Red Hat Enterprise Linux with KVM

Virtual GPU Software R580 for Red Hat Enterprise Linux with KVM Release Notes

Release information for all users of NVIDIA virtual GPU software and hardware on Red Hat Enterprise Linux with KVM.

These Release Notes summarize current status, information on validated platforms, and known issues with NVIDIA vGPU software and associated hardware on Red Hat Enterprise Linux with KVM.

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 Red Hat Enterprise Linux with KVM 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

• Support for Multi-Instance GPU (MIG)-backed vGPUs for graphics on GPUs that support MIG
• Support for time-sliced, MIG-backed vGPUs within a GPU instance on a MIG-enabled GPU
• 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
• Miscellaneous bug fixes

Newly Supported Hardware and Software in Release 19.0

• Newly supported graphics cards:
  • NVIDIA RTX PRO 6000 Blackwell Server Edition

Features Deprecated in Release 19.0

NVIDIA vGPU software 19 is the last release branch to support the following graphics cards:

• Tesla M10
• Tesla V100 SXM2
• Tesla V100 SXM2 32GB
• Tesla V100 PCIe
• Tesla V100 PCIe 32GB
• Tesla V100S PCIe 32GB
• Tesla V100 FHHL
• Quadro RTX 6000
• Quadro RTX 6000 passive
• Quadro RTX 8000
• Quadro RTX 8000 passive

Disabling strict round robin policy is deprecated and NVIDIA vGPU software 19 is the last release branch to support it. Support for this feature is planned to be removed in the next major release of NVIDIA vGPU software.

This release family of NVIDIA vGPU software provides support for several NVIDIA GPUs on validated server hardware platforms, Red Hat Enterprise Linux with KVM 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 Red Hat Enterprise Linux with KVM 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 Blackwell Architecture

GPUs Based on the NVIDIA Ada Lovelace Architecture

GPUs Based on the NVIDIA Ampere Architecture

GPUs Based on the NVIDIA Turing Architecture

GPUs Based on the NVIDIA Volta Architecture

GPUs Based on the NVIDIA Maxwell Graphic Architecture

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

Red Hat Enterprise Linux with KVM 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 Virtual GPU Software User Guide.

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

This release supports only the hypervisor software releases listed in the table.

2.3. Guest OS Support

NVIDIA vGPU software supports several Windows releases and Linux distributions as a guest OS. The supported guest operating systems depend on the hypervisor software version.

2.3.1. Windows Guest OS Support

NVIDIA vGPU software supports only the 64-bit Windows releases listed as a guest OS on Red Hat Enterprise Linux with KVM. The releases of Red Hat Enterprise Linux with KVM 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 2022
• Windows 11 24H2 and all Windows 11 releases supported by Microsoft up to and including this release
• Windows 10 2022 Update (22H2) and all Windows 10 releases supported by Microsoft up to and including this release
  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 64-bit Linux distributions listed as a guest OS on Red Hat Enterprise Linux with KVM. The releases of Red Hat Enterprise Linux with KVM 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 CoreOS 4.11
• Red Hat Enterprise Linux 10.0

  Supported only in console and command-line interface (CLI) mode because NVIDIA vGPU software does not support the Wayland display server protocol

  Not supported on Red Hat Enterprise Linux with KVM hypervisor 8 and 9 releases

• Red Hat Enterprise Linux 9.6

  Not supported on Red Hat Enterprise Linux with KVM hypervisor 8 releases

• Red Hat Enterprise Linux 9.4

  Not supported on Red Hat Enterprise Linux with KVM hypervisor 8 releases

• Red Hat Enterprise Linux 8.10

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 Red Hat Enterprise Linux with KVM releases and guest operating systems.

Limitations with vGPU Migration Support

For a host that is running Red Hat Enterprise Linux with KVM 9.4, the following migrations are not supported:

• Migration between hosts that are running different versions of the NVIDIA Virtual GPU Manager driver, even within the same NVIDIA Virtual GPU Manager driver branch
• Migration to or from a host that is running a version of Red Hat Enterprise Linux with KVM that uses of a vendor-specific VFIO framework

Unless explicitly stated otherwise, these restrictions do not apply to a host that is running Red Hat Enterprise Linux with KVM since 9.6. For example, the following migrations are supported:

• Migration between hosts that are running different versions of the NVIDIA Virtual GPU Manager driver
• Migration between a host that is running Red Hat Enterprise Linux with KVM 9.6 and a host that is running Red Hat Enterprise Linux with KVM 10.0

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 Red Hat Enterprise Linux with KVM 9.4

Supported Guest OS Releases

Windows and Linux.

