support. For more information, refer to the documentation for your hypervisor, for example:

• Citrix Hypervisor: Configuration limits
• Red Hat Enterprise Linux:
  • Red Hat Enterprise Linux 9 releases: Assigning a GPU to a virtual machine, Known Issues
  • Red Hat Enterprise Linux 8 releases: Assigning a GPU to a virtual machine, Known Issues
  • Red Hat Enterprise Linux 7 releases: GPU PCI Device Assignment
• VMware vSphere: vSphere 7.0 Configuration Limits

3.1. Display Resolutions for Physical GPUs

The display resolutions supported by a physical GPU depend on the NVIDIA GPU architecture and the NVIDIA vGPU software license that is applied to the GPU.

vWS Physical GPU Resolutions

GPUs that are licensed with a vWS license support a maximum combined resolution based on the number of available pixels, which is determined by the NVIDIA GPU architecture. You can choose between using a small number of high resolution displays or a larger number of lower resolution displays with these GPUs.

The following table lists the maximum number of displays per GPU at each supported display resolution for configurations in which all displays have the same resolution.

The following table provides examples of configurations with a mixture of display resolutions.

vApps or vCS Physical GPU Resolutions

GPUs that are licensed with a vApps or a vCS license support a single display with a fixed maximum resolution. The maximum resolution depends on the following factors:

• NVIDIA GPU architecture
• The NVIDIA vGPU software license that is applied to the GPU
• The operating system that is running in the on the system to which the GPU is assigned

3.2. Using GPU Pass-Through on Citrix Hypervisor

You can configure a GPU for pass-through on Citrix Hypervisor by using XenCenter or by using the xe command.

The following additional restrictions apply when GPU pass-through is used in a server platform alongside NVIDIA vGPU:

• The performance of a physical GPU passed through to a VM cannot be monitored through XenCenter.
• nvidia-smi in dom0 no longer has access to the GPU.
• Pass-through GPUs do not provide console output through XenCenter’s VM Console tab. Use a remote graphics connection directly into the VM to access the VM’s OS.

3.2.1. Configuring a VM for GPU Pass Through by Using XenCenter

Select the Pass-through whole GPU option as the GPU type in the VM’s Properties:

Figure 14. Using XenCenter to configure a pass-through GPU

After configuring a Citrix Hypervisor VM for GPU pass through, install the NVIDIA graphics driver in the guest OS on the VM as explained in Installing the NVIDIA vGPU Software Graphics Driver.

3.2.2. Configuring a VM for GPU Pass Through by Using xe

Create a vgpu object with the passthrough vGPU type:

            

            
[root@xenserver ~]# xe vgpu-type-list model-name="passthrough"
uuid ( RO)                : fa50b0f0-9705-6c59-689e-ea62a3d35237
         vendor-name ( RO):
          model-name ( RO): passthrough
    framebuffer-size ( RO): 0

[root@xenserver ~]# xe vgpu-create vm-uuid=753e77a9-e10d-7679-f674-65c078abb2eb vgpu-type-uuid=fa50b0f0-9705-6c59-689e-ea62a3d35237 gpu-group-uuid=585877ef-5a6c-66af-fc56-7bd525bdc2f6
6aa530ec-8f27-86bd-b8e4-fe4fde8f08f9
[root@xenserver ~]#
        

After configuring a Citrix Hypervisor VM for GPU pass through, install the NVIDIA graphics driver in the guest OS on the VM as explained in Installing the NVIDIA vGPU Software Graphics Driver.

3.3. Using GPU Pass-Through on Red Hat Enterprise Linux KVM or Ubuntu

You can configure a GPU for pass-through on Red Hat Enterprise Linux Kernel-based Virtual Machine (KVM) or Ubuntu by using any of the following tools:

• The Virtual Machine Manager (virt-manager) graphical tool
• The virsh command
• The QEMU command line

Before configuring a GPU for pass-through on Red Hat Enterprise Linux KVM or Ubuntu, ensure that the following prerequisites are met:

• Red Hat Enterprise Linux KVM or Ubuntu is installed.
• A virtual disk has been created.
  Note:

  Do not create any virtual disks in /root.

• A virtual machine has been created.

