Microsoft Azure Local

Virtual GPU Software R580 for Microsoft Azure Local Release Notes

Release information for all users of NVIDIA virtual GPU software and hardware on Microsoft Azure Local.

These Release Notes summarize current status, information on validated platforms, and known issues with NVIDIA vGPU software and associated hardware on Microsoft Azure Local.

1.1. NVIDIA vGPU Software Driver Versions

Each release in this release family of NVIDIA vGPU software includes a specific version of the NVIDIA Virtual GPU Manager, NVIDIA Windows driver, and NVIDIA Linux driver.

For details of which Microsoft Azure Local releases are supported, see Hypervisor Software Releases.

1.2. Compatibility Requirements for the NVIDIA vGPU Manager and Guest VM Driver

The releases of the NVIDIA vGPU Manager and guest VM drivers that you install must be compatible. If you install an incompatible guest VM driver release for the release of the vGPU Manager that you are using, the NVIDIA vGPU fails to load.

See VM running an incompatible NVIDIA vGPU guest driver fails to initialize vGPU when booted.

Compatible NVIDIA vGPU Manager and Guest VM Driver Releases

The following combinations of NVIDIA vGPU Manager and guest VM driver releases are compatible with each other.

• NVIDIA vGPU Manager with guest VM drivers from the same release
• NVIDIA vGPU Manager from a later major release branch with guest VM drivers from the previous branch
• NVIDIA vGPU Manager from a later long-term support branch with guest VM drivers from the previous long-term support branch

The following table lists the specific software releases that are compatible with the components in the NVIDIA vGPU software 19 major release branch.

Incompatible NVIDIA vGPU Manager and Guest VM Driver Releases

The following combinations of NVIDIA vGPU Manager and guest VM driver releases are incompatible with each other.

• NVIDIA vGPU Manager from a later major release branch with guest VM drivers from a production branch two or more major releases before the release of the vGPU Manager
• NVIDIA vGPU Manager from an earlier major release branch with guest VM drivers from a later branch

The following table lists the specific software releases that are incompatible with the components in the NVIDIA vGPU software 19 major release branch.

1.3. Updates in Release 19.0

New Features in Release 19.0

• New B-series vGPU profiles with 3 GB of frame buffer on supported GPUs based on the NVIDIA Ada Lovelace and NVIDIA Blackwell GPU architectures
• Support for Virtualization Based Security (VBS) in Windows 11 guest VMs
• Miscellaneous bug fixes

This release family of NVIDIA vGPU software provides support for several NVIDIA GPUs on validated server hardware platforms, Microsoft Azure Local hypervisor software versions, and guest operating systems. It also supports the version of NVIDIA CUDA Toolkit that is compatible with R580 drivers.

2.1. Supported NVIDIA GPUs and Validated Server Platforms

This release of NVIDIA vGPU software on Microsoft Azure Local provides support for several NVIDIA GPUs running on validated server hardware platforms.

For a list of validated server platforms, refer to NVIDIA GRID Certified Servers.

The supported products for each type of NVIDIA vGPU software deployment depend on the GPU.

GPUs Based on the NVIDIA Ada Lovelace Architecture

GPUs Based on the NVIDIA Ampere Architecture

2.1.1. Support for a Mixture of Time-Sliced vGPU Types on the Same GPU

Microsoft Azure Local does not support a mixture of different types of time-sliced vGPUs on the same GPU. All vGPUs on a single GPU must be of the same type: They must belong to the same vGPU series and be allocated the same amount of frame buffer.

For example, the following combinations of vGPUs are not supported on the same GPU:

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

A mixture of time-sliced vGPUs from different virtual GPU series on the same server is not supported. Therefore, all vGPUs on different physical GPUs on the same card must belong to the same vGPU series. However, the requirement for all vGPUs to be allocated the same amount of frame buffer doesn’t extend across physical GPUs on the same card. Different physical GPUs on the same card may host vGPUs with different amounts of frame buffer. For example, an NVIDIA A16 card has four physical GPUs, and can support several types of virtual GPU provided they all belong to the same vGPU series.

