1. Release Notes

These Release Notes summarize current status, information on validated platforms, and known issues with NVIDIA GRID™ software and hardware on Huawei UVP.

This release includes the following software:

  • NVIDIA GRID Virtual GPU Manager version 384.73 for the Huawei UVP releases listed in Hypervisor Software Versions
  • NVIDIA Windows driver version 385.41
  • NVIDIA Linux driver version 384.73
CAUTION:

If you install the wrong package for the version of Huawei UVP you are using, GRID vGPU Manager will fail to load.

The GRID vGPU Manager and Windows guest VM drivers must be installed together. Older VM drivers will not function correctly with this release of GRID vGPU Manager. Similarly, older GRID vGPU Managers will not function correctly with this release of Windows guest drivers. See VM running older NVIDIA vGPU drivers fails to initialize vGPU when booted.

Updates in this release:

  • New GRID vGPU schedulers for GPUs based on the NVIDIA Pascal architecture
  • Support for NVML and nvidia-smi on 32-Bit Windows VMs
  • Application-level monitoring of GRID vGPU engine utilization
  • Encoder session monitoring
  • Support for NVENC on Linux GRID vGPUs
  • Removal of support for GRID K1 and GRID K2 GPUs
  • Software enforcement of licensing requirements
  • Miscellaneous bug fixes

2. Validated Platforms

This release of NVIDIA GRID software provides support for several NVIDIA GPUs on validated server hardware platforms, Huawei UVP hypervisor software versions, and guest operating systems.

Supported NVIDIA GPUs and Validated Server Platforms

This release of NVIDIA GRID software provides support for the following NVIDIA GPUs on Huawei UVP, running on validated server hardware platforms:

  • Tesla M60

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

Note:

Tesla M60 and M6 GPUs support compute mode and graphics mode. GRID vGPU requires GPUs that support both modes to operate in graphics mode.

Recent Tesla M60 GPUs and M6 GPUs are supplied in graphics mode. However, your GPU might be in compute mode if it is an older Tesla M60 GPU or M6 GPU, or if its mode has previously been changed.

To configure the mode of Tesla M60 and M6 GPUs, use the gpumodeswitch tool provided with GRID software releases.

Hypervisor Software Versions

This release has been tested with the following hypervisor software versions:

Software Version Tested

Huawei UVP

Version RC520

Guest OS Support

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

Note:

Use only a guest OS release that is listed as supported by NVIDIA GRID software with your virtualization software. To be listed as supported, a guest OS release must be supported not only by NVIDIA GRID software, but also by your virtualization software. NVIDIA cannot support guest OS releases that your virtualization software does not support.

Windows Guest OS Support

NVIDIA GRID software supports the following Windows releases as a guest OS on Huawei UVP:

Guest OS GRID vGPU Pass-Through GPU
Windows Server 2016 RC520 RC520
Windows Server 2012 R2 RC520 RC520
Windows Server 2008 R2 RC520 RC520
Windows 10 RS2 (64-bit) RC520 RC520
Windows 10 RS2 (32-bit) RC520 RC520
Windows 8.1 Update (64-bit) RC520 RC520
Windows 8.1 Update (32-bit) RC520 RC520
Windows 8.1 (64-bit) RC520 -
Windows 8.1 (32-bit) RC520 -
Windows 8 (32/64-bit) RC520 -
Windows 7 (32/64-bit) RC520 RC520

Linux Guest OS Support

NVIDIA GRID software supports the following Linux distributions as a guest OS on Huawei UVP:

Guest OS GRID vGPU Pass-Through GPU
Red Hat Enterprise Linux 6.6 RC520 RC520
CentOS 6.6 RC520 RC520
Ubuntu 14.04 LTS RC520 RC520

3. Known Product Limitations

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

VM running older NVIDIA vGPU drivers fails to initialize vGPU when booted

Description

A VM running older NVIDIA drivers, such as those from a previous vGPU release, will fail to initialize vGPU when booted on a Huawei UVP platform running the current release of GRID Virtual GPU Manager.