Known Issues with vGPU Migration Support

2.6. 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.

2.6.1. vGPUs that Support Multiple vGPUs Assigned to a VM

The supported vGPUs depend on the architecture of the GPU on which the vGPUs reside:

• For GPUs based on the NVIDIA Volta architecture and later GPU architectures, all Q-series vGPUs are supported. On GPUs that support the Multi-Instance GPU (MIG) feature, both time-sliced and MIG-backed vGPUs are supported.
• For GPUs based on the NVIDIA Pascal™ architecture, only Q-series vGPUs that are allocated all of the physical GPU's frame buffer are supported.
• For GPUs based on the NVIDIA NVIDIA Maxwell™ graphic architecture, only Q-series vGPUs that are allocated all of the physical GPU's frame buffer 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 Blackwell Architecture

Multiple vGPU Support on the NVIDIA Ada Lovelace Architecture

Multiple vGPU Support on the NVIDIA Ampere GPU Architecture

Multiple vGPU Support on the NVIDIA Turing GPU Architecture

Multiple vGPU Support on the NVIDIA Volta GPU Architecture

Multiple vGPU Support on the NVIDIA Maxwell GPU Architecture

2.6.2. Maximum Number of vGPUs Supported per VM

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

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

All hypervisor releases that support NVIDIA vGPU software are supported.

2.7. Peer-to-Peer CUDA Transfers over NVLink Support

Peer-to-peer CUDA transfers enable device memory between vGPUs on different GPUs that are assigned to the same VM to be accessed from within the CUDA kernels. NVLink is a high-bandwidth interconnect that enables fast communication between such vGPUs. Peer-to-Peer CUDA transfers over NVLink are supported only on a subset of vGPUs, Red Hat Enterprise Linux with KVM releases, and guest OS releases.

2.7.1. vGPUs that Support Peer-to-Peer CUDA Transfers

Only Q-series time-sliced vGPUs that are allocated all of the physical GPU's frame buffer on physical GPUs that support NVLink are supported.

Peer-to-Peer CUDA Transfer Support on the NVIDIA Ampere GPU Architecture

Peer-to-Peer CUDA Transfer Support on the NVIDIA Turing GPU Architecture

Peer-to-Peer CUDA Transfer Support on the NVIDIA Volta GPU Architecture

2.7.2. Hypervisor Releases that Support Peer-to-Peer CUDA Transfers

Peer-to-Peer CUDA transfers over NVLink are supported on all hypervisor releases that support the assignment of more than one vGPU to a VM. For details, see Multiple vGPU Support.

2.7.3. Guest OS Releases that Support Peer-to-Peer CUDA Transfers

Linux only. Peer-to-Peer CUDA transfers over NVLink are not supported on Windows.

2.7.4. Limitations on Support for Peer-to-Peer CUDA Transfers

• NVSwitch is not supported. Only direct connections are supported.
• Only time-sliced vGPUs are supported. MIG-backed vGPUs are not supported.
• PCIe is not supported.
• SLI is not 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 GPUs that support the MIG feature and on which this feature is enabled, only Q-series MIG-backed vGPUs that occupy an entire GPU instance are supported. All other MIG-backed vGPUs are not supported.

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 Blackwell GPU Architecture

Unified Memory Support on the NVIDIA Ada Lovelace GPU Architecture

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.

2.8.3. Limitations on Support for Unified Memory

• Only time-sliced Q-series and C-series vGPUs that are allocated all of the physical GPU's frame buffer on physical GPUs that support unified memory are supported. Fractional time-sliced vGPUs are not supported.

2.9. NVIDIA GPU Operator Support

NVIDIA GPU Operator simplifies the deployment of NVIDIA vGPU software with software container platforms on immutable operating systems. An immutable operating system does not allow the installation of the NVIDIA vGPU software graphics driver directly on the operating system. NVIDIA GPU Operator is supported only on specific combinations of hypervisor software release, container platform, and guest OS release.

For more information, refer to Using NVIDIA vGPU in the NVIDIA GPU Operator documentation.

2.10. 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 RTX 6000 Ada
• NVIDIA RTX 5880 Ada
• NVIDIA RTX 5000 Ada
• NVIDIA A40
• NVIDIA A16
• NVIDIA A2
• NVIDIA A10
• NVIDIA RTX A6000
• NVIDIA RTX A5500
• NVIDIA RTX A5000
• NVIDIA RTX PRO 6000 Blackwell Server Edition
• Tesla T4
• Quadro RTX 8000
• Quadro RTX 8000 passive
• Quadro RTX 6000
• Quadro RTX 6000 passive

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

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

3.1. 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.