• A configuration with A16-16Q vGPUs on GPU 0 and GPU 1, A16-8Q vGPUs on GPU 2, and A16-4Q vGPUs on GPU3 is valid.
• A configuration with A16-4A vGPUs on GPU0 and A16-4Q vGPUs on GPU1 is invalid.
• A configuration with a mixture of A16-4A vGPUs and A16-4Q vGPUs on GPU0 is invalid.
• A configuration with a mixture of A16-8Q vGPUs and A16-4Q vGPUs on GPU0 is invalid.

2.1.2. 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.

2.2. Hypervisor Software Releases

Changes to Microsoft Product Names

Microsoft has changed the name of Azure Stack HCI to Azure Local. For more information, refer to New name for Azure Stack HCI on the Microsoft documentation portal.

For consistency with the changed product names, the name of the GridSW-Azure-Stack-HCI directory in the archive file in which the driver package for the Virtual GPU Manager is distributed is changed to GridSW-Azure-Local.

Supported Microsoft Azure Local Releases

This release of NVIDIA vGPU software is supported on the hypervisor software releases listed in the table.

2.3. Guest OS Support

2.3.1. Windows Guest OS Support

NVIDIA vGPU software supports only the 64-bit Windows releases listed as a guest OS on Microsoft Azure Local. The releases of Microsoft Azure Local for which a Windows release is supported depend on whether NVIDIA vGPU or pass-through GPU is used.

2.3.1.1. Windows Guest OS Support in Release 19.0

• Windows Server 2025
• Windows Server 2022
• Windows 11 24H2 and all Windows 11 releases supported by Microsoft up to and including this release
• Windows 10 May 2020 Update (2004)
  Note:

  The hardware-accelerated GPU scheduling feature introduced in Windows 10 May 2020 Update (2004) is not supported on GPUs based on the Maxwell architecture and is supported only in pass-through mode on GPUs based on later architectures.

2.3.2. Linux Guest OS Support

NVIDIA vGPU software supports only the Linux distributions listed as a guest OS on Microsoft Azure Local. The releases of Microsoft Azure Local for which a Linux release is supported depend on whether NVIDIA vGPU or pass-through GPU is used.

2.3.2.1. Linux Guest OS Support in Release 19.0

• Deprecated: CentOS Linux 8 (2105)
• Red Hat Enterprise Linux 9.6
• Red Hat Enterprise Linux 9.4
• Red Hat Enterprise Linux 8.10
• Ubuntu 24.04 LTS
• Ubuntu 22.04 LTS
• Ubuntu 20.04 LTS

2.4. NVIDIA CUDA Toolkit Version Support

The releases in this release family of NVIDIA vGPU software support NVIDIA CUDA Toolkit 13.0.

To build a CUDA application, the system must have the NVIDIA CUDA Toolkit and the libraries required for linking. For details of the components of NVIDIA CUDA Toolkit, refer to NVIDIA CUDA Toolkit 12.8 Release Notes.

To run a CUDA application, the system must have a CUDA-enabled GPU and an NVIDIA display driver that is compatible with the NVIDIA CUDA Toolkit release that was used to build the application. If the application relies on dynamic linking for libraries, the system must also have the correct version of these libraries.

For more information about NVIDIA CUDA Toolkit, refer to CUDA Toolkit Documentation 13.0.

2.5. vGPU Migration Support

vGPU Migration is supported on all supported GPUs, but only on a subset of supported Microsoft Azure Local releases and guest operating systems.

Limitations with vGPU Migration Support

vGPU migration is disabled for a VM for which any of the following NVIDIA CUDA Toolkit features is enabled:

• Unified memory
• Debuggers
• Profilers

Supported Hypervisor Software Releases

Since Microsoft Azure Local 12.2504

Supported Guest OS Releases

Windows and Linux.