In this scenario, the VM boots in standard VGA mode with reduced resolution and color depth. The NVIDIA GRID 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)

Depending on the versions of drivers in use, the Huawei UVP VM’s /var/log/messages log file reports one of the following errors:

  • An error message:
    vmiop_log: error: Unable to fetch Guest NVIDIA driver information
  • A version mismatch between guest and host drivers:
    vmiop_log: error: Guest VGX version(1.1) and Host VGX version(1.2) do not match
  • A signature mismatch:
    vmiop_log: error: VGPU message signature mismatch.

Resolution

Install the latest NVIDIA vGPU release drivers in the VM.

Virtual GPU fails to start if ECC is enabled

Description

Tesla M60 GPUs support error correcting code (ECC) memory for improved data integrity. Tesla M60 GPUs in graphics mode are supplied with ECC memory disabled by default, but it may subsequently be enabled using nvidia-smi.

However, NVIDIA GRID vGPU does not support ECC memory. If ECC memory is enabled, NVIDIA GRID vGPU fails to start. The following error is logged in the Huawei UVP VM’s /var/log/messages log file:

vmiop_log: error: Initialization: VGX not supported with ECC Enabled.

Resolution

Ensure that ECC is disabled on all GPUs.

  1. Use nvidia-smi to list the status of all GPUs, and check for ECC noted as enabled on GPUs.
  2. Change the ECC status to off on each GPU for which ECC is enabled by executing the following command:
    nvidia-smi -i id -e 0

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

  3. Reboot the host.

Single vGPU benchmark scores are lower than passthrough GPU

Description

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

Aside from performance differences that may be attributed to a vGPU’s smaller framebuffer size, vGPU incorporates a performance balancing feature known as Frame Rate Limiter (FRL), which is enabled on all vGPUs. 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 passthrough GPU.

Resolution

FRL is controlled by an internal vGPU setting. NVIDIA does not validate vGPU with FRL disabled, but for validation of benchmark performance, FRL can be temporarily disabled by setting plugin0.frame_rate_limiter=0 in the vGPU configuration file. vGPU configuration files are stored in /usr/share/nvidia/vgx and are named for the vGPU types they define, for example, grid_k100.conf.

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

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 by setting plugin0.frame_rate_limiter=1 in the vGPU configuration file.

nvidia-smi fails to operate when all GPUs are assigned to GPU passthrough mode

Description

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

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

This is because GPUs operating in passthrough mode are not visible to nvidia-smi and the NVIDIA kernel driver operating in the Huawei UVP dom0.

Resolution

N/A

VMs configured with large memory fail to initialize vGPU when booted

Description

When starting multiple VMs configured with large amounts of RAM (typically more than 32GB per VM), a VM may fail to initialize vGPU. In this scenario, the VM boots in standard VGA mode with reduced resolution and color depth. The NVIDIA GRID 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)

The Huawei UVP VM’s /var/log/messages log file contains these error messages:

vmiop_log: error: NVOS status 0x29
vmiop_log: error: Assertion Failed at 0x7620fd4b:179
vmiop_log: error: 8 frames returned by backtrace
...
vmiop_log: error: VGPU message 12 failed, result code: 0x29
...
vmiop_log: error: NVOS status 0x8
vmiop_log: error: Assertion Failed at 0x7620c8df:280
vmiop_log: error: 8 frames returned by backtrace
...
vmiop_log: error: VGPU message 26 failed, result code: 0x8

Resolution

vGPU reserves a portion of the VM’s framebuffer for use in GPU mapping of VM system memory. The reservation is sufficient to support up to 32GB of system memory, and may be increased to accommodate up to 64GB by specifying plugin0.enable_large_sys_mem=1 in the vGPU configuration file.

vGPU configuration files are stored in /usr/share/nvidia/vgx and are named for the vGPU types they define, for example, grid_k100.conf.