3.2. vCS is not supported on Red Hat Enterprise Linux with KVM

NVIDIA Virtual Compute Server (vCS) is not supported on Red Hat Enterprise Linux with KVM. C-series vGPU types are not available.

3.3. 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.

3.4. 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.

3.5. Virtual GPU hot plugging is not supported

NVIDIA vGPU software does not support the addition of virtual function I/O (VFIO) mediated device (mdev) devices after the VM has been started by QEMU. All mdev devices must be added before the VM is started.

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.

compression-adjustment depends on the vGPU type as shown in the following table.

vGPU Type	Compression Adjustment (MB)
T4-16Q T4-16C T4-16A	28
RTX6000-12Q RTX6000-12C RTX6000-12A	32
RTX6000-24Q RTX6000-24C RTX6000-24A	104
RTX6000P-12Q RTX6000P-12C RTX6000P-12A	32
RTX6000P-24Q RTX6000P-24C RTX6000P-24A	104
RTX8000-12Q RTX8000-12C RTX8000-12A	32
RTX8000-16Q RTX8000-16C RTX8000-16A	64
RTX8000-24Q RTX8000-24C RTX8000-24A	96
RTX8000-48Q RTX8000-48C RTX8000-48A	238
RTX8000P-12Q RTX8000P-12C RTX8000P-12A	32
RTX8000P-16Q RTX8000P-16C RTX8000P-16A	64
RTX8000P-24Q RTX8000P-24C RTX8000P-24A	96
RTX8000P-48Q RTX8000P-48C RTX8000P-48A	238

For all other vGPU types, 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. vGPU profiles with 512 Mbytes or less of frame buffer support only 1 virtual display head on Windows 10

Description

To reduce the possibility of memory exhaustion, vGPU profiles with 512 Mbytes or less of frame buffer support only 1 virtual display head on a Windows 10 guest OS.

The following vGPU profiles have 512 Mbytes or less of frame buffer:

• Tesla M10-0B
• Tesla M10-0Q

Workaround

Use a profile that supports more than 1 virtual display head and has at least 1 Gbyte of frame buffer.

3.10. NVENC requires at least 1 Gbyte of frame buffer

Description

Using the frame buffer for the NVIDIA hardware-based H.264/HEVC video encoder (NVENC) may cause memory exhaustion with vGPU profiles that have 512 Mbytes or less of frame buffer. To reduce the possibility of memory exhaustion, NVENC is disabled on profiles that have 512 Mbytes or less of frame buffer. Application GPU acceleration remains fully supported and available for all profiles, including profiles with 512 MBytes or less of frame buffer. NVENC support from both Citrix and VMware is a recent feature and, if you are using an older version, you should experience no change in functionality.

The following vGPU profiles have 512 Mbytes or less of frame buffer:

• Tesla M10-0B
• Tesla M10-0Q

Workaround

If you require NVENC to be enabled, use a profile that has at least 1 Gbyte of frame buffer.

3.11. 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 Red Hat Enterprise Linux with KVM 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 Red Hat Enterprise Linux with KVM VM’s /var/log/messages log file reports the following error:

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  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 Red Hat Enterprise Linux with KVM VM’s /var/log/messages log file reports the following error:

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  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.

3.12. 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.

Resolution

FRL is controlled by an internal vGPU setting. On vGPUs that use the best-effort scheduler, NVIDIA does not validate vGPU with FRL disabled, but for validation of benchmark performance, FRL can be temporarily disabled by setting frame_rate_limiter=0 in the vGPU configuration file.

            

            
# echo "frame_rate_limiter=0" > /sys/bus/mdev/devices/vgpu-id/nvidia/vgpu_params
        

For example:

            

            
# echo "frame_rate_limiter=0" > /sys/bus/mdev/devices/aa618089-8b16-4d01-a136-25a0f3c73123/nvidia/vgpu_params
        

The setting takes effect the next time any VM using the given vGPU type is started.

With this setting in place, the VM’s vGPU will run without any frame rate limit.

The FRL can be reverted back to its default setting as follows:

1. Clear all parameter settings in the vGPU configuration file.

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

   Note:

   You cannot clear specific parameter settings. If your vGPU configuration file contains other parameter settings that you want to keep, you must reinstate them in the next step.

2. Set frame_rate_limiter=1 in the vGPU configuration file.

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   # echo "frame_rate_limiter=1" > /sys/bus/mdev/devices/vgpu-id/nvidia/vgpu_params
           

   If you need to reinstate other parameter settings, include them in the command to set frame_rate_limiter=1. For example:

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   # echo "frame_rate_limiter=1 disable_vnc=1" > /sys/bus/mdev/devices/aa618089-8b16-4d01-a136-25a0f3c73123/nvidia/vgpu_params
           

3.13. 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 Red Hat Enterprise Linux with KVMhost.

To confirm that all GPUs are operating in pass-through mode, confirm that the vfio-pci kernel driver is handling each device.

            

            
# lspci -s 05:00.0 -k
05:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
               Subsystem: NVIDIA Corporation Device 113a
               Kernel driver in use: vfio-pci
        

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 Red Hat Enterprise Linux with KVM.

1. vGPUs created with a vendor-specific VFIO framework do not support Console VNC
2. Linux graphics driver installation from a .run file fails
3. GPU device is unavailable on Windows 11 VMs with more than 1 TB of memory
4. Default client configuration token folder missing on Windows client VMs
5. NVIDIA Control Panel is not available in multiuser environments
6. NVIDIA Control Panel crashes if a user session is disconnected and reconnected
7. VM assigned multiple fractional vGPUs from the same GPU hangs
8. CUDA profilers cannot gather hardware metrics on NVIDIA vGPU
9. NVIDIA vGPU software graphics driver for Windows sends a remote call to ngx.download.nvidia.com
10. On NVIDIA H100, creation of multiple compute instances after deletion of existing compute instances fails
11. NLS client fails to acquire a license with the error The allowed time to process response has expired
12. NVIDIA vGPU software graphics driver fails to load on KVM-based hypervsiors
13. With multiple active sessions, NVIDIA Control Panel incorrectly shows that the system is unlicensed
14. VP9 and AV1 decoding with web browsers are not supported on Microsoft Windows Server 2019
15. nvidia-smi ignores the second NVIDIA vGPU device added to a Microsoft Windows Server 2016 VM
16. After an upgrade of the Linux graphics driver from an RPM package in a licensed VM, licensing fails
17. The reported NVENC frame rate is double the actual frame rate
18. NVENC does not work with Teradici Cloud Access Software on Windows
19. A licensed client might fail to acquire a license if a proxy is set
20. Session connection fails with four 4K displays and NVENC enabled on a 2Q, 3Q, or 4Q vGPU
21. NVIDIA A100 HGX 80GB vGPU names shown as Graphics Device by nvidia-smi
22. Idle Teradici Cloud Access Software session disconnects from Linux VM
23. GPU Operator doesn't support vGPU on GPUs based on architectures before NVIDIA Turing
24. Idle NVIDIA A100, NVIDIA A40, and NVIDIA A10 GPUs show 100% GPU utilization
25. Guest VM frame buffer listed by nvidia-smi for vGPUs on GPUs that support SRIOV is incorrect
26. VMs fail to boot on RHV 4.4
27. Driver upgrade in a Linux guest VM with multiple vGPUs might fail
28. NVIDIA Control Panel fails to start if launched too soon from a VM without licensing information
29. On Linux, the frame rate might drop to 1 after several minutes
30. DWM crashes randomly occur in Windows VMs
31. Migration of VMs configured with vGPU stops before the migration is complete
32. ECC memory settings for a vGPU cannot be changed by using NVIDIA X Server Settings
33. Changes to ECC memory settings for a Linux vGPU VM by nvidia-smi might be ignored
34. Host core CPU utilization is higher than expected for moderate workloads
35. Frame capture while the interactive logon message is displayed returns blank screen
36. RDS sessions do not use the GPU with Microsoft Windows Server as guest OS
37. When the scheduling policy is fixed share, GPU utilization is reported as higher than expected
38. License is not acquired in Windows VMs
39. nvidia-smi reports that vGPU migration is supported on all hypervisors
40. Hot plugging and unplugging vCPUs causes a blue-screen crash in Windows VMs
41. Luxmark causes a segmentation fault on an unlicensed Linux client
42. A segmentation fault in DBus code causes nvidia-gridd to exit on Red Hat Enterprise Linux and CentOS
43. No Manage License option available in NVIDIA X Server Settings by default
44. Licenses remain checked out when VMs are forcibly powered off
45. VM bug checks after the guest VM driver for Windows 10 RS2 is installed
46. GNOME Display Manager (GDM) fails to start on Red Hat Enterprise Linux 7.2 and CentOS 7.0

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