Known Issues with vGPU Migration Support

2.6. vGPU Hibernation Support

NVIDIA vGPU software supports Advanced Configuration and Power Interface (ACPI) hibernation (Sx state S4) for VMs that are configured with GPU-P.

In Sx state S4, all contents of the main memory, including the runtime state of any vGPUs assigned to the VM, are saved to persistent storage and the VM is powered down. When the VM is woken up, all contents of the main memory are restored by the guest OS.

vGPU hibernation is supported on all supported GPUs, except for GPUs based on the NVIDIA Ada Lovelace GPU architecture, Microsoft Azure Local hypervisor software releases, Windows guest operating systems, and Ubuntu guest operating systems. vGPU hibernation is not supported on other Linux guest operating systems.

2.7. Multiple vGPU Support

To support applications and workloads that are compute or graphics intensive, multiple vGPUs can be added to a single VM. The assignment of more than one vGPU to a VM is supported only on a subset of vGPUs and hypervisor software releases.

2.7.1. vGPUs that Support Multiple vGPUs Assigned to a VM

All Q-series vGPUs are supported.

You can assign multiple vGPUs with differing amounts of frame buffer to a single VM, provided the board type and the series of all the vGPUs is the same. For example, you can assign an A40-48Q vGPU and an A40-16Q vGPU to the same VM. However, you cannot assign an A30-8Q vGPU and an A16-8Q vGPU to the same VM.

Multiple vGPU Support on the NVIDIA Ampere GPU Architecture

2.7.2. Maximum Number of vGPUs Supported per VM

NVIDIA vGPU software supports up to a maximum of 16 vGPUs per VM.

2.7.3. Hypervisor Releases that Support Multiple vGPUs Assigned to a VM

All hypervisor releases that support NVIDIA vGPU software are supported.

2.8. Unified Memory Support

Unified memory is a single memory address space that is accessible from any CPU or GPU in a system. It creates a pool of managed memory that is shared between the CPU and GPU to provide a simple way to allocate and access data that can be used by code running on any CPU or GPU in the system. Unified memory is supported only on a subset of vGPUs and guest OS releases.

2.8.1. vGPUs that Support Unified Memory

On single-instance GPUs, only Q-series vGPUs that are allocated all of the physical GPU's frame buffer on physical GPUs that support unified memory are supported.

Unified Memory Support on the NVIDIA Ampere GPU Architecture

2.8.2. Guest OS Releases that Support Unified Memory

Linux only. Unified memory is not supported on Windows.

2.9. NVIDIA Deep Learning Super Sampling (DLSS) Support

NVIDIA vGPU software supports NVIDIA DLSS on NVIDIA RTX Virtual Workstation.

Supported DLSS versions: 2.0. Version 1.0 is not supported.

Supported GPUs:

• NVIDIA L40
• NVIDIA L40S
• NVIDIA L20
• NVIDIA L20 liquid cooled
• NVIDIA L4
• NVIDIA L2
• NVIDIA A40
• NVIDIA A16
• NVIDIA A2
• NVIDIA A10

Supported applications: only applications that use nvngx_dlss.dll version 2.0.18 or newer

2.10. Virtualization-Based Security (VBS) Support

VBS uses hardware virtualization and the Windows hypervisor to create an isolated virtual environment that becomes the root of trust of the OS that assumes the kernel can be compromised. VBS is supported with NVIDIA vGPU on all supported GPUs, but on only a subset of supported Microsoft Azure Local releases and guest operating systems.

For more information about VBS, refer to Virtualization-based Security (VBS) on the Microsoft learning website.

Supported GPUs

All GPUs supported by NVIDIA vGPU software

Supported Hypervisor Software Releases

All supported releases of Microsoft Azure Local

Supported Guest OS Releases

Windows 11 only

Requirements for VBS Support

VBS support requires virtual Input-Output Memory Management Unit (vIOMMU) support in the NVIDIA vGPU software guest drivers.