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

With this setting in place, less GPU FB is available to applications running in the VM. To accommodate system memory larger than 64GB, the reservation can be further increased by specifying plugin0.extra_fb_reservation in the vGPU configuration file, setting its value to the desired reservation size in megabytes. The default value of 64M is sufficient to support 64GB of RAM. We recommend adding 2M of reservation for each additional 1GB of system memory. For example, to support 96GB of RAM, set extra_fb_reservation to 128:

plugin0.extra_fb_reservation=128 

The reservation can be reverted back to its default setting in one of the following ways:

  • Removing enable_large_sys_mem from the vGPU configuration file
  • Setting enable_large_sys_mem=0

vGPU host driver RPM upgrade fails

Description

Upgrading vGPU host driver RPM fails with the following message on the console:

[root@uvp ~]# rpm –U NVIDIA-vGPU-kepler-uvp-210.0-352.70.x86_64
error: Failed dependencies: NVIDIA-vgx-uvp conflicts with NVIDIA-vGPU-kepler-uvp-210.0-352.70.x86_64
[root@uvp ~]#

Resolution

Uninstall the older vGPU RPM before installing the latest driver.

Use the following command to uninstall the older vGPU RPM:

[root@uvp ~]# rpm –e NVIDIA-vgx-uvp

Resolved Issues

No resolved issues are reported in this release for Huawei UVP.

5. Known Issues

Multiple display heads are not detected by Ubuntu 14.04 guest VMs

Description

After an Ubuntu 14.04 guest VM has acquired a license, multiple display heads connected to the VM are not detected.

Version

Ubuntu 14.04

Workaround

To see all the connected display heads after the VM has acquired a license, open the Displays settings window and click Detect displays.

Status

Open

Ref. #

200334648

Resolution is not updated after a VM acquires a license and is restarted

Description

In a Red Enterprise Linux 7.3 guest VM, an increase in resolution from 1024×768 to 2560×1600 is not applied after a license is acquired and the gridd service is restarted. This issue occurs if the multimonitor parameter is added to the xorg.conf file.

Version

Red Enterprise Linux 7.3

Status

Open

Ref. #

200275925

GRID vGPU encoder and process utilization counters don't work with Windows Performance Counters

Description

GPU encoder and process utilization counter groups are listed in Windows Performance Counters, but no instances of the counters are available. The counters are disabled by default and must be enabled.

Workaround

Enable the counters by running the following sequence of commands from a command shell:

wmic /namespace:nv path System call enableProcessUtilizationPerfCounter
wmic /namespace:nv path System call enableEncoderSessionsPerfCounter

If you need to disable the counters, run the following sequence of commands from a command shell:

wmic /namespace:nv path System call disableProcessUtilizationPerfCounter
wmic /namespace:nv path System call disableEncoderSessionsPerfCounter

Status

Open

Ref. #

1971698

nvidia-gridd causes a segmentation fault in DBus code on Red Hat Enterprise Linux and CentOS

Description

The nvidia-gridd services causes a segmentation fault in DBus code on Red Hat Enterprise Linux 6.8 and 6.9 CentOS 6.8 and 6.9.

Version

Red Hat Enterprise Linux 6.8 and 6.9

CentOS 6.8 and 6.9

Workaround

  1. As root, restart the DBus service.

    # sudo service messagebus restart
  2. As root, start the NVIDIA GRID service.

    # sudo service nvidia-gridd start

Status

Open

Ref. #

1895945

Multiple WebGL tabs in Microsoft Internet Explorer may trigger TDR on Windows VMs

Description

Running intensive WebGL applications in multiple IE tabs may trigger a TDR on Windows VMs.

Workaround

Disable hardware acceleration in IE.

To enable software rendering in IE, refer to the Microsoft knowledge base article How to enable or disable software rendering in Internet Explorer.

Status

Open

Ref. #

200148377

Notices

Notice

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