3.3.1. Configuring a VM for GPU Pass-Through by Using Virtual Machine Manager (virt-manager)

For more information about using Virtual Machine Manager, see the following topics in the documentation for Red Hat Enterprise Linux 7:

• Managing Guests with the Virtual Machine Manager (virt-manager)
• Starting virt-manager
• Assigning a PCI Device with virt-manager

1. Start virt-manager.
2. In the virt-manager main window, select the VM that you want to configure for pass-through.
3. From the Edit menu, choose Virtual Machine Details.
4. In the virtual machine hardware information window that opens, click Add Hardware.
5. In the Add New Virtual Hardware dialog box that opens, in the hardware list on the left, select PCI Host Device.
6. From the Host Device list that appears, select the GPU that you want to assign to the VM and click Finish.

If you want to remove a GPU from the VM to which it is assigned, in the virtual machine hardware information window, select the GPU and click Remove.

After configuring the VM for GPU pass through, install the NVIDIA graphics driver in the guest OS on the VM as explained in Installing the NVIDIA vGPU Software Graphics Driver.

3.3.2. Configuring a VM for GPU Pass-Through by Using virsh

For more information about using virsh, see the following topics in the documentation for Red Hat Enterprise Linux 7:

• Managing Guest Virtual Machines with virsh
• Assigning a PCI Device with virsh

1. Verify that the vfio-pci module is loaded.
   Copy

   Copied!

               
   
               
   # lsmod | grep vfio-pci
           

2. Obtain the PCI device bus/device/function (BDF) of the GPU that you want to assign in pass-through mode to a VM.
   Copy

   Copied!

               
   
               
   # lspci | grep NVIDIA
           

   The NVIDIA GPUs listed in this example have the PCI device BDFs 85:00.0 and 86:00.0.

   Copy

   Copied!

               
   
               
   # lspci | grep NVIDIA
    85:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
    86:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
           

3. Obtain the full identifier of the GPU from its PCI device BDF.
   Copy

   Copied!

               
   
               
   # virsh nodedev-list --cap pci| grep transformed-bdf
           

   transformed-bdf

   The PCI device BDF of the GPU with the colon and the period replaced with underscores, for example, 85_00_0.

   This example obtains the full identifier of the GPU with the PCI device BDF 85:00.0.

   Copy

   Copied!

               
   
               
   # virsh nodedev-list --cap pci| grep 85_00_0
   pci_0000_85_00_0
           

4. Obtain the domain, bus, slot, and function of the GPU.
   Copy

   Copied!

               
   
               
   virsh nodedev-dumpxml full-identifier| egrep 'domain|bus|slot|function'
           

   full-identifier

   The full identifier of the GPU that you obtained in the previous step, for example, pci_0000_85_00_0.

   This example obtains the domain, bus, slot, and function of the GPU with the PCI device BDF 85:00.0.

   Copy

   Copied!

               
   
               
   # virsh nodedev-dumpxml pci_0000_85_00_0| egrep 'domain|bus|slot|function'
       <domain>0x0000</domain>
       <bus>0x85</bus>
       <slot>0x00</slot>
       <function>0x0</function>
         <address domain='0x0000' bus='0x85' slot='0x00' function='0x0'/>
           

5. In virsh, open for editing the XML file of the VM that you want to assign the GPU to.
   Copy

   Copied!

               
   
               
   # virsh edit vm-name
           

   vm-name

   The name of the VM to that you want to assign the GPU to.

6. Add a device entry in the form of an address element inside the source element to assign the GPU to the guest VM. You can optionally add a second address element after the source element to set a fixed PCI device BDF for the GPU in the guest operating system.
   Copy

   Copied!

               
   
               
   <hostdev mode='subsystem' type='pci' managed='yes'>
     <source>
       <address domain='domain' bus='bus' slot='slot' function='function'/>
     </source>
       <address type='pci' domain='0x0000' bus='0x00' slot='0x05' function='0x0'/>
   </hostdev>
           

   domain

   bus

   slot

   function

   The domain, bus, slot, and function of the GPU, which you obtained in the previous step.

   This example adds a device entry for the GPU with the PCI device BDF 85:00.0 and fixes the BDF for the GPU in the guest operating system.

   Copy

   Copied!

               
   
               
   <hostdev mode='subsystem' type='pci' managed='yes'>
     <source>
       <address domain='0x0000' bus='0x85' slot='0x00' function='0x0'/>
     </source>
       <address type='pci' domain='0x0000' bus='0x00' slot='0x05' function='0x0'/>
   </hostdev>
           

7. Start the VM that you assigned the GPU to.
   Copy

   Copied!

               
   
               
   # virsh start vm-name
           

   vm-name

   The name of the VM that you assigned the GPU to.

After configuring the VM for GPU pass through, install the NVIDIA graphics driver in the guest OS on the VM as explained in Installing the NVIDIA vGPU Software Graphics Driver.

3.3.3. Configuring a VM for GPU Pass-Through by Using the QEMU Command Line

1. Obtain the PCI device bus/device/function (BDF) of the GPU that you want to assign in pass-through mode to a VM.
   Copy

   Copied!

               
   
               
   # lspci | grep NVIDIA
           

   The NVIDIA GPUs listed in this example have the PCI device BDFs 85:00.0 and 86:00.0.

   Copy

   Copied!

               
   
               
   # lspci | grep NVIDIA
    85:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
    86:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
           

2. Add the following option to the QEMU command line:
   Copy

   Copied!

               
   
               
   -device vfio-pci,host=bdf
           

   bdf

   The PCI device BDF of the GPU that you want to assign in pass-through mode to a VM, for example, 85:00.0.

   This example assigns the GPU with the PCI device BDF 85:00.0 in pass-through mode to a VM.

   Copy

   Copied!

               
   
               
   -device vfio-pci,host=85:00.0
           

After configuring the VM for GPU pass through, install the NVIDIA graphics driver in the guest OS on the VM as explained in Installing the NVIDIA vGPU Software Graphics Driver.

3.3.4. Preparing a GPU Configured for vGPU for Use in Pass-Through Mode

The mode in which a physical GPU is being used determines the Linux kernel module to which the GPU is bound. If you want to switch the mode in which a GPU is being used, you must unbind the GPU from its current kernel module and bind it to the kernel module for the new mode. After binding the GPU to the correct kernel module, you can then configure it for pass-through.

When the Virtual GPU Manager is installed on a Red Hat Enterprise Linux KVM or Ubuntu host, the physical GPUs on the host are bound to the nvidia kernel module. A physical GPU that is bound to the nvidia kernel module can be used only for vGPU. To enable the GPU to be passed through to a VM, the GPU must be unbound from nvidia kernel module and bound to the vfio-pci kernel module.
Before you begin, ensure that you have the domain, bus, slot, and function of the GPU that you are preparing for use in pass-through mode. For instructions, see Getting the BDF and Domain of a GPU on a Linux with KVM Hypervisor.

1. If you are using a GPU that supports SR-IOV, such as a GPU based on the NVIDIA Ampere architecture, disable the virtual function for the GPU in the sysfs file system.

   If your GPU does not support SR-IOV, omit this step.

   Note:

   Before performing this step, ensure that the GPU is not being used by any other processes, such as CUDA applications, monitoring applications, or the nvidia-smi command.

   Use the custom script sriov-manage provided by NVIDIA vGPU software for this purpose.

   Copy

   Copied!

               
   
               
   # /usr/lib/nvidia/sriov-manage -d domain:bus:slot.function
           

   domain

   bus

   slot

   function

   The domain, bus, slot, and function of the GPU, without the 0x prefix.

   This example disables the virtual function for the GPU with the domain 00, bus 06, slot 0000, and function 0.

   Copy

   Copied!

               
   
               
   # /usr/lib/nvidia/sriov-manage -d 00:06:0000.0
           

2. Determine the kernel module to which the GPU is bound by running the lspci command with the -k option on the NVIDIA GPUs on your host.
   Copy

   Copied!

               
   
               
   # lspci -d 10de: -k
           

   The Kernel driver in use: field indicates the kernel module to which the GPU is bound.

   The following example shows that the NVIDIA Tesla M60 GPU with BDF06:00.0 is bound to the nvidia kernel module and is being used for vGPU.

   Copy

   Copied!

               
   
               
   06:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
            Subsystem: NVIDIA Corporation Device 115e
            Kernel driver in use: nvidia
           

3. To ensure that no clients are using the GPU, acquire the unbind lock of the GPU.
   1. Ensure that no VM is running to which a vGPU on the physical GPU is assigned and that no process running on the host is using that GPU. Processes on the host that use the GPU include the nvidia-smi command and all processes based on the NVIDIA Management Library (NVML).
   2. Change to the directory in the proc file system that represents the GPU.
      Copy

      Copied!

                  
      
                  
      # cd /proc/driver/nvidia/gpus/domain\:bus\:slot.function
              

      domain

      bus

      slot

      function

      The domain, bus, slot, and function of the GPU, without a 0x prefix.

      This example changes to the directory in the proc file system that represents the GPU with the domain 0000 and PCI device BDF 06:00.0.

      Copy

      Copied!

                  
      
                  
      # cd /proc/driver/nvidia/gpus/0000\:06\:00.0
              

   3. Write the value 1 to the unbindLock file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo 1 > unbindLock
              

   4. Confirm that the unbindLock file now contains the value 1.
      Copy

      Copied!

                  
      
                  
      # cat unbindLock
      1
              

      If the unbindLock file contains the value 0, the unbind lock could not be acquired because a process or client is using the GPU.

4. Unbind the GPU from nvidia kernel module.
   1. Change to the sysfs directory that represents the nvidia kernel module.
      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/drivers/nvidia
              

   2. Write the domain, bus, slot, and function of the GPU to the unbind file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo domain:bus:slot.function > unbind
              

      domain

      bus

      slot

      function

      The domain, bus, slot, and function of the GPU, without a 0x prefix.

      This example writes the domain, bus, slot, and function of the GPU with the domain 0000 and PCI device BDF 06:00.0.

      Copy

      Copied!

                  
      
                  
      # echo 0000:06:00.0 > unbind
              

5. Bind the GPU to the vfio-pci kernel module.
   1. Change to the sysfs directory that contains the PCI device information for the physical GPU.
      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/devices/domain\:bus\:slot.function
              

      domain

      bus

      slot

      function

      The domain, bus, slot, and function of the GPU, without a 0x prefix.

      This example changes to the sysfs directory that contains the PCI device information for the GPU with the domain 0000 and PCI device BDF 06:00.0.

      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/devices/0000\:06\:00.0
              

   2. Write the kernel module name vfio-pci to the driver_override file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo vfio-pci > driver_override
              

   3. Change to the sysfs directory that represents the nvidia kernel module.
      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/drivers/vfio-pci
              

   4. Write the domain, bus, slot, and function of the GPU to the bind file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo domain:bus:slot.function > bind
              

      domain

      bus

      slot

      function

      The domain, bus, slot, and function of the GPU, without a 0x prefix.

      This example writes the domain, bus, slot, and function of the GPU with the domain 0000 and PCI device BDF 06:00.0.

      Copy

      Copied!

                  
      
                  
      # echo 0000:06:00.0 > bind
              

   5. Change back to the sysfs directory that contains the PCI device information for the physical GPU.
      Copy

      Copied!

                  
      
                  
      # cd /sys/bus/pci/devices/domain\:bus\:slot.function
              

   6. Clear the content of the driver_override file in this directory.
      Copy

      Copied!

                  
      
                  
      # echo > driver_override
              

You can now configure the GPU for use in pass-through mode as explained in Using GPU Pass-Through on Red Hat Enterprise Linux KVM or Ubuntu.

3.4. Using GPU Pass-Through on Microsoft Windows Server

On supported versons of Microsoft Windows Server with Hyper-V role, you can use Discrete Device Assignment (DDA) to enable a VM to access a GPU directly.

3.4.1. Assigning a GPU to a VM on Microsoft Windows Server with Hyper-V

Perform this task in Windows PowerShell. If you do not know the location path of the GPU that you want to assign to a VM, use Device Manager to obtain it.

If you are using an actively cooled NVIDIA Quadro graphics card such as the RTX 8000 or RTX 6000, you must also pass through the audio device on the graphics card.

Ensure that the following prerequisites are met:

• Windows Server with Desktop Experience and the Hyper-V role are installed and configured on your server platform, and a VM is created.

  For instructions, refer to the following articles on the Microsoft technical documentation site:

  • Install Server with Desktop Experience
  • Install the Hyper-V role on Windows Server
  • Create a virtual switch for Hyper-V virtual machines
  • Create a virtual machine in Hyper-V
• The guest OS is installed in the VM.
• The VM is powered off.

1. Obtain the location path of the GPU that you want to assign to a VM.
   1. In the device manager, context-click the GPU and from the menu that pops up, choose Properties.
   2. In the Properties window that opens, click the Details tab and in the Properties drop-down list, select Location paths.

   An example location path is as follows:

   Copy

   Copied!

               
   
               
   PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)
           

2. If you are using an actively cooled NVIDIA Quadro graphics card, obtain the location path of the audio device on the graphics card and disable the device.
   1. In the device manager, from the View menu, choose Devices by connection.
   2. Navigate to ACPI x64-based PC > Microsoft ACPI-Compliant System > PCI Express Root Complex > PCI-to-PCI Bridge.
   3. Context-click High Definition Audio Controller and from the menu that pops up, choose Properties.
   4. In the Properties window that opens, click the Details tab and in the Properties drop-down list, select Location paths.
   5. Context-click High Definition Audio Controller again and from the menu that pops up, choose Disable device.
3. Dismount the GPU and, if present, the audio device from host to make them unavailable to the host so that they can be used solely by the VM.

   For each device that you are dismounting, type the following command:

   Copy

   Copied!

               
   
               
   Dismount-VMHostAssignableDevice -LocationPath gpu-device-location -force
           

   gpu-device-location

   The location path of the GPU or the audio device that you obtained previously.

   This example dismounts the GPU at the location path PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000).

   Copy

   Copied!

               
   
               
   Dismount-VMHostAssignableDevice -LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)" -force
           

4. Assign the GPU and, if present, the audio device that you dismounted in the previous step to the VM.

   For each device that you are assigning, type the following command:

   Copy

   Copied!

               
   
               
   Add-VMAssignableDevice -LocationPath gpu-device-location -VMName vm-name
           

   gpu-device-location

   The location path of the GPU or the audio device that you dismounted in the previous step.

   vm-name

   The name of the VM to which you are attaching the GPU or the audio device.

   Note:

   You can assign a pass-through GPU and, if present, its audio device to only one virtual machine at a time.

   This example assigns the GPU at the location path PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000) to the VM VM1.

   Copy

   Copied!

               
   
               
   Add-VMAssignableDevice -LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)" -VMName VM1
           

5. Power on the VM. The guest OS should now be able to use the GPU and, if present, the audio device.

After assigning a GPU to a VM, install the NVIDIA graphics driver in the guest OS on the VM as explained in Installing the NVIDIA vGPU Software Graphics Driver.

3.4.2. Returning a GPU to the Host OS from a VM on Windows Server with Hyper-V

Perform this task in the Windows PowerShell.

If you are using an actively cooled NVIDIA Quadro graphics card such as the RTX 8000 or RTX 6000, you must also return the audio device on the graphics card.

1. List the GPUs and, if present, the audio devices that are currently assigned to the virtual machine (VM).
   Copy

   Copied!

               
   
               
   Get-VMAssignableDevice -VMName vm-name
           

   vm-name

   The name of the VM whose assigned GPUs and audio devices you want to list.

2. Shut down the VM to which the GPU and any audio devices are assigned.
3. Remove the GPU and, if present, the audio device from the VM to which they are assigned.

   For each device that you are removing, type the following command:

   Copy

   Copied!

               
   
               
   Remove-VMAssignableDevice –LocationPath gpu-device-location -VMName vm-name
           

   gpu-device-location

   The location path of the GPU or the audio device that you are removing, which you obtained previously.

   vm-name

   The name of the VM from which you are removing the GPU or the audio device.

   This example removes the GPU at the location path PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000) from the VM VM1.

   Copy

   Copied!

               
   
               
   Remove-VMAssignableDevice –LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)" -VMName VM1
           

   After the GPU and, if present, its audio device are removed from the VM, they are unavailable to the host operating system (OS) until you remount them on the host OS.

4. Remount the GPU and, if present, its audio device on the host OS.

   For each device that you are remounting, type the following command:

   Copy

   Copied!

               
   
               
   Mount-VMHostAssignableDevice –LocationPath gpu-device-location
           

   gpu-device-location

   The location path of the GPU or the audio device that you are remounting, which you specified in the previous step to remove the GPU or the audio device from the VM.

   This example remounts the GPU at the location path PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000) on the host OS.

   Copy

   Copied!

               
   
               
   Mount-VMHostAssignableDevice -LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)"
           

   The host OS should now be able to use the GPU and, if present, its audio device.

3.5. Using GPU Pass-Through on VMware vSphere

On VMware vSphere, you can use Virtual Dedicated Graphics Acceleration (vDGA) to enable a VM to access a GPU directly. vDGA is a feature of VMware vSphere that dedicates a single physical GPU on an ESXi host to a single virtual machine.
Before configuring a vSphere VM with vDGA, ensure that these prerequisites are met

• The VM and the ESXi host are configured as explained in Preparing for vDGA Capabilities in the VMware Horizon documentation.
• The VM is powered off.

1. Open the vCenter Web UI.
2. In the vCenter Web UI, right-click the ESXi host and choose Configure.
3. From the Hardware menu, choose PCI Devices.
4. On the PCI Devices page that opens, click ALL PCI DEVICES and in the table of devices, select the GPU.
   Note:

   When selecting the GPU to pass through, you must select only the physical device. To list only NVIDIA physical devices, set the filter on the Vendor Name field to NVIDIA and filter out any virtual function devices of the GPU by setting the filter on the ID field to 00.0.

   

5. Click TOGGLE PASSTHROUGH.
6. Reboot the ESXi host.
7. After the ESXi host has booted, right-click the VM and choose Edit Settings.
8. From the New Device menu, choose PCI Device and click Add.
9. On the page that opens, from the New Device drop-down list, select the GPU.
10. Click Reserve all memory and click OK.
11. Start the VM.

For more information about vDGA, see the following topics in the VMware Horizon documentation:

• Configuring 3D Rendering for Desktops
• Configure RHEL 6 for vDGA

After configuring a vSphere VM with vDGA, install the NVIDIA graphics driver in the guest OS on the VM as explained in Installing the NVIDIA vGPU Software Graphics Driver.

The process for installing the NVIDIA vGPU software graphics driver depends on the OS that you are using. However, for any OS, the process for installing the driver is the same in a VM configured with vGPU, in a VM that is running pass-through GPU, or on a physical host in a bare-metal deployment.

After you install the NVIDIA vGPU software graphics driver, you can license any NVIDIA vGPU software licensed products that you are using.

4.1. Installing the NVIDIA vGPU Software Graphics Driver and NVIDIA Control Panel on Windows

To fully enable GPU operation in a VM or on a bare-metal host, the NVIDIA vGPU software graphics driver must be installed. If the NVIDIA Control Panel app is not installed when the graphics driver is installed, you can install it separately from the graphics driver.

4.1.1. Installing the NVIDIA vGPU Software Graphics Driver on Windows

Installation in a VM: After you create a Windows VM on the hypervisor and boot the VM, the VM should boot to a standard Windows desktop in VGA mode at 800×600 resolution. You can use the Windows screen resolution control panel to increase the resolution to other standard resolutions, but to fully enable GPU operation, the NVIDIA vGPU software graphics driver must be installed. Windows guest VMs are supported on all NVIDIA vGPU types, namely: Q-series, B-series, and A-series NVIDIA vGPU types.

Installation on bare metal: When the physical host is booted before the NVIDIA vGPU software graphics driver is installed, boot and the primary display are handled by an on-board graphics adapter. To install the NVIDIA vGPU software graphics driver, access the Windows desktop on the host by using a display connected through the on-board graphics adapter.

The procedure for installing the driver is the same in a VM and on bare metal.

1. Copy the NVIDIA Windows driver package to the guest VM or physical host where you are installing the driver.
2. Execute the package to unpack and run the driver installer.

   Figure 15. NVIDIA driver installation

   

3. Click through the license agreement.
4. Select Express Installation and click NEXT. After the driver installation is complete, the installer may prompt you to restart the platform.
5. If prompted to restart the platform, do one of the following:
   • Select Restart Now to reboot the VM or physical host.
   • Exit the installer and reboot the VM or physical host when you are ready.

   After the VM or physical host restarts, it boots to a Windows desktop.

6. Verify that the NVIDIA driver is running.
   1. Right-click on the desktop.
   2. From the menu that opens, choose NVIDIA Control Panel.
   3. In the NVIDIA Control Panel, from the Help menu, choose System Information.

      NVIDIA Control Panel reports the vGPU or physical GPU that is being used, its capabilities, and the NVIDIA driver version that is loaded.

      Figure 16. Verifying NVIDIA driver operation using NVIDIA Control Panel

      

Installation in a VM: After you install the NVIDIA vGPU software graphics driver, you can license any NVIDIA vGPU software licensed products that you are using. For instructions, refer to Virtual GPU Client Licensing User Guide.

Installation on bare metal: After you install the NVIDIA vGPU software graphics driver, complete the bare-metal deployment as explained in Bare-Metal Deployment.

4.1.2. Installing the Standalone NVIDIA Control Panel App

The NVIDIA Control Panel app is now distributed through the Microsoft Store. If your system does not allow the installation apps from the Microsoft Store, the NVIDIA Control Panel app is not installed when the NVIDIA vGPU software graphics driver for Windows is installed.
Your system might not allow the installation apps from the Microsoft Store for any of the following reasons:

• The Microsoft Store app is disabled.
• Your system is not connected to the Internet
• Installation of apps from the Microsoft Store is blocked by your system settings.

You can install the NVIDIA Control Panel app separately from the graphics driver by downloading and running the standalone NVIDIA Control Panel installer that is available from NVIDIA Licensing Portal.

1. Download and extract the standalone NVIDIA Control Panel installer from NVIDIA Licensing Portal.
2. Copy the extracted standalone NVIDIA Control Panel installer to the guest VM or physical host where you are installing the NVIDIA Control Panel app.
3. Double-click the installer executable file to start the installer.
4. When asked if you want to allow the installer app to make changes to your device, click Yes.
5. Accept the NVIDA software license agreement.
6. Select the Express installation option and click NEXT.
7. When the installation is complete, click CLOSE to close the installer. The NVIDIA Control Panel app opens.

4.2. Installing the NVIDIA vGPU Software Graphics Driver on Linux

The NVIDIA vGPU software graphics driver for Linux is distributed as a .run file that can be installed on all supported Linux distributions. The driver is also distributed as a Debian package for Ubuntu distributions and as an RPM package for Red Hat distributions.

Installation in a VM: After you create a Linux VM on the hypervisor and boot the VM, install the NVIDIA vGPU software graphics driver in the VM to fully enable GPU operation. Linux guest VMs are supported on all NVIDIA vGPU types, namely: Q-series, B-series, and A-series NVIDIA vGPU types.

Installation on bare metal: When the physical host is booted before the NVIDIA vGPU software graphics driver is installed, the vesa Xorg driver starts the X server. If a primary display device is connected to the host, use the device to access the desktop. Otherwise, use secure shell (SSH) to log in to the host from a remote host. In addition to the proprietary release of the NVIDIA vGPU software graphics driver for Linux, a release that is based on NVIDIA Linux open GPU kernel modules is also available. The release that is based on NVIDIA Linux open GPU kernel modules is compatible with the following NVIDIA vGPU software deployments:

• NVIDIA vGPU deployments on GPUs that are based on the NVIDIA Ada Lovelace GPU architecture or later architectures
• Bare-metal deployments on GPUs that are based on the NVIDIA Turing GPU architecture or later architectures

The release that is based on NVIDIA Linux open GPU kernel modules can be installed only from the .run file, not from a Debian package or RPM package.

The procedure for installing the driver is the same in a VM and on bare metal.
Before installing the NVIDIA vGPU software graphics driver, ensure that the following prerequisites are met:

• OpenSSL is installed in the VM. If OpenSSL is not installed, the VM will not be able to obtain NVIDIA vGPU software licenses.
• NVIDIA Direct Rendering Manager Kernel Modesetting (DRM KMS) is disabled. By default, DRM KMS is disabled. However, if it has been enabled, remove nvidia-drm.modeset=1 from the kernel command-line options.
• If the VM uses UEFI boot, ensure that secure boot is disabled.
• If the Nouveau driver for NVIDIA graphics cards is present, disable it. For instructions, refer to as explained in Disabling the Nouveau Driver for NVIDIA Graphics Cards.
• If you are using a Linux OS for which the Wayland display server protocol is enabled by default, disable it as explained in Disabling the Wayland Display Server Protocol for Red Hat Enterprise Linux.

How to install the NVIDIA vGPU softwaregraphics driver on Linux depends on the distribution format from which you are installing the driver. For detailed instructions, refer to:

• Installing the NVIDIA vGPU Software Graphics Driver on Linux from a .run File
• Installing the NVIDIA vGPU Software Graphics Driver on Ubuntu from a Debian Package
• Installing the NVIDIA vGPU Software Graphics Driver on Red Hat Distributions from an RPM Package

Installation in a VM: After you install the NVIDIA vGPU software graphics driver, you can license any NVIDIA vGPU software licensed products that you are using. For instructions, refer to Virtual GPU Client Licensing User Guide.

Installation on bare metal: After you install the NVIDIA vGPU software graphics driver, complete the bare-metal deployment as explained in Bare-Metal Deployment.

4.2.1. Installing the NVIDIA vGPU Software Graphics Driver on Linux from a .run File

You can use the .run file to install the NVIDIA vGPU software graphics driver on any supported Linux distribution.

Installation of the NVIDIA vGPU software graphics driver for Linux from a .run file requires:

• Compiler toolchain
• Kernel headers

If a driver has previously been installed on the guest VM or physical host from a Debian package or RPM package, uninstall that driver before installing the driver from a .run file.

If Dynamic Kernel Module Support (DKMS) is enabled, ensure that the dkms package is installed.

1. Copy the NVIDIA vGPU software Linux driver package, for example NVIDIA-Linux_x86_64-550.90.07-grid.run, to the guest VM or physical host where you are installing the driver.
2. Before attempting to run the driver installer, exit the X server and terminate all OpenGL applications.
   • On Red Hat Enterprise Linux and CentOS systems, exit the X server by transitioning to runlevel 3:
     Copy

     Copied!

                 
     
                 
     [nvidia@localhost ~]$ sudo init 3
             

   • On Ubuntu platforms, do the following:
     1. Switch to a console login prompt.
        • If you have access to the terminal’s function keys, press CTRL-ALT-F1.
        • If you are accessing the guest VM or physical host through VNC or a web browser and do not have access to the terminal’s function keys, run the chvt command of the OS as root.
          Copy

          Copied!

                      
          
                      
          [nvidia@localhost ~]$ sudo chvt 3
                  

     2. Log in and shut down the display manager:

        • For Ubuntu 18 and later releases, stop the gdm service.

          Copy

          Copied!

                      
          
                      
          [nvidia@localhost ~]$ sudo service gdm stop
                  

        • For releases earlier than Ubuntu 18, stop the lightdm service.

          Copy

          Copied!

                      
          
                      
          [nvidia@localhost ~]$ sudo service lightdm stop
                  

3. From a console shell, run the driver installer as the root user.
   • To install the proprietary release of the driver, run the driver installer without any additional options.
     Copy

     Copied!

                 
     
                 
     sudo sh ./NVIDIA-Linux_x86_64-550.90.07-grid.run
             

   • To install the release that is based on NVIDIA Linux open GPU kernel modules, run the driver installer with the -m=kernel-open option.
     Copy

     Copied!

                 
     
                 
     sudo sh ./NVIDIA-Linux_x86_64-550.90.07-grid.run -m=kernel-open
             

   If DKMS is enabled, set the -dkms option. This option requires the dkms package to be installed.

   Copy

   Copied!

               
   
               
   sudo sh ./NVIDIA-Linux_x86_64-550.90.07-grid.run -dkms
           

   In some instances, the installer may fail to detect the installed kernel headers and sources. In this situation, rerun the installer, specifying the kernel source path with the --kernel-source-path option.

   Copy

   Copied!

               
   
               
   sudo sh ./NVIDIA-Linux_x86_64-550.90.07-grid.run \
   –kernel-source-path=/usr/src/kernels/3.10.0-229.11.1.el7.x86_64
           

4. When prompted, accept the option to update the X configuration file (xorg.conf).

   Figure 17. Update xorg.conf settings

   

5. After the installation is complete, select OK to exit the installer.
6. Verify that the NVIDIA driver is operational.
   1. Reboot the system and log in.
   2. Run nvidia-settings.
      Copy

      Copied!

                  
      
                  
      [nvidia@localhost ~]$ nvidia-settings
              

      The NVIDIA X Server Settings dialog box opens to show that the NVIDIA driver is operational.