Known product limitations for this release of NVIDIA vGPU software are described in the following sections.

3.1. vGPUs of different types on the same GPU are not supported

Microsoft Azure Local does not support a mixture of different types of time-sliced vGPUs on the same GPU. All vGPUs on a single GPU must be of the same type: They must belong to the same vGPU series and be allocated the same amount of frame buffer.

3.2. NVENC does not support resolutions greater than 4096×4096

Description

The NVIDIA hardware-based H.264 video encoder (NVENC) does not support resolutions greater than 4096×4096. This restriction applies to all NVIDIA GPU architectures and is imposed by the GPU encoder hardware itself, not by NVIDIA vGPU software. The maximum supported resolution for each encoding scheme is listed in the documentation for NVIDIA Video Codec SDK. This limitation affects any remoting tool where H.264 encoding is used with a resolution greater than 4096×4096. Most supported remoting tools fall back to software encoding in such scenarios.

Workaround

If your GPU is based on a GPU architecture later than the NVIDIA Maxwell^® architecture, use H.265 encoding. H.265 is more efficient than H.264 encoding and has a maximum resolution of 8192×8192. On GPUs based on the NVIDIA Maxwell architecture, H.265 has the same maximum resolution as H.264, namely 4096×4096.

3.3. vCS is not supported on Microsoft Azure Local

NVIDIA Virtual Compute Server (vCS) is not supported on Microsoft Azure Local. C-series vGPU types are not available.

However, you can run compute workloads on physical GPUs in DDA deployments with Microsoft Azure Local.

3.4. Nested Virtualization Is Not Supported by NVIDIA vGPU

In general, NVIDIA vGPU deployments do not support nested virtualization, that is, running a hypervisor in a guest VM. For example, enabling the Hyper-V role in a guest VM running the Windows Server OS is not supported because it entails enabling nested virtualization. Similarly, enabling Windows Hypervisor Platform is not supported because it requires the Hyper-V role to be enabled.

However, Windows Subsystem for Linux v2, which relies on nested virtualization, is supported in Windows guest VMs. No other use case that relies on nested virtualization, is supported.

3.5. Issues occur when the channels allocated to a vGPU are exhausted

Description

Issues occur when the channels allocated to a vGPU are exhausted and the guest VM to which the vGPU is assigned fails to allocate a channel to the vGPU. A physical GPU has a fixed number of channels and the number of channels allocated to each vGPU is inversely proportional to the maximum number of vGPUs allowed on the physical GPU.

When the channels allocated to a vGPU are exhausted and the guest VM fails to allocate a channel, the following errors are reported on the hypervisor host or in an NVIDIA bug report:

            

            
Jun 26 08:01:25 srvxen06f vgpu-3[14276]: error: vmiop_log: (0x0): Guest attempted to allocate channel above its max channel limit 0xfb
Jun 26 08:01:25 srvxen06f vgpu-3[14276]: error: vmiop_log: (0x0): VGPU message 6 failed, result code: 0x1a
Jun 26 08:01:25 srvxen06f vgpu-3[14276]: error: vmiop_log: (0x0):         0xc1d004a1, 0xff0e0000, 0xff0400fb, 0xc36f,
Jun 26 08:01:25 srvxen06f vgpu-3[14276]: error: vmiop_log: (0x0):         0x1, 0xff1fe314, 0xff1fe038, 0x100b6f000, 0x1000,
Jun 26 08:01:25 srvxen06f vgpu-3[14276]: error: vmiop_log: (0x0):         0x80000000, 0xff0e0200, 0x0, 0x0, (Not logged),
Jun 26 08:01:25 srvxen06f vgpu-3[14276]: error: vmiop_log: (0x0):         0x1, 0x0
Jun 26 08:01:25 srvxen06f vgpu-3[14276]: error: vmiop_log: (0x0): , 0x0
        

Workaround

Use a vGPU type with more frame buffer, thereby reducing the maximum number of vGPUs allowed on the physical GPU. As a result, the number of channels allocated to each vGPU is increased.

3.6. Total frame buffer for vGPUs is less than the total frame buffer on the physical GPU

Some of the physical GPU's frame buffer is used by the hypervisor on behalf of the VM for allocations that the guest OS would otherwise have made in its own frame buffer. The frame buffer used by the hypervisor is not available for vGPUs on the physical GPU. In NVIDIA vGPU deployments, frame buffer for the guest OS is reserved in advance, whereas in bare-metal deployments, frame buffer for the guest OS is reserved on the basis of the runtime needs of applications.

If error-correcting code (ECC) memory is enabled on a physical GPU that does not have HBM2 memory, the amount of frame buffer that is usable by vGPUs is further reduced. All types of vGPU are affected, not just vGPUs that support ECC memory.

On all GPUs that support ECC memory and, therefore, dynamic page retirement, additional frame buffer is allocated for dynamic page retirement. The amount that is allocated is inversely proportional to the maximum number of vGPUs per physical GPU. All GPUs that support ECC memory are affected, even GPUs that have HBM2 memory or for which ECC memory is disabled.

The approximate amount of frame buffer that NVIDIA vGPU software reserves can be calculated from the following formula:

max-reserved-fb = vgpu-profile-size-in-mb÷16 + 16 + ecc-adjustments + page-retirement-allocation + compression-adjustment

max-reserved-fb

The maximum total amount of reserved frame buffer in Mbytes that is not available for vGPUs.

vgpu-profile-size-in-mb

The amount of frame buffer in Mbytes allocated to a single vGPU. This amount depends on the vGPU type. For example, for the T4-16Q vGPU type, vgpu-profile-size-in-mb is 16384.

ecc-adjustments

The amount of frame buffer in Mbytes that is not usable by vGPUs when ECC is enabled on a physical GPU that does not have HBM2 memory.

• If ECC is enabled on a physical GPU that does not have HBM2 memory ecc-adjustments is fb-without-ecc/16, which is equivalent to 64 Mbytes for every Gbyte of frame buffer assigned to the vGPU. fb-without-ecc is total amount of frame buffer with ECC disabled.
• If ECC is disabled or the GPU has HBM2 memory, ecc-adjustments is 0.

page-retirement-allocation

The amount of frame buffer in Mbytes that is reserved for dynamic page retirement.

• On GPUs based on the NVIDIA Maxwell GPU architecture, page-retirement-allocation = 4÷max-vgpus-per-gpu.
• On GPUs based on NVIDIA GPU architectures after the Maxwell architecture, page-retirement-allocation = 128÷max-vgpus-per-gpu

max-vgpus-per-gpu

The maximum number of vGPUs that can be created simultaneously on a physical GPU. This number varies according to the vGPU type. For example, for the T4-16Q vGPU type, max-vgpus-per-gpu is 1.

compression-adjustment

The amount of frame buffer in Mbytes that is reserved for the higher compression overhead in vGPU types with 12 Gbytes or more of frame buffer on GPUs based on the Turing architecture.

For all vGPU types supported by Microsoft Azure Local, compression-adjustment is 0.

3.7. Issues may occur with graphics-intensive OpenCL applications on vGPU types with limited frame buffer

Description

Issues may occur when graphics-intensive OpenCL applications are used with vGPU types that have limited frame buffer. These issues occur when the applications demand more frame buffer than is allocated to the vGPU.

For example, these issues may occur with the Adobe Photoshop and LuxMark OpenCL Benchmark applications:

• When the image resolution and size are changed in Adobe Photoshop, a program error may occur or Photoshop may display a message about a problem with the graphics hardware and a suggestion to disable OpenCL.
• When the LuxMark OpenCL Benchmark application is run, XID error 31 may occur.

Workaround

For graphics-intensive OpenCL applications, use a vGPU type with more frame buffer.

3.8. In pass through mode, all GPUs connected to each other through NVLink must be assigned to the same VM

Description

In pass through mode, all GPUs connected to each other through NVLink must be assigned to the same VM. If a subset of GPUs connected to each other through NVLink is passed through to a VM, unrecoverable error XID 74 occurs when the VM is booted. This error corrupts the NVLink state on the physical GPUs and, as a result, the NVLink bridge between the GPUs is unusable.

Workaround

Restore the NVLink state on the physical GPUs by resetting the GPUs or rebooting the hypervisor host.

3.9. VM running an incompatible NVIDIA vGPU guest driver fails to initialize vGPU when booted

Description

A VM running a version of the NVIDIA guest VM driver that is incompatible with the current release of Virtual GPU Manager will fail to initialize vGPU when booted on a Microsoft Azure Local platform running that release of Virtual GPU Manager.

A guest VM driver is incompatible with the current release of Virtual GPU Manager in either of the following situations:

• The guest driver is from a release in a branch two or more major releases before the current release, for example release 9.4.

  In this situation, the Microsoft Azure Local VM’s log file reports the following error:

  Copy

  Copied!

              
  
              
  vmiop_log: (0x0): Incompatible Guest/Host drivers: Guest VGX version is older than the minimum version supported by the Host. Disabling vGPU.
          

• The guest driver is from a later release than the Virtual GPU Manager.

  In this situation, the Microsoft Azure Local VM’s log file reports the following error:

  Copy

  Copied!

              
  
              
  vmiop_log: (0x0): Incompatible Guest/Host drivers: Guest VGX version is newer than the maximum version supported by the Host. Disabling vGPU.
          

In either situation, the VM boots in standard VGA mode with reduced resolution and color depth. The NVIDIA virtual GPU is present in Windows Device Manager but displays a warning sign, and the following device status:

            

            
Windows has stopped this device because it has reported problems. (Code 43)
        

Resolution

Install a release of the NVIDIA guest VM driver that is compatible with current release of Virtual GPU Manager.

3.10. Single vGPU benchmark scores are lower than pass-through GPU

Description

A single vGPU configured on a physical GPU produces lower benchmark scores than the physical GPU run in pass-through mode.

Aside from performance differences that may be attributed to a vGPU’s smaller frame buffer size, vGPU incorporates a performance balancing feature known as Frame Rate Limiter (FRL). On vGPUs that use the best-effort scheduler, FRL is enabled. On vGPUs that use the fixed share or equal share scheduler, FRL is disabled.

FRL is used to ensure balanced performance across multiple vGPUs that are resident on the same physical GPU. The FRL setting is designed to give good interactive remote graphics experience but may reduce scores in benchmarks that depend on measuring frame rendering rates, as compared to the same benchmarks running on a pass-through GPU.

3.11. nvidia-smi fails to operate when all GPUs are assigned to GPU pass-through mode

Description

If all GPUs in the platform are assigned to VMs in pass-through mode, nvidia-smi will return an error:

            

            
[root@vgx-test ~]# nvidia-smi
Failed to initialize NVML: Unknown Error
        

This is because GPUs operating in pass-through mode are not visible to nvidia-smi and the NVIDIA kernel driver operating in the Microsoft Azure Local .

Resolution

N/A

Only resolved issues that have been previously noted as known issues or had a noticeable user impact are listed. The summary and description for each resolved issue indicate the effect of the issue on NVIDIA vGPU software before the issue was resolved.

4.1. Issues Resolved in Release 19.0

No resolved issues are reported in this release for Microsoft Azure Local.

1. Linux graphics driver installation from a .run file fails
2. GPU device is unavailable on Windows 11 VMs with more than 1 TB of memory
3. Default client configuration token folder missing on Windows client VMs
4. NVIDIA Control Panel is not available in multiuser environments
5. CUDA profilers cannot gather hardware metrics on NVIDIA vGPU
6. NVIDIA vGPU software graphics driver for Windows sends a remote call to ngx.download.nvidia.com
7. Multiple RDP session reconnections on Windows Server 2022 can consume all frame buffer
8. NLS client fails to acquire a license with the error The allowed time to process response has expired
9. With multiple active sessions, NVIDIA Control Panel incorrectly shows that the system is unlicensed
10. VP9 and AV1 decoding with web browsers are not supported on Microsoft Windows Server 2019
11. After an upgrade of the Linux graphics driver from a Debian package, the driver is not loaded into the VM
12. The reported NVENC frame rate is double the actual frame rate
13. NVENC does not work with Teradici Cloud Access Software on Windows
14. A licensed client might fail to acquire a license if a proxy is set
15. Session connection fails with four 4K displays and NVENC enabled on a 2Q, 3Q, or 4Q vGPU
16. Disconnected sessions cannot be reconnected or might be reconnected very slowly with NVWMI installed
17. Idle Teradici Cloud Access Software session disconnects from Linux VM
18. Idle NVIDIA A100, NVIDIA A40, and NVIDIA A10 GPUs show 100% GPU utilization
19. Guest VM frame buffer listed by nvidia-smi for vGPUs on GPUs that support SRIOV is incorrect
20. Driver upgrade in a Linux guest VM with multiple vGPUs might fail
21. NVIDIA Control Panel fails to start if launched too soon from a VM without licensing information
22. On Linux, the frame rate might drop to 1 after several minutes
23. Microsoft DDA fails with some GPUs
24. DWM crashes randomly occur in Windows VMs
25. Citrix Virtual Apps and Desktops session freezes when the desktop is unlocked
26. NVIDIA vGPU software graphics driver fails after Linux kernel upgrade with DKMS enabled
27. Blue screen crash occurs or no devices are found after VM reset
28. Migration of VMs configured with vGPU stops before the migration is complete
29. ECC memory settings for a vGPU cannot be changed by using NVIDIA X Server Settings
30. Changes to ECC memory settings for a Linux vGPU VM by nvidia-smi might be ignored
31. Host core CPU utilization is higher than expected for moderate workloads
32. Frame capture while the interactive logon message is displayed returns blank screen
33. RDS sessions do not use the GPU with Microsoft Windows Server as guest OS
34. When the scheduling policy is fixed share, GPU utilization is reported as higher than expected
35. nvidia-smi reports that vGPU migration is supported on all hypervisors
36. A segmentation fault in DBus code causes nvidia-gridd to exit on Red Hat Enterprise Linux and CentOS
37. No Manage License option available in NVIDIA X Server Settings by default
38. Licenses remain checked out when VMs are forcibly powered off
39. VM bug checks after the guest VM driver for Windows 10 RS2 is installed
40. GNOME Display Manager (GDM) fails to start on Red Hat Enterprise Linux 7.2 and CentOS 7.0

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DisplayPort and DisplayPort Compliance Logo, DisplayPort Compliance Logo for Dual-mode Sources, and DisplayPort Compliance Logo for Active Cables are trademarks owned by the Video Electronics Standards Association in the United States and other countries.

HDMI

HDMI, the HDMI logo, and High-Definition Multimedia Interface are trademarks or registered trademarks of HDMI Licensing LLC.

OpenCL

OpenCL is a trademark of Apple Inc. used under license to the Khronos Group Inc.

Trademarks

NVIDIA, the NVIDIA logo, NVIDIA GRID, NVIDIA GRID vGPU, NVIDIA Maxwell, NVIDIA Pascal, NVIDIA Turing, NVIDIA Volta, GPUDirect, Quadro, and Tesla are trademarks or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated.