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.

1. Introduction to NVIDIA vGPU Software

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 NVIDA 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 Quadro vDWS and GRID Virtual Applications 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. How this Guide Is Organized

Virtual GPU Software User Guide is organized as follows:

1.3. 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

Diagram showing the high-level architecture of NVIDIA vGPU

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.

All vGPUs resident on a physical GPU share access to the GPU’s engines including the graphics (3D), video decode, and video encode engines.

Figure 2. NVIDIA vGPU Internal Architecture

Diagram showing the internal architecture of NVIDIA vGPU

1.4. Supported GPUs

NVIDIA vGPU is available as a licensed product on supported Tesla GPUs. For a list of recommended server platforms and supported GPUs, consult the release notes for supported hypervisors at NVIDIA Virtual GPU Software Documentation.

1.4.1. 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.

Series Optimal Workload
Q-series Virtual workstations for creative and technical professionals who require the performance and features of Quadro technology
C-series Compute-intensive server workloads, such as artificial intelligence (AI), deep learning, or high-performance computing (HPC)2
B-series Virtual desktops for business professionals and knowledge workers
A-series App streaming or session-based solutions for virtual applications users3

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 M60-2Q is allocated 2048 Mbytes of frame buffer on a Tesla M60 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, a Tesla M60 board can support up to 4 M60-2Q vGPUs on each of its two physical GPUs, for a total of 8 vGPUs, but only 2 M60-4Q vGPUs, for a total of 4 vGPUs.

Note:

NVIDIA vGPU is a licensed product on all supported GPU boards. A software license is required to enable all vGPU features within the guest VM. The type of license required depends on the vGPU type.

  • Q-series vGPU types require a Quadro vDWS license.
  • C-series vGPU types require a vComputeServer license but can also be used with a Quadro vDWS license.
  • B-series vGPU types require a GRID Virtual PC license but can also be used with a Quadro vDWS license.
  • A-series vGPU types require a GRID Virtual Applications license.

1.4.1.1. Tesla M60 Virtual GPU Types

Physical GPUs per board: 2
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
M60-8Q Virtual Workstations 8192 4 4096×2160 1 2 Quadro vDWS
M60-4Q Virtual Workstations 4096 4 4096×2160 2 4 Quadro vDWS
M60-2Q Virtual Workstations 2048 4 4096×2160 4 8 Quadro vDWS
M60-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 8 16 Quadro vDWS
M60-0Q Virtual Desktops, Virtual Workstations 512 21 2560×1600 16 32 Quadro vDWS
M60-2B Virtual Desktops 2048 2 4096×2160 4 8 GRID Virtual PC or Quadro vDWS
M60-2B4 Virtual Desktops 2048 4 2560×1600 4 8 GRID Virtual PC or Quadro vDWS
M60-1B Virtual Desktops 1024 4 2560×1600 8 16 GRID Virtual PC or Quadro vDWS
M60-1B4 Virtual Desktops 1024 1 4096×2160 8 16 GRID Virtual PC or Quadro vDWS
M60-0B Virtual Desktops 512 21 2560×1600 16 32 GRID Virtual PC or Quadro vDWS
M60-8A Virtual Applications 8192 1 1280×10243 1 2 GRID Virtual Application
M60-4A Virtual Applications 4096 1 1280×10243 2 4 GRID Virtual Application
M60-2A Virtual Applications 2048 1 1280×10243 4 8 GRID Virtual Application
M60-1A Virtual Applications 1024 1 1280×10243 8 16 GRID Virtual Application

1.4.1.2. Tesla M10 Virtual GPU Types

Physical GPUs per board: 4
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
M10-8Q Virtual Workstations 8192 4 4096×2160 1 4 Quadro vDWS
M10-4Q Virtual Workstations 4096 4 4096×2160 2 8 Quadro vDWS
M10-2Q Virtual Workstations 2048 4 4096×2160 4 16 Quadro vDWS
M10-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 8 32 Quadro vDWS
M10-0Q Virtual Desktops, Virtual Workstations 512 21 2560×1600 16 64 Quadro vDWS
M10-2B Virtual Desktops 2048 2 4096×2160 4 16 GRID Virtual PC or Quadro vDWS
M10-2B4 Virtual Desktops 2048 4 2560×1600 4 16 GRID Virtual PC or Quadro vDWS
M10-1B Virtual Desktops 1024 4 2560×1600 8 32 GRID Virtual PC or Quadro vDWS
M10-1B4 Virtual Desktops 1024 1 4096×2160 8 32 GRID Virtual PC or Quadro vDWS
M10-0B Virtual Desktops 512 21 2560×1600 16 64 GRID Virtual PC or Quadro vDWS
M10-8A Virtual Applications 8192 1 1280×10243 1 4 GRID Virtual Application
M10-4A Virtual Applications 4096 1 1280×10243 2 8 GRID Virtual Application
M10-2A Virtual Applications 2048 1 1280×10243 4 16 GRID Virtual Application
M10-1A Virtual Applications 1024 1 1280×10243 8 32 GRID Virtual Application

1.4.1.3. Tesla M6 Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
M6-8Q Virtual Workstations 8192 4 4096×2160 1 1 Quadro vDWS
M6-4Q Virtual Workstations 4096 4 4096×2160 2 2 Quadro vDWS
M6-2Q Virtual Workstations 2048 4 4096×2160 4 4 Quadro vDWS
M6-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 8 8 Quadro vDWS
M6-0Q Virtual Desktops, Virtual Workstations 512 21 2560×1600 16 16 Quadro vDWS
M6-2B Virtual Desktops 2048 2 4096×2160 4 4 GRID Virtual PC or Quadro vDWS
M6-2B4 Virtual Desktops 2048 4 2560×1600 4 4 GRID Virtual PC or Quadro vDWS
M6-1B Virtual Desktops 1024 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
M6-1B4 Virtual Desktops 1024 1 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
M6-0B Virtual Desktops 512 21 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
M6-8A Virtual Applications 8192 1 1280×10243 1 1 GRID Virtual Application
M6-4A Virtual Applications 4096 1 1280×10243 2 2 GRID Virtual Application
M6-2A Virtual Applications 2048 1 1280×10243 4 4 GRID Virtual Application
M6-1A Virtual Applications 1024 1 1280×10243 8 8 GRID Virtual Application

1.4.1.4. Tesla P100 PCIe 12GB Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
P100C-12Q Virtual Workstations 12288 4 4096×2160 1 1 Quadro vDWS
P100C-6Q Virtual Workstations 6144 4 4096×2160 2 2 Quadro vDWS
P100C-4Q Virtual Workstations 4096 4 4096×2160 3 3 Quadro vDWS
P100C-2Q Virtual Workstations 2048 4 4096×2160 6 6 Quadro vDWS
P100C-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 12 12 Quadro vDWS
P100C-12C Training Workloads 12288 1 4096×21602 1 1 vComputeServer or Quadro vDWS
P100C-6C Training Workloads 6144 1 4096×21602 2 2 vComputeServer or Quadro vDWS
P100C-4C Inference Workloads 4096 1 4096×21602 3 3 vComputeServer or Quadro vDWS
P100C-2B Virtual Desktops 2048 2 4096×2160 6 6 GRID Virtual PC or Quadro vDWS
P100C-2B4 Virtual Desktops 2048 4 2560×1600 6 6 GRID Virtual PC or Quadro vDWS
P100C-1B Virtual Desktops 1024 4 2560×1600 12 12 GRID Virtual PC or Quadro vDWS
P100C-1B4 Virtual Desktops 1024 1 4096×2160 12 12 GRID Virtual PC or Quadro vDWS
P100C-12A Virtual Applications 12288 1 1280×10243 1 1 GRID Virtual Application
P100C-6A Virtual Applications 6144 1 1280×10243 2 2 GRID Virtual Application
P100C-4A Virtual Applications 4096 1 1280×10243 3 3 GRID Virtual Application
P100C-2A Virtual Applications 2048 1 1280×10243 6 6 GRID Virtual Application
P100C-1A Virtual Applications 1024 1 1280×10243 12 12 GRID Virtual Application

1.4.1.5. Tesla P100 PCIe 16GB Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
P100-16Q Virtual Workstations 16384 4 4096×2160 1 1 Quadro vDWS
P100-8Q Virtual Workstations 8192 4 4096×2160 2 2 Quadro vDWS
P100-4Q Virtual Workstations 4096 4 4096×2160 4 4 Quadro vDWS
P100-2Q Virtual Workstations 2048 4 4096×2160 8 8 Quadro vDWS
P100-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 16 16 Quadro vDWS
P100-16C Training Workloads 16384 1 4096×21602 1 1 vComputeServer or Quadro vDWS
P100-8C Training Workloads 8192 1 4096×21602 2 2 vComputeServer or Quadro vDWS
P100-4C Inference Workloads 4096 1 4096×21602 4 4 vComputeServer or Quadro vDWS
P100-2B Virtual Desktops 2048 2 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
P100-2B4 Virtual Desktops 2048 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
P100-1B Virtual Desktops 1024 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
P100-1B4 Virtual Desktops 1024 1 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
P100-16A Virtual Applications 16384 1 1280×10243 1 1 GRID Virtual Application
P100-8A Virtual Applications 8192 1 1280×10243 2 2 GRID Virtual Application
P100-4A Virtual Applications 4096 1 1280×10243 4 4 GRID Virtual Application
P100-2A Virtual Applications 2048 1 1280×10243 8 8 GRID Virtual Application
P100-1A Virtual Applications 1024 1 1280×10243 16 16 GRID Virtual Application

1.4.1.6. Tesla P100 SXM2 Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
P100X-16Q Virtual Workstations 16384 4 4096×2160 1 1 Quadro vDWS
P100X-8Q Virtual Workstations 8192 4 4096×2160 2 2 Quadro vDWS
P100X-4Q Virtual Workstations 4096 4 4096×2160 4 4 Quadro vDWS
P100X-2Q Virtual Workstations 2048 4 4096×2160 8 8 Quadro vDWS
P100X-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 16 16 Quadro vDWS
P100X-16C Training Workloads 16384 1 4096×21602 1 1 vComputeServer or Quadro vDWS
P100X-8C Training Workloads 8192 1 4096×21602 2 2 vComputeServer or Quadro vDWS
P100X-4C Inference Workloads 4096 1 4096×21602 4 4 vComputeServer or Quadro vDWS
P100X-2B Virtual Desktops 2048 2 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
P100X-2B4 Virtual Desktops 2048 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
P100X-1B Virtual Desktops 1024 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
P100X-1B4 Virtual Desktops 1024 1 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
P100X-16A Virtual Applications 16384 1 1280×10243 1 1 GRID Virtual Application
P100X-8A Virtual Applications 8192 1 1280×10243 2 2 GRID Virtual Application
P100X-4A Virtual Applications 4096 1 1280×10243 4 4 GRID Virtual Application
P100X-2A Virtual Applications 2048 1 1280×10243 8 8 GRID Virtual Application
P100X-1A Virtual Applications 1024 1 1280×10243 16 16 GRID Virtual Application

1.4.1.7. Tesla P40 Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
P40-24Q Virtual Workstations 24576 4 4096×2160 1 1 Quadro vDWS
P40-12Q Virtual Workstations 12288 4 4096×2160 2 2 Quadro vDWS
P40-8Q Virtual Workstations 8192 4 4096×2160 3 3 Quadro vDWS
P40-6Q Virtual Workstations 6144 4 4096×2160 4 4 Quadro vDWS
P40-4Q Virtual Workstations 4096 4 4096×2160 6 6 Quadro vDWS
P40-3Q Virtual Workstations 3072 4 4096×2160 8 8 Quadro vDWS
P40-2Q Virtual Workstations 2048 4 4096×2160 12 12 Quadro vDWS
P40-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 24 24 Quadro vDWS
P40-24C Training Workloads 24576 1 4096×21602 1 1 vComputeServer or Quadro vDWS
P40-12C Training Workloads 12288 1 4096×21602 2 2 vComputeServer or Quadro vDWS
P40-8C Training Workloads 8192 1 4096×21602 3 3 vComputeServer or Quadro vDWS
P40-6C Training Workloads 6144 1 4096×21602 4 4 vComputeServer or Quadro vDWS
P40-4C Inference Workloads 4096 1 4096×21602 6 6 vComputeServer or Quadro vDWS
P40-2B Virtual Desktops 2048 2 4096×2160 12 12 GRID Virtual PC or Quadro vDWS
P40-2B4 Virtual Desktops 2048 4 2560×1600 12 12 GRID Virtual PC or Quadro vDWS
P40-1B Virtual Desktops 1024 4 2560×1600 24 24 GRID Virtual PC or Quadro vDWS
P40-1B4 Virtual Desktops 1024 1 4096×2160 24 24 GRID Virtual PC or Quadro vDWS
P40-24A Virtual Applications 24576 1 1280×10243 1 1 GRID Virtual Application
P40-12A Virtual Applications 12288 1 1280x10243 2 2 GRID Virtual Application
P40-8A Virtual Applications 8192 1 1280×10243 3 3 GRID Virtual Application
P40-6A Virtual Applications 6144 1 1280×10243 4 4 GRID Virtual Application
P40-4A Virtual Applications 4096 1 1280×10243 6 6 GRID Virtual Application
P40-3A Virtual Applications 3072 1 1280×10243 8 8 GRID Virtual Application
P40-2A Virtual Applications 2048 1 1280×10243 12 12 GRID Virtual Application
P40-1A Virtual Applications 1024 1 1280×10243 24 24 GRID Virtual Application

1.4.1.8. Tesla P6 Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
P6-16Q Virtual Workstations 16384 4 4096×2160 1 1 Quadro vDWS
P6-8Q Virtual Workstations 8192 4 4096×2160 2 2 Quadro vDWS
P6-4Q Virtual Workstations 4096 4 4096×2160 4 4 Quadro vDWS
P6-2Q Virtual Workstations 2048 4 4096×2160 8 8 Quadro vDWS
P6-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 16 16 Quadro vDWS
P6-16C Training Workloads 16384 1 4096×21602 1 1 vComputeServer or Quadro vDWS
P6-8C Training Workloads 8192 1 4096×21602 2 2 vComputeServer or Quadro vDWS
P6-4C Inference Workloads 4096 1 4096×21602 4 4 vComputeServer or Quadro vDWS
P6-2B Virtual Desktops 2048 2 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
P6-2B4 Virtual Desktops 2048 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
P6-1B Virtual Desktops 1024 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
P6-1B4 Virtual Desktops 1024 1 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
P6-16A Virtual Applications 16384 1 1280×10243 1 1 GRID Virtual Application
P6-8A Virtual Applications 8192 1 1280×10243 2 2 GRID Virtual Application
P6-4A Virtual Applications 4096 1 1280×10243 4 4 GRID Virtual Application
P6-2A Virtual Applications 2048 1 1280×10243 8 8 GRID Virtual Application
P6-1A Virtual Applications 1024 1 1280×10243 16 16 GRID Virtual Application

1.4.1.9. Tesla P4 Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
P4-8Q Virtual Workstations 8192 4 4096×2160 1 1 Quadro vDWS
P4-4Q Virtual Workstations 4096 4 4096×2160 2 2 Quadro vDWS
P4-2Q Virtual Workstations 2048 4 4096×2160 4 4 Quadro vDWS
P4-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 8 8 Quadro vDWS
P4-8C Training Workloads 8192 1 4096×21602 1 1 vComputeServer or Quadro vDWS
P4-4C Inference Workloads 4096 1 4096×21602 2 2 vComputeServer or Quadro vDWS
P4-2B Virtual Desktops 2048 2 4096×2160 4 4 GRID Virtual PC or Quadro vDWS
P4-2B4 Virtual Desktops 2048 4 2560×1600 4 4 GRID Virtual PC or Quadro vDWS
P4-1B Virtual Desktops 1024 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
P4-1B4 Virtual Desktops 1024 1 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
P4-8A Virtual Applications 8192 1 1280×10243 1 1 GRID Virtual Application
P4-4A Virtual Applications 4096 1 1280×10243 2 2 GRID Virtual Application
P4-2A Virtual Applications 2048 1 1280×10243 4 4 GRID Virtual Application
P4-1A Virtual Applications 1024 1 1280×10243 8 8 GRID Virtual Application

1.4.1.10. Tesla T4 Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
T4-16Q Virtual Workstations 16384 4 4096×2160 1 1 Quadro vDWS
T4-8Q Virtual Workstations 8192 4 4096×2160 2 2 Quadro vDWS
T4-4Q Virtual Workstations 4096 4 4096×2160 4 4 Quadro vDWS
T4-2Q Virtual Workstations 2048 4 4096×2160 8 8 Quadro vDWS
T4-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 16 16 Quadro vDWS
T4-16C Training Workloads 16384 1 4096×21602 1 1 vComputeServer or Quadro vDWS
T4-8C Training Workloads 8192 1 4096×21602 2 2 vComputeServer or Quadro vDWS
T4-4C Inference Workloads 4096 1 4096×21602 4 4 vComputeServer or Quadro vDWS
T4-2B Virtual Desktops 2048 2 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
T4-2B4 Virtual Desktops 2048 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
T4-1B Virtual Desktops 1024 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
T4-1B4 Virtual Desktops 1024 1 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
T4-16A Virtual Applications 16384 1 1280×10243 1 1 GRID Virtual Application
T4-8A Virtual Applications 8192 1 1280×10243 2 2 GRID Virtual Application
T4-4A Virtual Applications 4096 1 1280×10243 4 4 GRID Virtual Application
T4-2A Virtual Applications 2048 1 1280×10243 8 8 GRID Virtual Application
T4-1A Virtual Applications 1024 1 1280×10243 16 16 GRID Virtual Application

1.4.1.11. Tesla V100 SXM2 Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
V100X-16Q Virtual Workstations 16384 4 4096×2160 1 1 Quadro vDWS
V100X-8Q Virtual Workstations 8192 4 4096×2160 2 2 Quadro vDWS
V100X-4Q Virtual Workstations 4096 4 4096×2160 4 4 Quadro vDWS
V100X-2Q Virtual Workstations 2048 4 4096×2160 8 8 Quadro vDWS
V100X-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 16 16 Quadro vDWS
V100X-16C Training Workloads 16384 1 4096×21602 1 1 vComputeServer or Quadro vDWS
V100X-8C Training Workloads 8192 1 4096×21602 2 2 vComputeServer or Quadro vDWS
V100X-4C Inference Workloads 4096 1 4096×21602 4 4 vComputeServer or Quadro vDWS
V100X-2B Virtual Desktops 2048 2 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
V100X-2B4 Virtual Desktops 2048 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
V100X-1B Virtual Desktops 1024 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
V100X-1B4 Virtual Desktops 1024 1 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
V100X-16A Virtual Applications 16384 1 1280×10243 1 1 GRID Virtual Application
V100X-8A Virtual Applications 8192 1 1280×10243 2 2 GRID Virtual Application
V100X-4A Virtual Applications 4096 1 1280×10243 4 4 GRID Virtual Application
V100X-2A Virtual Applications 2048 1 1280×10243 8 8 GRID Virtual Application
V100X-1A Virtual Applications 1024 1 1280×10243 16 16 GRID Virtual Application

1.4.1.12. Tesla V100 SXM2 32GB Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
V100DX-32Q Virtual Workstations 32768 4 4096×2160 1 1 Quadro vDWS
V100DX-16Q Virtual Workstations 16384 4 4096×2160 2 2 Quadro vDWS
V100DX-8Q Virtual Workstations 8192 4 4096×2160 4 4 Quadro vDWS
V100DX-4Q Virtual Workstations 4096 4 4096×2160 8 8 Quadro vDWS
V100DX-2Q Virtual Workstations 2048 4 4096×2160 16 16 Quadro vDWS
V100DX-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 32 32 Quadro vDWS
V100DX-32C Training Workloads 32768 1 4096×21602 1 1 vComputeServer or Quadro vDWS
V100DX-16C Training Workloads 16384 1 4096×21602 2 2 vComputeServer or Quadro vDWS
V100DX-8C Training Workloads 8192 1 4096×21602 4 4 vComputeServer or Quadro vDWS
V100DX-4C Inference Workloads 4096 1 4096×21602 8 8 vComputeServer or Quadro vDWS
V100DX-2B Virtual Desktops 2048 2 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
V100DX-2B4 Virtual Desktops 2048 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
V100DX-1B Virtual Desktops 1024 4 2560×1600 32 32 GRID Virtual PC or Quadro vDWS
V100DX-1B4 Virtual Desktops 1024 1 4096×2160 32 32 GRID Virtual PC or Quadro vDWS
V100DX-32A Virtual Applications 32768 1 1280×10243 1 1 GRID Virtual Application
V100DX-16A Virtual Applications 16384 1 1280×10243 2 2 GRID Virtual Application
V100DX-8A Virtual Applications 8192 1 1280×10243 4 4 GRID Virtual Application
V100DX-4A Virtual Applications 4096 1 1280×10243 8 8 GRID Virtual Application
V100DX-2A Virtual Applications 2048 1 1280×10243 16 16 GRID Virtual Application
V100DX-1A Virtual Applications 1024 1 1280×10243 32 32 GRID Virtual Application

1.4.1.13. Tesla V100 PCIe Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
V100-16Q Virtual Workstations 16384 4 4096×2160 1 1 Quadro vDWS
V100-8Q Virtual Workstations 8192 4 4096×2160 2 2 Quadro vDWS
V100-4Q Virtual Workstations 4096 4 4096×2160 4 4 Quadro vDWS
V100-2Q Virtual Workstations 2048 4 4096×2160 8 8 Quadro vDWS
V100-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 16 16 Quadro vDWS
V100-16C Training Workloads 16384 1 4096×21602 1 1 vComputeServer or Quadro vDWS
V100-8C Training Workloads 8192 1 4096×21602 2 2 vComputeServer or Quadro vDWS
V100-4C Inference Workloads 4096 1 4096×21602 4 4 vComputeServer or Quadro vDWS
V100-2B Virtual Desktops 2048 2 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
V100-2B4 Virtual Desktops 2048 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
V100-1B Virtual Desktops 1024 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
V100-1B4 Virtual Desktops 1024 1 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
V100-16A Virtual Applications 16384 1 1280×10243 1 1 GRID Virtual Application
V100-8A Virtual Applications 8192 1 1280×10243 2 2 GRID Virtual Application
V100-4A Virtual Applications 4096 1 1280×10243 4 4 GRID Virtual Application
V100-2A Virtual Applications 2048 1 1280×10243 8 8 GRID Virtual Application
V100-1A Virtual Applications 1024 1 1280×10243 16 16 GRID Virtual Application

1.4.1.14. Tesla V100 PCIe 32GB Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
V100D-32Q Virtual Workstations 32768 4 4096×2160 1 1 Quadro vDWS
V100D-16Q Virtual Workstations 16384 4 4096×2160 2 2 Quadro vDWS
V100D-8Q Virtual Workstations 8192 4 4096×2160 4 4 Quadro vDWS
V100D-4Q Virtual Workstations 4096 4 4096×2160 8 8 Quadro vDWS
V100D-2Q Virtual Workstations 2048 4 4096×2160 16 16 Quadro vDWS
V100D-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 32 32 Quadro vDWS
V100D-32C Training Workloads 32768 1 4096×21602 1 1 vComputeServer or Quadro vDWS
V100D-16C Training Workloads 16384 1 4096×21602 2 2 vComputeServer or Quadro vDWS
V100D-8C Training Workloads 8192 1 4096×21602 4 4 vComputeServer or Quadro vDWS
V100D-4C Inference Workloads 4096 1 4096×21602 8 8 vComputeServer or Quadro vDWS
V100D-2B Virtual Desktops 2048 2 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
V100D-2B4 Virtual Desktops 2048 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
V100D-1B Virtual Desktops 1024 4 2560×1600 32 32 GRID Virtual PC or Quadro vDWS
V100D-1B4 Virtual Desktops 1024 1 4096×2160 32 32 GRID Virtual PC or Quadro vDWS
V100D-32A Virtual Applications 32768 1 1280×10243 1 1 GRID Virtual Application
V100D-16A Virtual Applications 16384 1 1280×10243 2 2 GRID Virtual Application
V100D-8A Virtual Applications 8192 1 1280×10243 4 4 GRID Virtual Application
V100D-4A Virtual Applications 4096 1 1280×10243 8 8 GRID Virtual Application
V100D-2A Virtual Applications 2048 1 1280×10243 16 16 GRID Virtual Application
V100D-1A Virtual Applications 1024 1 1280×10243 32 32 GRID Virtual Application

1.4.1.15. Tesla V100 FHHL Virtual GPU Types

Physical GPUs per board: 1
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
V100L-16Q Virtual Workstations 16384 4 4096×2160 1 1 Quadro vDWS
V100L-8Q Virtual Workstations 8192 4 4096×2160 2 2 Quadro vDWS
V100L-4Q Virtual Workstations 4096 4 4096×2160 4 4 Quadro vDWS
V100L-2Q Virtual Workstations 2048 4 4096×2160 8 8 Quadro vDWS
V100L-1Q Virtual Desktops, Virtual Workstations 1024 2 4096×2160 16 16 Quadro vDWS
V100L-16C Training Workloads 16384 1 4096×21602 1 1 vComputeServer or Quadro vDWS
V100L-8C Training Workloads 8192 1 4096×21602 2 2 vComputeServer or Quadro vDWS
V100L-4C Inference Workloads 4096 1 4096×21602 4 4 vComputeServer or Quadro vDWS
V100L-2B Virtual Desktops 2048 2 4096×2160 8 8 GRID Virtual PC or Quadro vDWS
V100L-2B4 Virtual Desktops 2048 4 2560×1600 8 8 GRID Virtual PC or Quadro vDWS
V100L-1B Virtual Desktops 1024 4 2560×1600 16 16 GRID Virtual PC or Quadro vDWS
V100L-1B4 Virtual Desktops 1024 1 4096×2160 16 16 GRID Virtual PC or Quadro vDWS
V100L-16A Virtual Applications 16384 1 1280×10243 1 1 GRID Virtual Application
V100L-8A Virtual Applications 8192 1 1280×10243 2 2 GRID Virtual Application
V100L-4A Virtual Applications 4096 1 1280×10243 4 4 GRID Virtual Application
V100L-2A Virtual Applications 2048 1 1280×10243 8 8 GRID Virtual Application
V100L-1A Virtual Applications 1024 1 1280×10243 16 16 GRID Virtual Application

1.4.1.16. Quadro RTX 8000 Virtual GPU Types

Physical GPUs per board: 1
Note: C-series virtual GPU types are supported only since release 9.1.
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
RTX8000-48Q Virtual Workstations 49152 4 4096×2160 1 1 Quadro vDWS
RTX8000-24Q Virtual Workstations 24576 4 4096×2160 2 2 Quadro vDWS
RTX8000-16Q Virtual Workstations 16384 4 4096×2160 3 3 Quadro vDWS
RTX8000-12Q Virtual Workstations 12288 4 4096×2160 4 4 Quadro vDWS
RTX8000-8Q Virtual Workstations 8192 4 4096×2160 6 6 Quadro vDWS
RTX8000-6Q Virtual Workstations 6144 4 4096×2160 8 8 Quadro vDWS
RTX8000-4Q Virtual Workstations 4096 4 4096×2160 12 12 Quadro vDWS
RTX8000-3Q Virtual Workstations 3072 4 4096×2160 16 16 Quadro vDWS
RTX8000-2Q Virtual Workstations 2048 4 4096×2160 24 24 Quadro vDWS
RTX8000-1Q Virtual Workstations 1024 2 4096×2160 324 32 Quadro vDWS
RTX8000-48C Training Workloads 49152 1 4096×21602 1 1 vComputeServer or Quadro vDWS
RTX8000-24C Training Workloads 24576 1 4096×21602 2 2 vComputeServer or Quadro vDWS
RTX8000-16C Training Workloads 16384 1 4096×21602 3 3 vComputeServer or Quadro vDWS
RTX8000-12C Training Workloads 12288 1 4096×21602 4 4 vComputeServer or Quadro vDWS
RTX8000-8C Training Workloads 8192 1 4096×21602 6 6 vComputeServer or Quadro vDWS
RTX8000-6C Training Workloads 6144 1 4096×21602 8 8 vComputeServer or Quadro vDWS
RTX8000-4C Inference Workloads 4096 1 4096×21602 12 12 vComputeServer or Quadro vDWS

1.4.1.17. Quadro RTX 6000 Virtual GPU Types

Physical GPUs per board: 1
Note: C-series virtual GPU types are supported only since release 9.1.
Virtual GPU Type Intended Use Case Frame Buffer (MB) Virtual Display Heads Maximum Resolution per Display Head Maximum vGPUs per GPU Maximum vGPUs per Board Required License Edition
RTX6000-24Q Virtual Workstations 24576 4 4096×2160 1 1 Quadro vDWS
RTX6000-12Q Virtual Workstations 12288 4 4096×2160 2 2 Quadro vDWS
RTX6000-8Q Virtual Workstations 8192 4 4096×2160 3 3 Quadro vDWS
RTX6000-6Q Virtual Workstations 6144 4 4096×2160 4 4 Quadro vDWS
RTX6000-4Q Virtual Workstations 4096 4 4096×2160 6 6 Quadro vDWS
RTX6000-3Q Virtual Workstations 3072 4 4096×2160 8 8 Quadro vDWS
RTX6000-2Q Virtual Workstations 2048 4 4096×2160 12 12 Quadro vDWS
RTX6000-1Q Virtual Workstations 1024 2 4096×2160 24 24 Quadro vDWS
RTX6000-24C Training Workloads 24576 1 4096×21602 1 1 vComputeServer or Quadro vDWS
RTX6000-12C Training Workloads 12288 1 4096×21602 2 2 vComputeServer or Quadro vDWS
RTX6000-8C Training Workloads 8192 1 4096×21602 3 3 vComputeServer or Quadro vDWS
RTX6000-6C Training Workloads 6144 1 4096×21602 4 4 vComputeServer or Quadro vDWS
RTX6000-4C Inference Workloads 4096 1 4096×21602 6 6 vComputeServer or Quadro vDWS

1.4.2. Homogeneous Virtual GPUs

This release of NVIDIA vGPU supports only homogeneous virtual GPUs. At any given time, the virtual GPUs resident on a single physical GPU must be all of the same type. However, this restriction doesn’t extend across physical GPUs on the same card. Different physical GPUs on the same card may host different types of virtual GPU at the same time, provided that the vGPU types on any one physical GPU are the same.

For example, a Tesla M60 card has two physical GPUs, and can support several types of virtual GPU. Figure 3 shows the following examples of valid and invalid virtual GPU configurations on Tesla M60:

  • A valid configuration with M60-2Q vGPUs on GPU 0 and M60-4Q vGPUs on GPU 1
  • A valid configuration with M60-1B vGPUs on GPU 0 and M60-2Q vGPUs on GPU 1
  • An invalid configuration with mixed vGPU types on GPU 0
Figure 3. Example vGPU Configurations on Tesla M60

Diagram showing examples of examples of valid and invalid virtual GPU configurations on Tesla M60.

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.

1.5.1. Windows Guest VM Support

Windows guest VMs are supported only on Q-series, B-series, and A-series NVIDIA vGPU types. They are not supported on C-series NVIDIA vGPU types.

1.5.2. Linux Guest VM support

64-bit Linux guest VMs are supported only on Q-series, C-series, and B-series NVIDIA vGPU types. They are not supported on A-series NVIDIA vGPU types.

1.6. NVIDIA vGPU Software Features

NVIDIA vGPU software includes Quadro vDWS, vComputeServer, GRID Virtual PC, and GRID Virtual Applications.

1.6.1. API Support on NVIDIA vGPU

NVIDIA vGPU includes support for the following APIs:
  • Open Computing Language (OpenCL™ software) 1.2
  • OpenGL® 4.6
  • Vulkan® 1.1
  • DirectX 11
  • DirectX 12 (Windows 10)
  • Direct2D
  • DirectX Video Acceleration (DXVA)
  • NVIDIA® CUDA® 10.1 Update 1
  • NVIDIA vGPU software SDK (remote graphics acceleration)
  • NVIDIA RTX (on GPUs based on the NVIDIA Volta graphic architecture and later architectures)

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

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

  • The 8Q vGPU type on Tesla M6, Tesla M10, and Tesla M60 GPUs
  • All Q-series vGPU types on the following GPUs:
    • Tesla P4
    • Tesla P6
    • Tesla P40
    • Tesla P100 SXM2 16 GB
    • Tesla P100 PCIe 16 GB
    • Tesla P100 PCIe 12 GB
    • Tesla V100 SXM2
    • Tesla V100 SXM2 32GB
    • Tesla V100 PCIe
    • Tesla V100 PCIe 32GB
    • Tesla V100 FHHL
    • Tesla T4
    • Quadro RTX 6000
    • Quadro RTX 8000
  • All C-series vGPU types

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:
    $ nvidia-smi topo -m

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

NVIDIA vGPU does not support the following NVIDIA CUDA Toolkit features:

  • Unified Memory
  • GPUDirect remote direct memory access (RDMA)
  • Development tools such as IDEs, debuggers, profilers, and utilities as listed under CUDA Toolkit Major Components in CUDA Toolkit 10.1 Release Notes for Windows, Linux, and Mac OS
  • Tracing and profiling through the CUDA Profiling Tools Interface (CUPTI)
Note: These features are supported in GPU pass-through mode and in bare-metal deployments.

For more information about NVIDIA CUDA Toolkit, see CUDA Toolkit 10.1 Documentation.

Note:

If you are using NVIDIA vGPU software with CUDA on Linux, avoid conflicting installation methods by installing CUDA from a distribution-independent runfile package. Do not install CUDA from distribution-specific RPM or Deb package.

To ensure that the NVIDIA vGPU software graphics driver is not overwritten when CUDA is installed, deselect the CUDA driver when selecting the CUDA components to install.

For more information, see NVIDIA CUDA Installation Guide for Linux.

1.6.3. Additional Quadro vDWS Features

In addition to the features of GRID Virtual PC and GRID Virtual Applications, Quadro vDWS 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, Quadro vDWS supports up to four virtual display heads at 4K resolution.

1.6.4. 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, the following vGPU types are supported only on GPUs based on NVIDIA GPU architectures after the Maxwell architecture:

  • All Q-series vGPU types
  • All C-series vGPU types

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

The Ubuntu guest operating system is supported.

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

Installing and Configuring NVIDIA Virtual GPU Manager

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. 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.
  • 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, Red Hat Virtualization (RHV), 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 VMware Distributed Resource Scheduler (DRS) cluster.
  • A VM to be enabled with vGPU is created.
    Note:Red Hat Enterprise Linux KVM and VMware vSphere support multiple vGPUs in a VM. However, other hypervisors covered in this guide support only a single vGPU in a VM.
  • 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:

2.2. Switching the Mode of a Tesla M60 or M6 GPU

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

Only Tesla M60 and M6 GPUs require and support mode switching. Other GPUs that support NVIDIA vGPU do not require or support mode switching.

Even in compute mode, Tesla M60 and M6 GPUs do not support NVIDIA vComputeServer vGPU types.

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.

If your GPU supports both modes but is in compute mode, you must use the gpumodeswitch tool to change the mode of the GPU to graphics mode. If you are unsure which mode your GPU is in, use the gpumodeswitch tool to find out the mode.

For more information, see gpumodeswitch User Guide.

2.3. 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.

2.3.1. 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.

CAUTION:
NVIDIA Virtual GPU Manager and Guest VM drivers must be matched from the same main driver branch. If you update vGPU Manager to a release from another driver branch, guest VMs will boot with vGPU disabled until their guest vGPU driver is updated to match the vGPU Manager version. Consult Virtual GPU Software for Citrix Hypervisor Release Notes for further details.

2.3.1.1. 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:
    [root@xenserver ~]# rpm -iv NVIDIA-vGPU-xenserver-7.0-430.46.x86_64.rpm
    Preparing packages for installation...
    NVIDIA-vGPU-xenserver-7.0-430.46
    [root@xenserver ~]#
  2. Reboot the Citrix Hypervisor platform:
    [root@xenserver ~]# shutdown –r now
    
    Broadcast message from root (pts/1) (Fri Aug 30 14:24:11 2019):
    
    The system is going down for reboot NOW! 
    [root@xenserver ~]#

2.3.1.2. 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:
    [root@xenserver ~]# rpm -Uv NVIDIA-vGPU-xenserver-7.0-430.46.x86_64.rpm
    Preparing packages for installation...
    NVIDIA-vGPU-xenserver-7.0-430.46
    [root@xenserver ~]# 
    Note:

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

    [root@xenserver ~]# rpm –q NVIDIA-vGPU-xenserver-7.0-430.46
    [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-xenserver-7.0-430.46.x86_64 conflicts with file from package NVIDIA-vGPU-xenserver-7.0-430.27.x86_64
            file /usr/lib/libnvidia-ml.so from install of NVIDIA-vGPU-xenserver-7.0-430.46.x86_64 conflicts with file from package NVIDIA-vGPU-xenserver-7.0-430.27.x86_64
            ...
  3. Reboot the Citrix Hypervisor platform:
    [root@xenserver ~]# shutdown –r now
    Broadcast message from root (pts/1) (Fri Aug 30 14:24:11 2019):
    
    The system is going down for reboot NOW! 
    [root@xenserver ~]#

2.3.1.3. 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 4. NVIDIA vGPU Manager supplemental pack selected in XenCenter

    Screen capture showing 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 5. Successful installation of NVIDIA vGPU Manager supplemental pack

Screen capture showing successful installation of the NVIDIA vGPU Manager supplemental pack

2.3.1.4. 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.
    [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 Aug 30 18:46:50 2019
+------------------------------------------------------+
| NVIDIA-SMI 430.46     Driver Version: 430.46         |
|-------------------------------+----------------------+----------------------+
| 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.

2.3.2. Configuring a Citrix Hypervisor VM with Virtual GPU

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 6. Using Citrix XenCenter to configure a VM with a vGPU

    Screen capture showing the use of 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. Installing and Configuring the NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM or RHV

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

Red Hat Enterprise Linux KVM and RHV use the same Virtual GPU Manager package, but are configured with NVIDIA vGPU in different ways.

For RHV, follow this sequence of instructions:

  1. Installing the NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM or RHV
  2. Adding a vGPU to a Red Hat Virtualization (RHV) VM

For Red Hat Enterprise Linux KVM, follow this sequence of instructions:

  1. Installing the NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM or RHV
  2. Getting the BDF and Domain of a GPU on Red Hat Enterprise Linux KVM
  3. Creating an NVIDIA vGPU on Red Hat Enterprise Linux KVM
  4. Adding One or More vGPUs to a Red Hat Enterprise Linux KVM VM
  5. Setting vGPU Plugin Parameters on Red Hat Enterprise Linux KVM

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.

2.4.1. Installing the NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM or RHV

The NVIDIA Virtual GPU Manager for Red Hat Enterprise Linux KVM and Red Hat Virtualization (RHV) is provided as a .rpm file.

CAUTION:
NVIDIA Virtual GPU Manager and Guest VM drivers must be matched from the same main driver branch. If you update vGPU Manager to a release from another driver branch, guest VMs will boot with vGPU disabled until their guest vGPU driver is updated to match the vGPU Manager version. Consult Virtual GPU Software for Red Hat Enterprise Linux with KVM Release Notes for further details.

2.4.1.1. Installing the Virtual GPU Manager Package for Red Hat Enterprise Linux KVM or RHV

Before installing the RPM package for Red Hat Enterprise Linux KVM or RHV, ensure that the sshd service on the Red Hat Enterprise Linux KVM or RHV 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).
  1. Securely copy the RPM file from the system where you downloaded the file to the Red Hat Enterprise Linux KVM or RHV 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 or RHV server.
    # ssh root@kvm-server
    kvm-server
    The host name or IP address of the Red Hat Enterprise Linux KVM or RHV server.
  3. Change to the directory on the Red Hat Enterprise Linux KVM or RHV server to which you copied the RPM file.
    # 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.
    # rpm -iv NVIDIA-vGPU-rhel-7.5-430.46.x86_64.rpm
    Preparing packages for installation...
    NVIDIA-vGPU-rhel-7.5-430.46
    #
  5. Reboot the Red Hat Enterprise Linux KVM or RHV server.
    # systemctl reboot

2.4.1.2. Verifying the Installation of the NVIDIA vGPU Software for Red Hat Enterprise Linux KVM or RHV

After the Red Hat Enterprise Linux KVM or RHV server has rebooted, verify the installation of the NVIDIA vGPU software package for Red Hat Enterprise Linux KVM or RHV.
  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.
    # 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.
    # 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 Aug 30 18:46:50 2019
+------------------------------------------------------+
| NVIDIA-SMI 430.46     Driver Version: 430.46         |
|-------------------------------+----------------------+----------------------+
| 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.

2.4.2. Adding a vGPU to a Red Hat Virtualization (RHV) VM

Ensure that the VM to which you want to add the vGPU is shut down.
  1. Determine the mediated device type (mdev_type) identifiers of the vGPU types available on the RHV host.
    # vdsm-client Host hostdevListByCaps
    ...
      "mdev": {
                   "nvidia-155": {
                       "name": "GRID M10-2B",
                       "available_instances": "4"
                   },
                   "nvidia-36": {
                       "name": "GRID M10-0Q",
                       "available_instances": "16"
                   },
      ...
    
    The preceding example shows the mdev_type identifiers of the following vGPU types:
    • For the GRID M10-2B vGPU type, the mdev_type identifier is nvidia-155.
    • For the GRID M10-0Q vGPU type, the mdev_type identifier is nvidia-36.
  2. Note the mdev_type identifier of the vGPU type that you want to add.
  3. Log in to the RHV Administration Portal.
  4. From the Main Navigation Menu, choose Compute > Virtual Machines > virtual-machine-name.
    virtual-machine-name
    The name of the virtual machine to which you want to add the vGPU.
  5. Click Edit.
  6. In the Edit Virtual Machine window that opens, click Show Advanced Options and in the list of options, select Custom Properties.
  7. From the drop-down list, select mdev_type.
  8. In the text field, type the mdev_type identifier of the vGPU type that you want to add and click OK.

    Screen capture showing options in the Edit Virtual Machine window for adding a vGPU to an RHV VM

After adding a vGPU to an RHV VM, start the VM.

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. Getting the BDF and Domain of a GPU on Red Hat Enterprise Linux KVM

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 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.
    # lspci | grep NVIDIA

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

    # 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.
    # 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.

    # 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.
    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.

    # 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'/>

2.4.4. Creating an NVIDIA vGPU on Red Hat Enterprise Linux KVM

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

Note: The mdev device file that you create to represent the vGPU does not persist when the host is rebooted and must be re-created after the host is rebooted. If necessary, 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, by writing a custom script that is executed when the host is rebooted.
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 Red Hat Enterprise Linux KVM.
  1. Change to the mdev_supported_types directory for the physical GPU.
    # 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.

    # 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.
    # 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.

    # 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.
    # 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.

    # cat nvidia-41/available_instances
    4
  4. Generate a correctly formatted universally unique identifier (UUID) for the vGPU.
    # 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.
    # 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.

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

    An mdev device file for the vGPU is added 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. Confirm that the vGPU was created.
    # 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

2.4.5. Adding One or More vGPUs to a Red Hat Enterprise Linux KVM VM

To support applications and workloads that are compute or graphics intensive, you can add multiple vGPUs to a single VM. If you are adding multiple vGPUs to a single VM, all vGPUs must be of the same type.

For details about which Red Hat Enterprise Linux KVM 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.

Ensure that the following prerequisites are met:

You can add vGPUs to a Red Hat Enterprise Linux KVM VM by using any of the following tools:

  • The virsh command
  • The QEMU command line

After adding vGPUs to a Red Hat Enterprise Linux KVM 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.

2.4.5.1. Adding One or More vGPUs to a Red Hat Enterprise Linux KVM VM by Using virsh

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

    <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
    <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>

2.4.5.2. Adding One or More vGPUs to a Red Hat Enterprise Linux KVM VM by Using the QEMU Command Line

Add the following options to the QEMU command line:
  • For each vGPU that you want to add to the VM, add one -device option in the following format:

    -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.
  • Add a -uuid option to specify the VM as follows:

    -uuid vm-uuid
    vm-uuid
    The UUID that was assigned to the VM when the VM was created.

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

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

2.4.6. Setting vGPU Plugin Parameters on Red Hat Enterprise Linux KVM

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 Red Hat Enterprise Linux KVM host.

  1. Change to the nvidia subdirectory of the mdev device directory that represents the vGPU.
    # cd /sys/bus/mdev/devices/uuid/nvidia
    uuid
    The UUID of the vGPU, for example, aa618089-8b16-4d01-a136-25a0f3c73123.
  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.
    # 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.

    # echo "frame_rate_limiter=0, disable_vnc=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

2.4.7. Deleting a vGPU on Red Hat Enterprise Linux KVM

For each vGPU that you want to delete, perform this task in a Linux command shell on the Red Hat Enterprise Linux KVM host.

Before you begin, ensure that the following prerequisites are met:

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

    # 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.
    # 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.
    # echo "1" > remove
    Note: On the Red Hat Virtualization (RHV) kernel, if you try to remove a vGPU device while its VM is running, the vGPU device might not be removed even if the remove file has been written to successfully. To confirm that the vGPU device is removed, confirm that the UUID of the vGPU is not found in the sysfs file system.

2.4.8. 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 Red Hat Enterprise Linux KVM.
  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.
    # 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 BDF 06:00.0 is bound to the vfio-pci kernel module and is being used for GPU pass through.

       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.
      # 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.
      # 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.

      # 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.
      # 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.

      # cd /sys/bus/pci/devices/0000\:06\:00.0
    2. Write the kernel module name nvidia to the driver_override file in this directory.
      # echo nvidia > driver_override
    3. Change to the sysfs directory that represents the nvidia kernel module.
      # cd /sys/bus/pci/drivers/nvidia
    4. Write the domain, bus, slot, and function of the GPU to the bind file in this directory.
      # 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.

      # echo 0000:06:00.0 > bind

2.4.9. NVIDIA vGPU Information in the sysfs File System

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

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 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:

# 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
After the Virtual GPU Manager is installed on the host and the host has been rebooted, a directory named mdev_supported_types is created under the sysfs directory for each physical GPU. 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:
# 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 vGPU is created, the content of the available_instances for all other vGPU types on the physical GPU is set to 0. This behavior enforces the requirement that all vGPUs on a physical GPU must be of the same type.
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:
# 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:
# 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:
# cat name
GRID M10-2Q

2.5. 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 or VMware vSGA. The vGPU Manager vSphere Installation Bundles (VIBs) for VMware vSphere 6.5 and later provide vSGA and vGPU functionality in a single VIB. For VMware vSphere 6.0, vSGA and vGPU functionality are provided in separate vGPU Manager VIBs.

For NVIDIA vGPU, follow this sequence of instructions:

  1. Installing and Updating the NVIDIA Virtual GPU Manager for vSphere
  2. Configuring VMware vMotion with vGPU for VMware vSphere
  3. Changing the Default Graphics Type in VMware vSphere 6.5 and Later
  4. Configuring a vSphere VM with NVIDIA vGPU

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.

For VMware vSGA, follow this sequence of instructions:

  1. Installing and Updating the NVIDIA Virtual GPU Manager for vSphere
  2. Configuring a vSphere VM with VMware vSGA

Installation of the NVIDIA vGPU software graphics driver for the guest OS is not required for vSGA.

2.5.1. Installing and Updating the NVIDIA Virtual GPU Manager for vSphere

The NVIDIA Virtual GPU Manager runs on the ESXi host. It is provided in the following formats:

  • As a VIB file, which must be copied to the ESXi host and then installed
  • As an offline bundle that you can import manually as explained in Import Patches Manually in the VMware vSphere documentation
CAUTION:
NVIDIA Virtual GPU Manager and Guest VM drivers must be matched from the same main driver branch. If you update vGPU Manager to a release from another driver branch, guest VMs will boot with vGPU disabled until their guest vGPU driver is updated to match the vGPU Manager version. Consult Virtual GPU Software for VMware vSphere Release Notes for further details.

2.5.1.1. Installing the NVIDIA Virtual GPU Manager Package for vSphere

To install 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.

Note: Before proceeding with the vGPU Manager installation make sure that all VMs are powered off and the ESXi host is placed in maintenance mode. Refer to VMware’s documentation on how to place an ESXi host in maintenance mode.
  1. Use the esxcli command to install the vGPU Manager package:
    [root@esxi:~] esxcli software vib install -v directory/NVIDIA-vGPU-VMware_ESXi_6.7_Host_Driver_430.46-1OEM.600.0.0.2159203.vib
    Installation Result
       Message: Operation finished successfully.
       Reboot Required: false
       VIBs Installed: NVIDIA-vGPU-VMware_ESXi_6.7_Host_Driver_430.46-1OEM.600.0.0.2159203
       VIBs Removed:
       VIBs Skipped:

    directory is the absolute path to the directory that contains the VIB file. You must specify the absolute path even if the VIB file is in the current working directory.

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

2.5.1.2. Updating the NVIDIA Virtual GPU Manager Package for vSphere

Update the vGPU Manager VIB package 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.

Note: Before proceeding with the vGPU Manager update, make sure that all VMs are powered off and the ESXi host is placed in maintenance mode. Refer to VMware’s documentation on how to place an ESXi host in maintenance mode
  1. Use the esxcli command to update the vGPU Manager package:
    [root@esxi:~] esxcli software vib update -v directory/NVIDIA-vGPU-VMware_ESXi_6.7_Host_Driver_430.46-1OEM.600.0.0.2159203.vib
    
    Installation Result
       Message: Operation finished successfully.
       Reboot Required: false
       VIBs Installed: NVIDIA-vGPU-VMware_ESXi_6.7_Host_Driver_430.46-1OEM.600.0.0.2159203
       VIBs Removed: NVIDIA-vGPU-VMware_ESXi_6.7_Host_Driver_430.27-1OEM.600.0.0.2159203
       VIBs Skipped:

    directory is the path to the directory that contains the VIB file.

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

2.5.1.3. 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.
    [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 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 Aug 30 17:56:22 2019
+------------------------------------------------------+
| NVIDIA-SMI 430.46     Driver Version: 430.46         |
|-------------------------------+----------------------+----------------------+
| 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.

2.5.2. 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.

    Screen capture showing the vgpu.hotmigrate.enabled setting in the Edit Advanced vCenter Server Settings window.

2.5.3. Changing the Default Graphics Type in VMware vSphere 6.5 and Later

The vGPU Manager VIBs for VMware vSphere 6.5 and later provide vSGA and vGPU functionality in a single VIB. After this VIB is installed, the default graphics type is Shared, which provides vSGA functionality. To enable vGPU support for VMs in VMware vSphere 6.5, 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.
Note:

If you are using a supported version of VMware vSphere earlier than 6.5, or are configuring a VM to use vSGA, omit this task.

Change the default graphics type before configuring vGPU. Output from the VM console in the VMware vSphere Web Client is not available for VMs that are running vGPU.

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 7. Shared default graphics type

    Screen capture of the Host Graphics tab in the VMware vCenter Web UI, showing the default graphics type as Shared

  5. In the Edit Host Graphics Settings dialog box that opens, select Shared Direct and click OK.
    Figure 8. Host graphics settings for vGPU

    Screen capture showing the Edit Host Graphics Settings dialog box in the VMware vCenter Web UI for changing the default graphics type

    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 9. Shared graphics type

      Screen capture of the Graphics Devices tab in the VMware vCenter Web UI, showing the active type and configured type of two NVIDIA GPUs as Shared

    2. In the Edit Graphics Device Settings dialog box that opens, select Shared Direct and click OK.
      Figure 10. Graphics device settings for a physical GPU

      Screen capture showing the Edit Graphics Device Settings dialog box in the VMware vCenter Web UI for changing the graphics type of a physical GPU

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

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

    1. Stop the Xorg service.
      [root@esxi:~] /etc/init.d/xorg stop
    2. Stop nv-hostengine.
      [root@esxi:~] nv-hostengine -t
    3. Wait for 1 second to allow nv-hostengine to stop.
    4. Start nv-hostengine.
      [root@esxi:~] nv-hostengine -d
    5. Start the Xorg service.
      [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 11. Shared direct graphics type

    Screen capture of the Graphics Devices tab in the VMware vCenter Web UI, showing the active type and configured type of two NVIDIA GPUs as Shared Direct

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:

2.5.4. 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. If you are adding multiple vGPUs to a single VM, all vGPUs must be of the same type.

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.

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

CAUTION:
Output from the VM console in the VMware vSphere Web Client is not available for VMs that are running vGPU. Make sure that you have installed an alternate means of accessing the VM (such as VMware Horizon or a VNC server) before you configure vGPU.

VM console in vSphere Web Client will become active again once the vGPU parameters are removed from the VM’s configuration.

Note: If you are configuring a VM to use VMware vSGA, omit this task.
  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 12. VM settings for vGPU

    Screen capture showing VM settings for vGPU in the Edit Settings window in the VMware vCenter Web UI

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

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.

2.5.5. Configuring a vSphere VM with VMware vSGA

Virtual Shared Graphics Acceleration (vSGA) is a feature of VMware vSphere that enables multiple virtual machines to share the physical GPUs on ESXi hosts.

Note: If you are configuring a VM to use NVIDIA vGPU, omit this task.

Before configuring a vSphere VM with vSGA, ensure that these prerequisites are met:

  • VMware tools are installed on the VM.
  • The VM is powered off.
  • The NVIDIA Virtual GPU Manager package for vSphere is installed.
  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 device list, expand the Video card node and set the following options:
    1. Select the Enable 3D support option.
    2. Set the 3D Renderer to Hardware.
    For more information, see Configure 3D Graphics and Video Cards in the VMware Horizon documentation.
  5. Start the VM.
  6. After the VM has booted, verify that the VM has been configured correctly with vSGA.
    1. Under the Display Adapter section of Device Manager, confirm that VMware SVGA 3D is listed.
    2. Verify that the virtual machine is using the GPU card.
      # gpuvm

      The output from the command is similar to the following example for a VM named samplevm1:

      Xserver unix:0, GPU maximum memory 4173824KB
      pid 21859, VM samplevm1, reserved 131072KB of GPU memory.
      GPU memory left 4042752KB.

      The memory reserved for the VM and the GPU maximum memory depend on the GPU installed in the host and the 3D memory allocated to the virtual machine.

Installation of the NVIDIA vGPU software graphics driver for the guest OS is not required for vSGA.

2.6. 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. These GPUs are supplied with ECC memory enabled.

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.

2.6.1. 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 from 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.
    # nvidia-smi -q
    
    ==============NVSMI LOG==============
    
    Timestamp                           : Tue Sep 10 18:36:45 2019
    Driver Version                      : 430.46
    
    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:
      # nvidia-smi -e 0
    • If you want to change the ECC status to off for a specific GPU or vGPU, run this command:
      # 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.

      # 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.
    # nvidia—smi —q
    
    ==============NVSMI LOG==============
    
    Timestamp                           : Tue Sep 10 18:37:53 2019
    Driver Version                      : 430.46
    
    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.

2.6.2. 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 from 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.
    # nvidia-smi -q
    
    ==============NVSMI LOG==============
    
    Timestamp                           : Tue Sep 10 18:36:45 2019
    Driver Version                      : 430.46
    
    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:
      # nvidia-smi -e 1
    • If you want to change the ECC status to on for a specific GPU or vGPU, run this command:
      # 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.

      # 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.
    # nvidia—smi —q
    
    ==============NVSMI LOG==============
    
    Timestamp                           : Tue Sep 10 18:37:53 2019
    Driver Version                      : 430.46
    
    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.

3. Using GPU Pass-Through

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
Note: If you are configuring a GPU for pass-through, do not install the NVIDIA Virtual GPU Manager.

3.1. 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.

3.1.1. 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 13. Using XenCenter to configure a pass-through GPU Screen capture showing how to use 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.

3.1.2. 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 ~]#
CAUTION:
Do not assign pass-through GPUs using the legacy other-config:pci parameter setting. This mechanism is not supported alongside the XenCenter UI and xe vgpu mechanisms, and attempts to use it may lead to undefined results.
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. Using GPU Pass-Through on Red Hat Enterprise Linux KVM

You can configure a GPU for pass-through on Red Hat Enterprise Linux Kernel-based Virtual Machine (KVM) 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, ensure that the following prerequisites are met:

  • Red Hat Enterprise Linux KVM is installed.
  • A virtual disk has been created.
    Note: Do not create any virtual disks in /root.
  • A virtual machine has been created.

3.2.1. 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:

  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 a Red Hat Enterprise Linux KVM 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 virsh

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

  1. Verify that the vfio-pci module is loaded.
    # 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.
    # lspci | grep NVIDIA

    The NVIDIA GPUs listed in this example have the PCI device BDFs 85:00.0 and 86:00.0.

    # 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.
    # 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.

    # 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.
    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.

    # 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.
    # 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.
    <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.

    <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.
    # virsh start vm-name
    vm-name
    The name of the VM that you assigned the GPU to.
After configuring a Red Hat Enterprise Linux KVM 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.

3.2.3. 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.
    # lspci | grep NVIDIA

    The NVIDIA GPUs listed in this example have the PCI device BDFs 85:00.0 and 86:00.0.

    # 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:
    -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.

    -device vfio-pci,host=85:00.0
After configuring a Red Hat Enterprise Linux KVM 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.

3.2.4. 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 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 Red Hat Enterprise Linux KVM.
  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.
    # 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 BDF 06:00.0 is bound to the nvidia kernel module and is being used for vGPU.

       06:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
             Subsystem: NVIDIA Corporation Device 115e
             Kernel driver in use: nvidia
  2. 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.
      # 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.

      # cd /proc/driver/nvidia/gpus/0000\:06\:00.0
    3. Write the value 1 to the unbindLock file in this directory.
      # echo 1 > unbindLock
    4. Confirm that the unbindLock file now contains the value 1.
      # 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.

  3. Unbind the GPU from nvidia kernel module.
    1. Change to the sysfs directory that represents the nvidia kernel module.
      # cd /sys/bus/pci/drivers/nvidia
    2. Write the domain, bus, slot, and function of the GPU to the unbind file in this directory.
      # 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.

      # echo 0000:06:00.0 > unbind
  4. 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.
      # 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.

      # 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.
      # echo vfio-pci > driver_override
    3. Change to the sysfs directory that represents the nvidia kernel module.
      # 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.
      # 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.

      # echo 0000:06:00.0 > bind
    5. Change back to the sysfs directory that contains the PCI device information for the physical GPU.
      # cd /sys/bus/pci/devices/domain\:bus\:slot.function
    6. Clear the content of the driver_override file in this directory.
      # 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.

3.3. 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.

3.3.1. 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.

Ensure that the following prerequisites are met:

  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:

    PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)
  2. Dismount the GPU from host to make it unavailable to the host so that it can be used solely by the VM.
    Dismount-VMHostAssignableDevice -LocationPath gpu-device-location -force
    gpu-device-location
    The location path of the GPU that you obtained in the previous step.

    This example dismounts the GPU at the location path PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000).

    Dismount-VMHostAssignableDevice -LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)" -force
  3. Assign the GPU that you dismounted in the previous step to the VM.
    Add-VMAssignableDevice -LocationPath gpu-device-location -VMName vm-name
    gpu-device-location
    The location path of the GPU that you dismounted in the previous step.
    vm-name
    The name of the VM to which you are attaching the GPU.
    Note: You can assign a pass-through GPU 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.

    Add-VMAssignableDevice -LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)" -VMName VM1
  4. Power on the VM. The guest OS should now be able to use the GPU.
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.

3.3.2. Returning a GPU to the Host OS from a VM on Windows Server with Hyper-V

Perform this task in the Windows PowerShell.

  1. List the GPUs that are currently assigned to the virtual machine (VM).
    Get-VMAssignableDevice -VMName vm-name
    vm-name
    The name of the VM whose assigned GPUs you want to list.
  2. Shut down the VM to which the GPU is assigned.
  3. Remove the GPU from VM to which it is assigned.
    Remove-VMAssignableDevice –LocationPath gpu-device-location -VMName vm-name
    gpu-device-location
    The location path of the GPU that you are removing, which you obtained in the previous step.
    vm-name
    The name of the VM from which you are removing the GPU.

    This example removes the GPU at the location path PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000) from the VM VM1.

    Remove-VMAssignableDevice –LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)" -VMName VM1
    After the GPU is removed from the VM, it is unavailable to the host operating system (OS) until you remount it on the host OS.
  4. Remount the GPU on the host OS.
    Mount-VMHostAssignableDevice –LocationPath gpu-device-location
    gpu-device-location
    The location path of the GPU that you are remounting, which you specified in the previous step to remove the GPU 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.

    Mount-VMHostAssignableDevice -LocationPath "PCIROOT(80)#PCI(0200)#PCI(0000)#PCI(1000)#PCI(0000)"
    The host OS should now be able to use the GPU.

3.4. 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
  1. Open the vCenter Web UI.
  2. In the vCenter Web UI, right-click the ESXi host and choose Settings.
  3. From the Hardware menu, choose PCI Devices and click the Edit icon.
  4. Select all NVIDIA GPUs and click OK.
  5. Reboot the ESXi host.
  6. After the ESXi host has booted, right-click the VM and choose Edit Settings.
  7. From the New Device menu, choose PCI Device and click Add.
  8. On the page that opens, from the New Device drop-down list, select the GPU.
  9. Click Reserve all memory and click OK.
  10. Start the VM.

For more information about vDGA, see the following topics in the VMware Horizon documentation:

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.

4. 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 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 only on Q-series, B-series, and A-series NVIDIA vGPU types. They are not supported on C-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 14. NVIDIA driver installation

    Screen capture showing 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 15. Verifying NVIDIA driver operation using NVIDIA Control Panel

      Screen capture showing the verification of 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.

4.2. Installing the NVIDIA vGPU Software Graphics Driver on Linux

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. 64-bit Linux guest VMs are supported only on Q-series, C-series, and B-series NVIDIA vGPU types. They are not supported on 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. If the Nouveau driver for NVIDIA graphics cards is present, disable it before installing the NVIDIA vGPU software graphics driver.

The procedure for installing the driver is the same in a VM and on bare metal.

Installation of the NVIDIA vGPU software graphics driver for Linux requires:

  • Compiler toolchain
  • Kernel headers

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.

  1. Copy the NVIDIA vGPU software Linux driver package, for example NVIDIA-Linux_x86_64-430.46-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:
      [nvidia@localhost ~]$ sudo init 3
    • On Ubuntu platforms, do the following:
      1. Use CTRL-ALT-F1 to switch to a console login prompt.
      2. Log in and shut down the display manager:
        [nvidia@localhost ~]$ sudo service lightdm stop
  3. From a console shell, run the driver installer as the root user.
    sudo sh ./ NVIDIA-Linux_x86_64-352.47-grid.run
    In some instances the installer may fail to detect the installed kernel headers and sources. In this situation, re-run the installer, specifying the kernel source path with the --kernel-source-path option:
    sudo sh ./ NVIDIA-Linux_x86_64-352.47-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 16. Update xorg.conf settings

    Screen capture of the character-based UI of the NVIDIA Linux driver installer displaying the prompt to update the X configuration file (xorg.conf) settings

  5. Once installation has completed, 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.
      [nvidia@localhost ~]$ nvidia-settings
      The NVIDIA X Server Settings dialog box opens to show that the NVIDIA driver is operational.
      Figure 17. Verifying operation with nvidia-settings

      Screen capture of the NVIDIA X Server Settings dialog box showing that the NVIDIA driver is operational

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.

4.3. Disabling the Wayland Display Server Protocol for Red Hat Enterprise Linux

Starting with Red Hat Enterprise Linux Desktop 8.0, the Wayland display server protocol is used by default on supported GPU and graphics driver configurations. However, the NVIDIA vGPU software graphics driver for Linux requires the X Window System. Before installing the driver, you must disable the Wayland display server protocol to revert to the X Window System.

Perform this task from the host or guest VM that is running Red Hat Enterprise Linux Desktop.
This task requires administrative access.
  1. In a plain text editor, edit the file /etc/gdm/custom.conf and remove the comment from the option WaylandEnable=false.
  2. Save your changes to /etc/gdm/custom.conf.
  3. Reboot the host or guest VM.

5. Licensing an NVIDIA vGPU

NVIDIA vGPU is a licensed product. When booted on a supported GPU, a vGPU runs at reduced capability until a license is acquired.

The performance of an unlicensed vGPU is restricted as follows:

  • Frame rate is capped at 3 frames per second.
  • GPU resource allocations are limited, which will prevent some applications from running correctly.
  • On vGPUs that support CUDA, CUDA is disabled.

These restrictions are removed when a license is acquired.

After you license NVIDIA vGPU, the VM that is set up to use NVIDIA vGPU is capable of running the full range of DirectX and OpenGL graphics applications.

If licensing is configured, the virtual machine (VM) obtains a license from the license server when a vGPU is booted on these GPUs. The VM retains the license until it is shut down. It then releases the license back to the license server. Licensing settings persist across reboots and need only be modified if the license server address changes, or the VM is switched to running GPU pass through.

Note: For complete information about configuring and using NVIDIA vGPU software licensed features, including vGPU, refer to Virtual GPU Client Licensing User Guide.

5.1. Licensing an NVIDIA vGPU on Windows

Perform this task from the guest VM to which the vGPU is assigned.

The NVIDIA Control Panel tool that you use to perform this task detects that a vGPU is assigned to the VM and, therefore, provides no options for selecting the license type. After you license the vGPU, NVIDIA vGPU software automatically selects the correct type of license based on the vGPU type.

  1. Open NVIDIA Control Panel:
    • Right-click on the Windows desktop and select NVIDIA Control Panel from the menu.
    • Open Windows Control Panel and double-click the NVIDIA Control Panel icon.
  2. In NVIDIA Control Panel, select the Manage License task in the Licensing section of the navigation pane.
    Note: If the Licensing section and Manage License task are not displayed in NVIDIA Control Panel, the system has been configured to hide licensing controls in NVIDIA Control Panel. For information about registry settings, see Virtual GPU Client Licensing User Guide.
    The Manage License task pane shows that NVIDIA vGPU is currently unlicensed.
    Figure 18. Managing vGPU licensing in NVIDIA Control Panel

    Screen capture showing the Manage License option in NVIDIA Control Panel for a vGPU license

  3. In the Primary License Server field, enter the address of your primaryNVIDIA vGPU software License Server. The address can be a fully-qualified domain name such as gridlicense1.example.com, or an IP address such as 10.31.20.45. If you have only one license server configured, enter its address in this field.
  4. Leave the Port Number field under the Primary License Server field unset. The port defaults to 7070, which is the default port number used by NVIDIA vGPU software License Server.
  5. In the Secondary License Server field, enter the address of your secondary NVIDIA vGPU software License Server. If you have only one license server configured, leave this field unset. The address can be a fully-qualified domain name such as gridlicense2.example.com, or an IP address such as 10.31.20.46.
  6. Leave the Port Number field under the Secondary License Server field unset. The port defaults to 7070, which is the default port number used by NVIDIA vGPU software License Server.
  7. Click Apply to assign the settings. The system requests the appropriate license for the current vGPU from the configured license server.

The vGPU within the VM should now exhibit full frame rate, resolution, and display output capabilities. The VM is now capable of running the full range of DirectX and OpenGL graphics applications.

If the system fails to obtain a license, see Virtual GPU Client Licensing User Guide for guidance on troubleshooting.

5.2. Licensing an NVIDIA vGPU on Linux

Perform this task from the guest VM to which the vGPU is assigned.

The NVIDIA X Server Settings tool that you use to perform this task detects that a vGPU is assigned to the VM and, therefore, provides no options for selecting the license type. After you license the vGPU, NVIDIA vGPU software automatically selects the correct type of license based on the vGPU type.

Ensure that the Manage License option is enabled as explained in index.html#enabling-license-management-x-server-settings.

Note: Do not enable the Manage License option with Red Hat Enterprise Linux 6.8 and 6.9 or CentOS 6.8 and 6.9. To prevent a segmentation fault in DBus code from causing the nvidia-gridd service from exiting, the GUI for licensing must be disabled with these OS versions.
  1. Start NVIDIA X Server Settings by using the method for launching applications provided by your Linux distribution. For example, on Ubuntu Desktop, open the Dash, search for NVIDIA X Server Settings, and click the NVIDIA X Server Settings icon.
  2. In the NVIDIA X Server Settings window that opens, click Manage GRID License. The License Edition section of the NVIDIA X Server Settings window shows that NVIDIA vGPU is currently unlicensed.
  3. In the Primary Server field, enter the address of your primary NVIDIA vGPU software License Server. The address can be a fully-qualified domain name such as gridlicense1.example.com, or an IP address such as 10.31.20.45. If you have only one license server configured, enter its address in this field.
  4. Leave the Port Number field under the Primary Server field unset. The port defaults to 7070, which is the default port number used by NVIDIA vGPU software License Server.
  5. In the Secondary Server field, enter the address of your secondary NVIDIA vGPU software License Server. If you have only one license server configured, leave this field unset. The address can be a fully-qualified domain name such as gridlicense2.example.com, or an IP address such as 10.31.20.46.
  6. Leave the Port Number field under the Secondary Server field unset. The port defaults to 7070, which is the default port number used by NVIDIA vGPU software License Server.
  7. Click Apply to assign the settings. The system requests the appropriate license for the current vGPU from the configured license server.
The vGPU within the VM should now exhibit full frame rate, resolution, and display output capabilities. The VM is now capable of running the full range of DirectX and OpenGL graphics applications.
If the system fails to obtain a license, see Virtual GPU Client Licensing User Guide for guidance on troubleshooting.

6. Modifying a VM's NVIDIA vGPU Configuration

You can modify a VM's NVIDIA vGPU configuration by removing the NVIDIA vGPU configuration from a VM or by modifying GPU allocation policy.

6.1. Removing a VM’s NVIDIA vGPU Configuration

Remove a VM’s NVIDIA vGPU configuration when you no longer require the VM to use a virtual GPU.

6.1.1. Removing a Citrix Virtual Apps and Desktops VM’s vGPU configuration

You can remove a virtual GPU assignment from a VM, such that it no longer uses a virtual GPU, by using either XenCenter or the xe command.

Note: The VM must be in the powered-off state in order for its vGPU configuration to be modified or removed.

6.1.1.1. Removing a VM’s vGPU configuration by using XenCenter

  1. Set the GPU type to None in the VM’s GPU Properties, as shown in Figure 19.
    Figure 19. Using XenCenter to remove a vGPU configuration from a VM

    Screen capture showing the use of XenCenter to remove a vGPU configuration from a VM

  2. Click OK.

6.1.1.2. Removing a VM’s vGPU configuration by using xe

  1. Use vgpu-list to discover the vGPU object UUID associated with a given VM:
    [root@xenserver ~]# xe vgpu-list vm-uuid=e71afda4-53f4-3a1b-6c92-a364a7f619c2
    uuid ( RO)              : c1c7c43d-4c99-af76-5051-119f1c2b4188
               vm-uuid ( RO): e71afda4-53f4-3a1b-6c92-a364a7f619c2
        gpu-group-uuid ( RO): d53526a9-3656-5c88-890b-5b24144c3d96
  2. Use vgpu-destroy to delete the virtual GPU object associated with the VM:
    [root@xenserver ~]# xe vgpu-destroy uuid=c1c7c43d-4c99-af76-5051-119f1c2b4188
    [root@xenserver ~]#

6.1.2. Removing a vSphere VM’s vGPU Configuration

To remove a vSphere vGPU configuration from a VM:
  1. Select Edit settings after right-clicking on the VM in the vCenter Web UI.
  2. Select the Virtual Hardware tab.
  3. Mouse over the PCI Device entry showing NVIDIA GRID vGPU and click on the (X) icon to mark the device for removal.
  4. Click OK to remove the device and update the VM settings.

6.2. Modifying GPU Allocation Policy

Citrix Hypervisor and VMware vSphere both support the breadth first and depth-first GPU allocation policies for vGPU-enabled VMs.

breadth-first
The breadth-first allocation policy attempts to minimize the number of vGPUs running on each physical GPU. Newly created vGPUs are placed on the physical GPU that can support the new vGPU and that has the fewest vGPUs already resident on it. This policy generally leads to higher performance because it attempts to minimize sharing of physical GPUs, but it may artificially limit the total number of vGPUs that can run.
depth-first
The depth-first allocation policy attempts to maximize the number of vGPUs running on each physical GPU. Newly created vGPUs are placed on the physical GPU that can support the new vGPU and that has the most vGPUs already resident on it. This policy generally leads to higher density of vGPUs, particularly when different types of vGPUs are being run, but may result in lower performance because it attempts to maximize sharing of physical GPUs.

Each hypervisor uses a different GPU allocation policy by default.

  • Citrix Hypervisor uses the depth-first allocation policy.
  • VMware vSphere ESXi uses the breadth-first allocation policy.

If the default GPU allocation policy does not meet your requirements for performance or density of vGPUs, you can change it.

6.2.1. Modifying GPU Allocation Policy on Citrix Hypervisor

You can modify GPU allocation policy on Citrix Hypervisor by using XenCenter or the xe command.

6.2.1.1. Modifying GPU Allocation Policy by Using xe

The allocation policy of a GPU group is stored in the allocation-algorithm parameter of the gpu-group object.

To change the allocation policy of a GPU group, use gpu-group-param-set:

[root@xenserver ~]# xe gpu-group-param-get uuid=be825ba2-01d7-8d51-9780-f82cfaa64924 param-name=allocation-algorithmdepth-first
[root@xenserver ~]# xe gpu-group-param-set uuid=be825ba2-01d7-8d51-9780-f82cfaa64924 allocation-algorithm=breadth-first
[root@xenserver ~]#

6.2.1.2. Modifying GPU Allocation Policy GPU by Using XenCenter

You can modify GPU allocation policy from the GPU tab in XenCenter.

Figure 20. Modifying GPU placement policy in XenCenter

Screen capture showing how to use the GPU tab in XenCenter to control GPU placement policy

6.2.2. Modifying GPU Allocation Policy on VMware vSphere

How to switch to a depth-first allocation scheme depends on the version of VMware vSphere that you are using.

  • Supported versions earlier than 6.5: Add the following parameter to /etc/vmware/config:

    vGPU.consolidation = true
  • Version 6.5: Use the vSphere Web Client.

Before using the vSphere Web Client to change the allocation scheme, 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 21. Breadth-first allocation scheme setting for vGPU-enabled VMs

    Screen capture of the Host Graphics tab in the VMware vCenter Web UI, showing the allocation scheme for vGPU-enabled VMs as breadth-first

  5. In the Edit Host Graphics Settings dialog box that opens, select these options and click OK.
    1. If not already selected, select Shared Direct.
    2. Select Group VMs on GPU until full.
    Figure 22. Host graphics settings for vGPU

    Screen capture showing the Edit Host Graphics Settings dialog box in the VMware vCenter Web UI for changing the allocation scheme for vGPU-enabled VMs

    After you click OK, the default graphics type changes to Shared Direct and the allocation scheme for vGPU-enabled VMs is breadth-first.

    Figure 23. Depth-first allocation scheme setting for vGPU-enabled VMs

    Screen capture of the Host Graphics tab in the VMware vCenter Web UI, showing the default graphics type as Shared Direct and the allocation scheme for vGPU-enabled VMs as depth-first

  6. Restart the ESXi host or the Xorg service on the host.

See also the following topics in the VMware vSphere documentation:

6.3. Migrating a VM Configured with vGPU

On some hypervisors, NVIDIA vGPU software supports migration of VMs that are configured with vGPU.

Before migrating a VM configured with vGPU, ensure that the following prerequisites are met:
  • The VM is configured with vGPU.
  • The VM is running.
  • The VM obtained a suitable vGPU license when it was booted.
  • The destination host has a physical GPU of the same type as the GPU where the vGPU currently resides.
  • ECC memory configuration (enabled or disabled) on both the source and destination hosts must be identical.
  • The GPU topologies (including NVLink widths) on both the source and destination hosts must be identical.
How to migrate a VM configured with vGPU depends on the hypervisor that you are using.

After migration, the vGPU type of the vGPU remains unchanged.

The time required for migration depends on the amount of frame buffer that the vGPU has. Migration for a vGPU with a large amount of frame buffer is slower than for a vGPU with a small amount of frame buffer.

6.3.1. Migrating a VM Configured with vGPU on Citrix Hypervisor

NVIDIA vGPU software supports XenMotion for VMs that are configured with vGPU. XenMotion enables you to move a running virtual machine from one physical host machine to another host with very little disruption or downtime. For a VM that is configured with vGPU, the vGPU is migrated with the VM to an NVIDIA GPU on the other host. The NVIDIA GPUs on both host machines must be of the same type.

For details about which Citrix Hypervisor versions, NVIDIA GPUs, and guest OS releases support XenMotion with vGPU, see Virtual GPU Software for Citrix Hypervisor Release Notes.

For best performance, the physical hosts should be configured to use the following:

  • Shared storage, such as NFS, iSCSI, or Fiberchannel

    If shared storage is not used, migration can take a very long time because vDISK must also be migrated.

  • 10 GB networking.
  1. In Citrix XenCenter, context-click the VM and from the menu that opens, choose Migrate.
  2. From the list of available hosts, select the destination host to which you want to migrate the VM. The destination host must have a physical GPU of the same type as the GPU where the vGPU currently resides. Furthermore, the physical GPU must be capable of hosting the vGPU. If these requirements are not met, no available hosts are listed.

6.3.2. Migrating a VM Configured with vGPU on VMware vSphere

NVIDIA vGPU software supports VMware vMotion for VMs that are configured with vGPU. VMware vMotion enables you to move a running virtual machine from one physical host machine to another host with very little disruption or downtime. For a VM that is configured with vGPU, the vGPU is migrated with the VM to an NVIDIA GPU on the other host. The NVIDIA GPUs on both host machines must be of the same type.

For details about which VMware vSphere versions, NVIDIA GPUs, and guest OS releases support suspend and resume, see Virtual GPU Software for VMware vSphere Release Notes.

Perform this task in the VMware vSphere web client by using the Migration wizard.

Before migrating a VM configured with vGPU on VMware vSphere, ensure that the following prerequisites are met:
  1. Context-click the VM and from the menu that opens, choose Migrate.
  2. For the type of migration, select Change compute resource only and click Next. If you select Change both compute resource and storage, the time required for the migration increases.
  3. Select the destination host and click Next. The destination host must have a physical GPU of the same type as the GPU where the vGPU currently resides. Furthermore, the physical GPU must be capable of hosting the vGPU. If these requirements are not met, no available hosts are listed.
  4. Select the destination network and click Next.
  5. Select the migration priority level and click Next.
  6. Review your selections and click Finish.
For more information, see the following topics in the VMware documentation:

If NVIDIA vGPU migration is not configured, any attempt to migrate a VM with an NVIDIA vGPU fails and a window containing the following error message is displayed:

Compatibility Issue/Host
Migration was temporarily disabled due to another 
migration activity.
vGPU hot migration is not enabled.

The window appears as follows:



Screen capture showing the Compatibility Issue/Host error window

If you see this error, configure NVIDIA vGPU migration as explained in Configuring VMware vMotion with vGPU for VMware vSphere.

If your version of VMware vSpehere ESXi does not support vMotion for VMs configured with NVIDIA vGPU, any attempt to migrate a VM with an NVIDIA vGPU fails and a window containing the following error message is displayed:

Compatibility Issues
...
A required migration feature is not supported on the "Source" host 'host-name'.

A warning or error occurred when migrating the virtual machine.
Virtual machine relocation, or power on after relocation or cloning can fail if 
vGPU resources are not available on the destination host.

The window appears as follows:



Screen capture showing the Compatibility Issues error window

For details about which VMware vSphere versions, NVIDIA GPUs, and guest OS releases support suspend and resume, see Virtual GPU Software for VMware vSphere Release Notes.

6.3.3. Suspending and Resuming a VM Configured with vGPU on VMware vSphere

NVIDIA vGPU software supports suspend and resume for VMs that are configured with vGPU.

For details about which VMware vSphere versions, NVIDIA GPUs, and guest OS releases support suspend and resume, see Virtual GPU Software for VMware vSphere Release Notes.

Perform this task in the VMware vSphere web client.

  • To suspend a VM, context-click the VM that you want to suspend, and from the context menu that pops up, choose Power > Suspend.
  • To resume a VM, context-click the VM that you want to resume, and from the context menu that pops up, choose Power > Power On.

7. Monitoring GPU Performance

NVIDIA vGPU software enables you to monitor the performance of physical GPUs and virtual GPUs from the hypervisor and from within individual guest VMs.

You can use several tools for monitoring GPU performance:

  • From any supported hypervisor, and from a guest VM that is running a 64-bit edition of Windows or Linux, you can use NVIDIA System Management Interface, nvidia-smi.
  • From Citrix Hypervisor, you can use Citrix XenCenter.
  • From a Windows guest VM, you can use these tools:
    • Windows Performance Monitor
    • Windows Management Instrumentation (WMI)

7.1. NVIDIA System Management Interface nvidia-smi

NVIDIA System Management Interface, nvidia-smi, is a command-line tool that reports management information for NVIDIA GPUs.

The nvidia-smi tool is included in the following packages:

  • NVIDIA Virtual GPU Manager package for each supported hypervisor
  • NVIDIA driver package for each supported guest OS

The scope of the reported management information depends on where you run nvidia-smi from:

  • From a hypervisor command shell, such as the Citrix Hypervisor dom0 shell or VMware ESXi host shell, nvidia-smi reports management information for NVIDIA physical GPUs and virtual GPUs present in the system.

    Note: When run from a hypervisor command shell, nvidia-smi will not list any GPU that is currently allocated for GPU pass-through.
  • From a guest VM that is running Windows or Linux, nvidia-smi retrieves usage statistics for vGPUs or pass-through GPUs that are assigned to the VM.

    From a Windows guest VM, you can run nvidia-smi from a command prompt by changing to the C:\Program Files\NVIDIA Corporation\NVSMI folder and running the nvidia-smi.exe command.

7.2. Monitoring GPU Performance from a Hypervisor

You can monitor GPU performance from any supported hypervisor by using the NVIDIA System Management Interface nvidia-smi command-line utility. On Citrix Hypervisor platforms, you can also use Citrix XenCenter to monitor GPU performance.

Note: You cannot monitor from the hypervisor the performance of GPUs that are being used for GPU pass-through. You can monitor the performance of pass-through GPUs only from within the guest VM that is using them.

7.2.1. Using nvidia-smi to Monitor GPU Performance from a Hypervisor

You can get management information for the NVIDIA physical GPUs and virtual GPUs present in the system by running nvidia-smi from a hypervisor command shell such as the Citrix Hypervisor dom0 shell or the VMware ESXi host shell.

Without a subcommand, nvidia-smi provides management information for physical GPUs. To examine virtual GPUs in more detail, use nvidia-smi with the vgpu subcommand.

From the command line, you can get help information about the nvidia-smi tool and the vgpu subcommand.

Help Information Command
A list of subcommands supported by the nvidia-smi tool. Note that not all subcommands apply to GPUs that support NVIDIA vGPU software. nvidia-smi -h
A list of all options supported by the vgpu subcommand. nvidia-smi vgpu –h

7.2.1.1. Getting a Summary of all Physical GPUs in the System

To get a summary of all physical GPUs in the system, along with PCI bus IDs, power state, temperature, current memory usage, and so on, run nvidia-smi without additional arguments.

Each vGPU instance is reported in the Compute processes section, together with its physical GPU index and the amount of frame-buffer memory assigned to it.

In the example that follows, three vGPUs are running in the system: One vGPU is running on each of the physical GPUs 0, 1, and 2.

[root@vgpu ~]# nvidia-smi
Fri Aug 30 09:26:18 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.46                 Driver Version: 430.46                    |
|-------------------------------+----------------------+----------------------+
| 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   | 0000:83:00.0     Off |                  Off |
| N/A   31C    P8    23W / 150W |   1889MiB /  8191MiB |      7%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla M60           On   | 0000:84:00.0     Off |                  Off |
| N/A   26C    P8    23W / 150W |    926MiB /  8191MiB |      9%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla M10           On   | 0000:8A:00.0     Off |                  N/A |
| N/A   23C    P8    10W /  53W |   1882MiB /  8191MiB |     12%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla M10           On   | 0000:8B:00.0     Off |                  N/A |
| N/A   26C    P8    10W /  53W |     10MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   4  Tesla M10           On   | 0000:8C:00.0     Off |                  N/A |
| N/A   34C    P8    10W /  53W |     10MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   5  Tesla M10           On   | 0000:8D:00.0     Off |                  N/A |
| N/A   32C    P8    10W /  53W |     10MiB /  8191MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|    0     11924  C+G   /usr/lib64/xen/bin/vgpu                       1856MiB |
|    1     11903  C+G   /usr/lib64/xen/bin/vgpu                        896MiB |
|    2     11908  C+G   /usr/lib64/xen/bin/vgpu                       1856MiB |
+-----------------------------------------------------------------------------+
[root@vgpu ~]#

7.2.1.2. Getting a Summary of all vGPUs in the System

To get a summary of the vGPUs currently that are currently running on each physical GPU in the system, run nvidia-smi vgpu without additional arguments.

[root@vgpu ~]# nvidia-smi vgpu
Fri Aug 30 09:27:06 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.46                 Driver Version: 430.46                    |
|-------------------------------+--------------------------------+------------+
| GPU  Name                     | Bus-Id                         | GPU-Util   |
|      vGPU ID    Name          | VM ID    VM Name               | vGPU-Util  |
|===============================+================================+============|
|   0  Tesla M60                | 0000:83:00.0                   |   7%       |
|      11924      GRID M60-2Q   | 3        Win7-64 GRID test 2   |       6%   |
+-------------------------------+--------------------------------+------------+
|   1  Tesla M60                | 0000:84:00.0                   |   9%       |
|      11903      GRID M60-1B   | 1        Win8.1-64 GRID test 3 |       8%   |
+-------------------------------+--------------------------------+------------+
|   2  Tesla M10                | 0000:8A:00.0                   |  12%       |
|      11908      GRID M10-2Q   | 2        Win7-64 GRID test 1   |      10%   |
+-------------------------------+--------------------------------+------------+
|   3  Tesla M10                | 0000:8B:00.0                   |   0%       |
+-------------------------------+--------------------------------+------------+
|   4  Tesla M10                | 0000:8C:00.0                   |   0%       |
+-------------------------------+--------------------------------+------------+
|   5  Tesla M10                | 0000:8D:00.0                   |   0%       |
+-------------------------------+--------------------------------+------------+
[root@vgpu ~]#

7.2.1.3. Getting vGPU Details

To get detailed information about all the vGPUs on the platform, run nvidia-smi vgpu with the –q or --query option.

To limit the information retrieved to a subset of the GPUs on the platform, use the –i or --id option to select one or more vGPUs.

[root@vgpu ~]# nvidia-smi vgpu -q -i 1
GPU 00000000:86:00.0
    Active vGPUs              : 1
    vGPU ID                   : 3251634178
        VM ID                 : 1
        VM Name               : Win7
        vGPU Name             : GRID M60-8Q
        vGPU Type             : 22
        vGPU UUID             : b8c6d0e1-d167-11e8-b8c9-55705e5a54a6
        Guest Driver Version  : 411.81
        License Status        : Unlicensed
        Accounting Mode       : Disabled
        Accounting Buffer Size: 4000
        Frame Rate Limit      : 3 FPS
        FB Memory Usage       :
            Total             : 8192 MiB
            Used              : 675 MiB
            Free              : 7517 MiB
        Utilization           :
            Gpu               : 3 %
            Memory            : 0 %
            Encoder           : 0 %
            Decoder           : 0 %
        Encoder Stats         :
            Active Sessions   : 0
            Average FPS       : 0
            Average Latency   : 0
        FBC Stats             :
            Active Sessions   : 1
            Average FPS       : 227
            Average Latency   : 4403
[root@vgpu ~]#

7.2.1.4. Monitoring vGPU engine usage

To monitor vGPU engine usage across multiple vGPUs, run nvidia-smi vgpu with the –u or --utilization option.

For each vGPU, the usage statistics in the following table are reported once every second. The table also shows the name of the column in the command output under which each statistic is reported.

Statistic Column
3D/Compute sm
Memory controller bandwidth mem
Video encoder enc
Video decoder dec

Each reported percentage is the percentage of the physical GPU’s capacity that a vGPU is using. For example, a vGPU that uses 20% of the GPU’s graphics engine’s capacity will report 20%.

To modify the reporting frequency, use the –l or --loop option.

To limit monitoring to a subset of the GPUs on the platform, use the –i or --id option to select one or more vGPUs.

[root@vgpu ~]# nvidia-smi vgpu -u
# gpu    vgpu    sm   mem   enc   dec
# Idx      Id     %     %     %     %
    0   11924     6     3     0     0
    1   11903     8     3     0     0
    2   11908    10     4     0     0
    3       -     -     -     -     -
    4       -     -     -     -     -
    5       -     -     -     -     -
    0   11924     6     3     0     0
    1   11903     9     3     0     0
    2   11908    10     4     0     0
    3       -     -     -     -     -
    4       -     -     -     -     -
    5       -     -     -     -     -
    0   11924     6     3     0     0
    1   11903     8     3     0     0
    2   11908    10     4     0     0
    3       -     -     -     -     -
    4       -     -     -     -     -
    5       -     -     -     -     -
^C[root@vgpu ~]#

7.2.1.5. Monitoring vGPU engine usage by applications

To monitor vGPU engine usage by applications across multiple vGPUs, run nvidia-smi vgpu with the –p option.

For each application on each vGPU, the usage statistics in the following table are reported once every second. Each application is identified by its process ID and process name. The table also shows the name of the column in the command output under which each statistic is reported.

Statistic Column
3D/Compute sm
Memory controller bandwidth mem
Video encoder enc
Video decoder dec

Each reported percentage is the percentage of the physical GPU’s capacity used by an application running on a vGPU that resides on the physical GPU. For example, an application that uses 20% of the GPU’s graphics engine’s capacity will report 20%.

To modify the reporting frequency, use the –l or --loop option.

To limit monitoring to a subset of the GPUs on the platform, use the –i or --id option to select one or more vGPUs.

[root@vgpu ~]# nvidia-smi vgpu -p
# GPU    vGPU process        process   sm  mem  enc  dec
# Idx      Id      Id           name    %    %    %    %
    0   38127    1528        dwm.exe    0    0    0    0
    1   37408    4232  DolphinVS.exe   32   25    0    0
    1  257869    4432    FurMark.exe   16   12    0    0
    1  257969    4552    FurMark.exe   48   37    0    0
    0   38127    1528        dwm.exe    0    0    0    0
    1   37408    4232  DolphinVS.exe   16   12    0    0
    1  257911     656  DolphinVS.exe   32   24    0    0
    1  257969    4552    FurMark.exe   48   37    0    0
    0   38127    1528        dwm.exe    0    0    0    0
    1  257869    4432    FurMark.exe   38   30    0    0
    1  257911     656  DolphinVS.exe   19   14    0    0
    1  257969    4552    FurMark.exe   38   30    0    0
    0   38127    1528        dwm.exe    0    0    0    0
    1  257848    3220    Balls64.exe   16   12    0    0
    1  257869    4432    FurMark.exe   16   12    0    0
    1  257911     656  DolphinVS.exe   16   12    0    0
    1  257969    4552    FurMark.exe   48   37    0    0
    0   38127    1528        dwm.exe    0    0    0    0
    1  257911     656  DolphinVS.exe   32   25    0    0
    1  257969    4552    FurMark.exe   64   50    0    0
    0   38127    1528        dwm.exe    0    0    0    0
    1   37408    4232  DolphinVS.exe   16   12    0    0
    1  257911     656  DolphinVS.exe   16   12    0    0
    1  257969    4552    FurMark.exe   64   49    0    0
    0   38127    1528        dwm.exe    0    0    0    0
    1   37408    4232  DolphinVS.exe   16   12    0    0
    1  257869    4432    FurMark.exe   16   12    0    0
    1  257969    4552    FurMark.exe   64   49    0    0
[root@vgpu ~]#

7.2.1.6. Monitoring Encoder Sessions

Note: Encoder sessions can be monitored only for vGPUs assigned to Windows VMs. No encoder session statistics are reported for vGPUs assigned to Linux VMs.

To monitor the encoder sessions for processes running on multiple vGPUs, run nvidia-smi vgpu with the –es or --encodersessions option.

For each encoder session, the following statistics are reported once every second:

  • GPU ID
  • vGPU ID
  • Encoder session ID
  • PID of the process in the VM that created the encoder session
  • Codec type, for example, H.264 or H.265
  • Encode horizontal resolution
  • Encode vertical resolution
  • One-second trailing average encoded FPS
  • One-second trailing average encode latency in microseconds

To modify the reporting frequency, use the –l or --loop option.

To limit monitoring to a subset of the GPUs on the platform, use the –i or --id option to select one or more vGPUs.

[root@vgpu ~]# nvidia-smi vgpu -es
# GPU    vGPU Session Process   Codec       H       V Average     Average
# Idx      Id      Id      Id    Type     Res     Res     FPS Latency(us)
    1   21211       2    2308   H.264    1920    1080     424        1977
    1   21206       3    2424   H.264    1920    1080       0           0
    1   22011       1    3676   H.264    1920    1080     374        1589
    1   21211       2    2308   H.264    1920    1080     360         807
    1   21206       3    2424   H.264    1920    1080     325        1474
    1   22011       1    3676   H.264    1920    1080     313        1005
    1   21211       2    2308   H.264    1920    1080     329        1732
    1   21206       3    2424   H.264    1920    1080     352        1415
    1   22011       1    3676   H.264    1920    1080     434        1894
    1   21211       2    2308   H.264    1920    1080     362        1818
    1   21206       3    2424   H.264    1920    1080     296        1072
    1   22011       1    3676   H.264    1920    1080     416        1994
    1   21211       2    2308   H.264    1920    1080     444        1912
    1   21206       3    2424   H.264    1920    1080     330        1261
    1   22011       1    3676   H.264    1920    1080     436        1644
    1   21211       2    2308   H.264    1920    1080     344        1500
    1   21206       3    2424   H.264    1920    1080     393        1727
    1   22011       1    3676   H.264    1920    1080     364        1945
    1   21211       2    2308   H.264    1920    1080     555        1653
    1   21206       3    2424   H.264    1920    1080     295         925
    1   22011       1    3676   H.264    1920    1080     372        1869
    1   21211       2    2308   H.264    1920    1080     326        2206
    1   21206       3    2424   H.264    1920    1080     318        1366
    1   22011       1    3676   H.264    1920    1080     464        2015
    1   21211       2    2308   H.264    1920    1080     305        1167
    1   21206       3    2424   H.264    1920    1080     445        1892
    1   22011       1    3676   H.264    1920    1080     361         906
    1   21211       2    2308   H.264    1920    1080     353        1436
    1   21206       3    2424   H.264    1920    1080     354        1798
    1   22011       1    3676   H.264    1920    1080     373        1310 
^C[root@vgpu ~]#

7.2.1.7. Monitoring Frame Buffer Capture (FBC) Sessions

To monitor the FBC sessions for processes running on multiple vGPUs, run nvidia-smi vgpu with the -fs or --fbcsessions option.

For each FBC session, the following statistics are reported once every second:

  • GPU ID
  • vGPU ID
  • FBC session ID
  • PID of the process in the VM that created the FBC session
  • Display ordinal associated with the FBC session.
  • FBC session type
  • FBC session flags
  • Capture mode
  • Maximum horizontal resolution supported by the session
  • Maximum vertical resolution supported by the session
  • Horizontal resolution requested by the caller in the capture call
  • Vertical resolution requested by the caller in the capture call
  • Moving average of new frames captured per second by the session
  • Moving average new frame capture latency in microseconds for the session

To modify the reporting frequency, use the –l or --loop option.

To limit monitoring to a subset of the GPUs on the platform, use the –i or --id option to select one or more vGPUs.

[root@vgpu ~]# nvidia-smi vgpu -fs
# GPU        vGPU   Session   Process   Display   Session Diff. Map  Class. Map       Capture   Max H   Max V     H     V   Average       Average
# Idx          Id        Id        Id   Ordinal      Type     State       State          Mode     Res     Res   Res   Res       FPS   Latency(us)
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         -         -         -         -         -           -             -       -       -     -     -         -             -
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         -         -         -         -         -           -             -       -       -     -     -         -             -
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         -         -         -         -         -           -             -       -       -     -     -         -             -
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         -         -         -         -         -           -             -       -       -     -     -         -             -
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         -         -         -         -         -           -             -       -       -     -     -         -             -
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
# GPU        vGPU   Session   Process   Display   Session Diff. Map  Class. Map       Capture   Max H   Max V     H     V   Average       Average
# Idx          Id        Id        Id   Ordinal      Type     State       State          Mode     Res     Res   Res   Res       FPS   Latency(us)
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled       Unknown    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160  1600   900        25         39964
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160  1600   900        25         39964
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
# GPU        vGPU   Session   Process   Display   Session Diff. Map  Class. Map       Capture   Max H   Max V     H     V   Average       Average
# Idx          Id        Id        Id   Ordinal      Type     State       State          Mode     Res     Res   Res   Res       FPS   Latency(us)
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160  1600   900       135          7400
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160  1600   900       227          4403
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160  1600   900       227          4403
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
# GPU        vGPU   Session   Process   Display   Session Diff. Map  Class. Map       Capture   Max H   Max V     H     V   Average       Average
# Idx          Id        Id        Id   Ordinal      Type     State       State          Mode     Res     Res   Res   Res       FPS   Latency(us)
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    0           -         -         -         -         -         -           -             -       -       -     -     -         -             -
    1  3251634178         1      3984         0     ToSys  Disabled    Disabled      Blocking    4096    2160     0     0         0             0
    2           -         -         -         -         -         -           -             -       -       -     -     -         -             -
^C[root@vgpu ~]#

7.2.1.8. Listing Supported vGPU Types

To list the virtual GPU types that the GPUs in the system support, run nvidia-smi vgpu with the –s or --supported option.

To limit the retrieved information to a subset of the GPUs on the platform, use the –i or --id option to select one or more vGPUs.

[root@vgpu ~]# nvidia-smi vgpu -s -i 0
GPU 0000:83:00.0
    GRID M60-0B
    GRID M60-0Q
    GRID M60-1A
    GRID M60-1B
    GRID M60-1Q
    GRID M60-2A
    GRID M60-2Q
    GRID M60-4A
    GRID M60-4Q
    GRID M60-8A
    GRID M60-8Q
[root@vgpu ~]#

To view detailed information about the supported vGPU types, add the –v or --verbose option:

[root@vgpu ~]# nvidia-smi vgpu -s -i 0 -v   | less
GPU 00000000:83:00.0
    vGPU Type ID              : 0xb
        Name                  : GRID M60-0B
        Class                 : NVS
        Max Instances         : 16
        Device ID             : 0x13f210de
        Sub System ID         : 0x13f21176
        FB Memory             : 512 MiB
        Display Heads         : 2
        Maximum X Resolution  : 2560
        Maximum Y Resolution  : 1600
        Frame Rate Limit      : 45 FPS
        GRID License          : GRID-Virtual-PC,2.0;GRID-Virtual-WS,2.0;GRID-Virtual-WS-Ext,2.0;Quadro-Virtual-DWS,5.0
    vGPU Type ID              : 0xc
        Name                  : GRID M60-0Q
        Class                 : Quadro
        Max Instances         : 16
        Device ID             : 0x13f210de
        Sub System ID         : 0x13f2114c
        FB Memory             : 512 MiB
        Display Heads         : 2
        Maximum X Resolution  : 2560
        Maximum Y Resolution  : 1600
        Frame Rate Limit      : 60 FPS
        GRID License          : GRID-Virtual-WS,2.0;GRID-Virtual-WS-Ext,2.0;Quadro-Virtual-DWS,5.0
    vGPU Type ID              : 0xd
        Name                  : GRID M60-1A
        Class                 : NVS
        Max Instances         : 8
…
[root@vgpu ~]#

7.2.1.9. Listing the vGPU Types that Can Currently Be Created

To list the virtual GPU types that can currently be created on GPUs in the system, run nvidia-smi vgpu with the –c or --creatable option.

This property is a dynamic property that varies according to the vGPUs that are already running on each GPU.

To limit the retrieved information to a subset of the GPUs on the platform, use the –i or --id option to select one or more vGPUs.

[root@vgpu ~]# nvidia-smi vgpu -c -i 0
GPU 0000:83:00.0
    GRID M60-2Q
[root@vgpu ~]#

To view detailed information about the vGPU types that can currently be created, add the –v or --verbose option.

7.2.2. Using Citrix XenCenter to monitor GPU performance

If you are using Citrix Hypervisor as your hypervisor, you can monitor GPU performance in XenCenter.
  1. Click on a server’s Performance tab.
  2. Right-click on the graph window, then select Actions and New Graph.
  3. Provide a name for the graph.
  4. In the list of available counter resources, select one or more GPU counters.
Counters are listed for each physical GPU not currently being used for GPU pass-through.
Figure 24. Using Citrix XenCenter to monitor GPU performanceScreen capture of Citrix Xencenter showing GPU performance graphs

7.3. Monitoring GPU Performance from a Guest VM

You can use monitoring tools within an individual guest VM to monitor the performance of vGPUs or pass-through GPUs that are assigned to the VM. The scope of these tools is limited to the guest VM within which you use them. You cannot use monitoring tools within an individual guest VM to monitor any other GPUs in the platform.

For a vGPU, only these metrics are reported in a guest VM:

  • 3D/Compute
  • Memory controller
  • Video encoder
  • Video decoder
  • Frame buffer usage

Other metrics normally present in a GPU are not applicable to a vGPU and are reported as zero or N/A, depending on the tool that you are using.

7.3.1. Using nvidia-smi to Monitor GPU Performance from a Guest VM

In VMs that are running Windows and 64-bit editions of Linux, you can use the nvidia-smi command to retrieve statistics for the total usage by all applications running in the VM and usage by individual applications of the following resources:

  • GPU
  • Video encoder
  • Video decoder
  • Frame buffer

To use nvidia-smi to retrieve statistics for the total resource usage by all applications running in the VM, run the following command:

nvidia-smi dmon

The following example shows the result of running nvidia-smi dmon from within a Windows guest VM.

Figure 25. Using nvidia-smi from a Windows guest VM to get total resource usage by all applications

Screen capture showing a Windows Command Prompt window in which the nvidia-smi command has been run to retrieve total resource usage by all applications

To use nvidia-smi to retrieve statistics for resource usage by individual applications running in the VM, run the following command:

nvidia-smi pmon
Figure 26. Using nvidia-smi from a Windows guest VM to get resource usage by individual applications

Screen capture showing a Windows Command Prompt window in which the nvidia-smi command has been run to retrieve resource usage by individual applications

7.3.2. Using Windows Performance Counters to monitor GPU performance

In Windows VMs, GPU metrics are available as Windows Performance Counters through the NVIDIA GPU object.

Any application that is enabled to read performance counters can access these metrics. You can access these metrics directly through the Windows Performance Monitor application that is included with the Windows OS.

The following example shows GPU metrics in the Performance Monitor application.

Figure 27. Using Windows Performance Monitor to monitor GPU performance

Screen capture showing GPU metrics n the Windows Performance Monitor application

On vGPUs, the following GPU performance counters read as 0 because they are not applicable to vGPUs:

  • % Bus Usage
  • % Cooler rate
  • Core Clock MHz
  • Fan Speed
  • Memory Clock MHz
  • PCI-E current speed to GPU Mbps
  • PCI-E current width to GPU
  • PCI-E downstream width to GPU
  • Power Consumption mW
  • Temperature C

7.3.3. Using NVWMI to monitor GPU performance

In Windows VMs, Windows Management Instrumentation (WMI) exposes GPU metrics in the ROOT\CIMV2\NV namespace through NVWMI. NVWMI is included with the NVIDIA driver package. After the driver is installed, NVWMI help information in Windows Help format is available as follows:

C:\Program Files\NVIDIA Corporation\NVIDIA WMI Provider>nvwmi.chm

Any WMI-enabled application can access these metrics. The following example shows GPU metrics in the third-party application WMI Explorer, which is available for download from the from the CodePlex WMI Explorer page.

Figure 28. Using WMI Explorer to monitor GPU performance

Screen capture showing GPU metrics from the ROOT\CIMV2\NV namespace in the WMI Explorer screen

On vGPUs, some instance properties of the following classes do not apply to vGPUs:

  • Gpu
  • PcieLink

Gpu instance properties that do not apply to vGPUs

Gpu Instance Property Value reported on vGPU
gpuCoreClockCurrent -1
memoryClockCurrent -1
pciDownstreamWidth 0
pcieGpu.curGen 0
pcieGpu.curSpeed 0
pcieGpu.curWidth 0
pcieGpu.maxGen 1
pcieGpu.maxSpeed 2500
pcieGpu.maxWidth 0
power -1
powerSampleCount -1
powerSamplingPeriod -1
verVBIOS.orderedValue 0
verVBIOS.strValue -
verVBIOS.value 0

PcieLink instance properties that do not apply to vGPUs

No instances of PcieLink are reported for vGPU.

8. Citrix Hypervisor vGPU Management

You can perform Citrix Hypervisor advanced vGPU management techniques by using XenCenter and by using xe command line operations.

8.1. Management objects for GPUs

Citrix Hypervisor uses four underlying management objects for GPUs: physical GPUs, vGPU types, GPU groups, and vGPUs. These objects are used directly when managing vGPU by using xe, and indirectly when managing vGPU by using XenCenter.

8.1.1. pgpu - Physical GPU

A pgpu object represents a physical GPU, such as one of the multiple GPUs present on a Tesla M60 or M10 card. Citrix Hypervisor automatically creates pgpu objects at startup to represent each physical GPU present on the platform.

8.1.1.1. Listing the pgpu Objects Present on a Platform

To list the physical GPU objects present on a platform, use xe pgpu-list.

For example, this platform contains a Tesla P40 card with a single physical GPU and a Tesla M60 card with two physical GPUs:

[root@xenserver ~]# xe pgpu-list
uuid ( RO)              : f76d1c90-e443-4bfc-8f26-7959a7c85c68
       vendor-name ( RO): NVIDIA Corporation
       device-name ( RO): GP102GL [Tesla P40]
    gpu-group-uuid ( RW): 134a7b71-5ceb-8066-ef1b-3b319fb2bef3

uuid ( RO)              : 4c5e05d9-60fa-4fe5-9cfc-c641e95c8e85
       vendor-name ( RO): NVIDIA Corporation
       device-name ( RO): GM204GL [Tesla M60]
    gpu-group-uuid ( RW): 3df80574-c303-f020-efb3-342f969da5de

uuid ( RO)              : 4960e63c-c9fe-4a25-add4-ee697263e04c
       vendor-name ( RO): NVIDIA Corporation
       device-name ( RO): GM204GL [Tesla M60]
    gpu-group-uuid ( RW): d32560f2-2158-42f9-d201-511691e1cb2b
[root@xenserver ~]#

8.1.1.2. Viewing Detailed Information About a pgpu Object

To view detailed information about a pgpu, use xe pgpu-param-list:
[root@xenserver ~]# xe pgpu-param-list uuid=4960e63c-c9fe-4a25-add4-ee697263e04c
uuid ( RO)                        : 4960e63c-c9fe-4a25-add4-ee697263e04c
                 vendor-name ( RO): NVIDIA Corporation
                 device-name ( RO): GM204GL [Tesla M60]
                 dom0-access ( RO): enabled
    is-system-display-device ( RO): false
              gpu-group-uuid ( RW): d32560f2-2158-42f9-d201-511691e1cb2b
        gpu-group-name-label ( RO): 86:00.0 VGA compatible controller: NVIDIA Corporation GM204GL   [Tesla M60] (rev a1)
                   host-uuid ( RO): b55452df-1ee4-4e4e-bd97-3aee97b2123a
             host-name-label ( RO): xs7.1
                      pci-id ( RO): 0000:86:00.0
                dependencies (SRO):
                other-config (MRW):
        supported-VGPU-types ( RO): 5b9acd25-06fa-43e1-8b53-c35bceb8515c; 16326fcb-543f-4473-a4ae-2d30516a2779; 0f9fc39a-0758-43c8-88cc-54c8491aa4d4; cecb2033-3b4a-437c-a0c0-c9dfdb692d9b; 095d8939-5f84-405d-a39a-684738f9b957; 56c335be-4036-4a38-816c-c246a60556ac; ef0a94fd-2230-4fd4-aee0-d6d3f6ced4ef; 11615f73-47b8-4494-806e-2a7b5e1d7bea; dbd8f2ac-f548-4c40-804b-9133cfda8090; a33189f1-1417-4593-aa7d-978c4f25b953; 3f437337-3682-4897-a7ba-6334519f4c19; 99900aab-42b0-4cc4-8832-560ff6b60231
          enabled-VGPU-types (SRW): 5b9acd25-06fa-43e1-8b53-c35bceb8515c; 16326fcb-543f-4473-a4ae-2d30516a2779; 0f9fc39a-0758-43c8-88cc-54c8491aa4d4; cecb2033-3b4a-437c-a0c0-c9dfdb692d9b; 095d8939-5f84-405d-a39a-684738f9b957; 56c335be-4036-4a38-816c-c246a60556ac; ef0a94fd-2230-4fd4-aee0-d6d3f6ced4ef; 11615f73-47b8-4494-806e-2a7b5e1d7bea; dbd8f2ac-f548-4c40-804b-9133cfda8090; a33189f1-1417-4593-aa7d-978c4f25b953; 3f437337-3682-4897-a7ba-6334519f4c19; 99900aab-42b0-4cc4-8832-560ff6b60231
              resident-VGPUs ( RO):
[root@xenserver ~]#

8.1.1.3. Viewing physical GPUs in XenCenter

To view physical GPUs in XenCenter, click on the server’s GPU tab:

Figure 29. Physical GPU display in XenCenter

Screen capture showing details for a physical GPU in Citrix XenCenter

8.1.2. vgpu-type - Virtual GPU Type

A vgpu-type represents a type of virtual GPU, such as M60-0B, P40-8A, and P100-16Q. An additional, pass-through vGPU type is defined to represent a physical GPU that is directly assignable to a single guest VM.

Citrix Hypervisor automatically creates vgpu-type objects at startup to represent each virtual type supported by the physical GPUs present on the platform.

8.1.2.1. Listing the vgpu-type Objects Present on a Platform

To list the vgpu-type objects present on a platform, use xe vgpu-type-list.

For example, as this platform contains Tesla P100, Tesla P40, and Tesla M60 cards, the vGPU types reported are the types supported by these cards:

[root@xenserver ~]# xe vgpu-type-list
uuid ( RO)              : d27f84a2-53f8-4430-ad15-0eca225cd974
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-12A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 57bb231f-f61b-408e-a0c0-106bddd91019
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-3Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 9b2eaba5-565f-4cb4-ad9b-6347cfb03e93
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-2Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : af593219-0800-42da-a51d-d13b35f589e1
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-4A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 5b9acd25-06fa-43e1-8b53-c35bceb8515c
       vendor-name ( RO):
        model-name ( RO): passthrough
         max-heads ( RO): 0
    max-resolution ( RO): 0x0


uuid ( RO)              : af121387-0b58-498a-8d04-fe0305e4308f
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-3A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 3b28a628-fd6c-4cda-b0fb-80165699229e
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P100-4Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 99900aab-42b0-4cc4-8832-560ff6b60231
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-1Q
         max-heads ( RO): 2
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 0f9fc39a-0758-43c8-88cc-54c8491aa4d4
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-4A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 4017c9dd-373f-431a-b36f-50e4e5c9f0c0
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-6A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 125fbbdf-406e-4d7c-9de8-a7536aa1a838
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-24A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 88162a34-1151-49d3-98ae-afcd963f3105
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-2A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : ad00a95c-d066-4158-b361-487abf57dd30
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-1A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 11615f73-47b8-4494-806e-2a7b5e1d7bea
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-0Q
         max-heads ( RO): 2
    max-resolution ( RO): 2560x1600


uuid ( RO)              : 6ea0cd56-526c-4966-8f53-7e1721b95a5c
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-4Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 095d8939-5f84-405d-a39a-684738f9b957
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-4Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 9626e649-6802-4396-976d-94c0ead1f835
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-12Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : a33189f1-1417-4593-aa7d-978c4f25b953
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-0B
         max-heads ( RO): 2
    max-resolution ( RO): 2560x1600


uuid ( RO)              : dbd8f2ac-f548-4c40-804b-9133cfda8090
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-1A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : ef0a94fd-2230-4fd4-aee0-d6d3f6ced4ef
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-8Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 67fa06ab-554e-452b-a66e-a4048a5bfdf7
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-6Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 739d7b8e-50e2-48a1-ae0d-5047aa490f0e
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-8A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 9fb62f31-7dfb-46f8-a4a9-cca8db48147e
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P100-8Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 56c335be-4036-4a38-816c-c246a60556ac
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-1B
         max-heads ( RO): 4
    max-resolution ( RO): 2560x1600


uuid ( RO)              : 3f437337-3682-4897-a7ba-6334519f4c19
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-8A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 25dbb2d3-a074-4f9f-92ce-b42d8b3d1de2
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-1B
         max-heads ( RO): 4
    max-resolution ( RO): 2560x1600


uuid ( RO)              : cecb2033-3b4a-437c-a0c0-c9dfdb692d9b
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-2Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 16326fcb-543f-4473-a4ae-2d30516a2779
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID M60-2A
         max-heads ( RO): 1
    max-resolution ( RO): 1280x1024


uuid ( RO)              : 7ca2399f-89ab-49dd-bf96-75071ced28fc
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-24Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : 9611a3f4-d130-4a66-a61b-21d4a2ca4663
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-8Q
         max-heads ( RO): 4
    max-resolution ( RO): 4096x2160


uuid ( RO)              : d0e4a116-a944-42ef-a8dc-62a54c4d2d77
       vendor-name ( RO): NVIDIA Corporation
        model-name ( RO): GRID P40-1Q
         max-heads ( RO): 2
    max-resolution ( RO): 4096x2160

[root@xenserver ~]#

8.1.2.2. Viewing Detailed Information About a vgpu-type Object

To see detailed information about a vgpu-type, use xe vgpu-type-param-list:

[root@xenserver ~]# xe xe vgpu-type-param-list uuid=7ca2399f-89ab-49dd-bf96-75071ced28fc
uuid ( RO)                       : 7ca2399f-89ab-49dd-bf96-75071ced28fc
                vendor-name ( RO): NVIDIA Corporation
                 model-name ( RO): GRID P40-24Q
           framebuffer-size ( RO): 24092082176
                  max-heads ( RO): 4
             max-resolution ( RO): 4096x2160
         supported-on-PGPUs ( RO): f76d1c90-e443-4bfc-8f26-7959a7c85c68
           enabled-on-PGPUs ( RO): f76d1c90-e443-4bfc-8f26-7959a7c85c68
    supported-on-GPU-groups ( RO): 134a7b71-5ceb-8066-ef1b-3b319fb2bef3
      enabled-on-GPU-groups ( RO): 134a7b71-5ceb-8066-ef1b-3b319fb2bef3
                 VGPU-uuids ( RO):
               experimental ( RO): false
[root@xenserver ~]#

8.1.3. gpu-group - collection of physical GPUs

A gpu-group is a collection of physical GPUs, all of the same type. Citrix Hypervisor automatically creates gpu-group objects at startup to represent the distinct types of physical GPU present on the platform.

8.1.3.1. Listing the gpu-group Objects Present on a Platform

To list the gpu-group objects present on a platform, use xe gpu-group-list.

For example, a system with a single Tesla P100 card, a single Tesla P40 card, and two Tesla M60 cards contains a single GPU group of type Tesla P100, a single GPU group of type Tesla P40, and two GPU groups of type Tesla M60:

[root@xenserver ~]# xe gpu-group-list
uuid ( RO)                : 3d652a59-beaf-ddb3-3b19-c8c77ef60605
          name-label ( RW): Group of NVIDIA Corporation GP100GL [Tesla P100 PCIe 16GB] GPUs
    name-description ( RW):

uuid ( RO)                : 3df80574-c303-f020-efb3-342f969da5de
          name-label ( RW): 85:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
    name-description ( RW): 85:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)

uuid ( RO)                : 134a7b71-5ceb-8066-ef1b-3b319fb2bef3
          name-label ( RW): 87:00.0 3D controller: NVIDIA Corporation GP102GL [TESLA P40] (rev a1)
    name-description ( RW): 87:00.0 3D controller: NVIDIA Corporation GP102GL [TESLA P40] (rev a1)

uuid ( RO)                : d32560f2-2158-42f9-d201-511691e1cb2b
          name-label ( RW): 86:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
    name-description ( RW): 86:00.0 VGA compatible controller: NVIDIA Corporation GM204GL [Tesla M60] (rev a1)
[root@xenserver ~]#

8.1.3.2. Viewing Detailed Information About a gpu-group Object

To view detailed information about a gpu-group, use xe gpu-group-param-list:

[root@xenserver ~]# xe gpu-group-param-list uuid=134a7b71-5ceb-8066-ef1b-3b319fb2bef3
uuid ( RO)                    : 134a7b71-5ceb-8066-ef1b-3b319fb2bef3
              name-label ( RW): 87:00.0 3D controller: NVIDIA Corporation GP102GL [TESLA P40] (rev a1)
        name-description ( RW): 87:00.0 3D controller: NVIDIA Corporation GP102GL [TESLA P40] (rev a1)
              VGPU-uuids (SRO): 101fb062-427f-1999-9e90-5a914075e9ca
              PGPU-uuids (SRO): f76d1c90-e443-4bfc-8f26-7959a7c85c68
            other-config (MRW):
      enabled-VGPU-types ( RO): d0e4a116-a944-42ef-a8dc-62a54c4d2d77; 9611a3f4-d130-4a66-a61b-21d4a2ca4663; 7ca2399f-89ab-49dd-bf96-75071ced28fc; 25dbb2d3-a074-4f9f-92ce-b42d8b3d1de2; 739d7b8e-50e2-48a1-ae0d-5047aa490f0e; 67fa06ab-554e-452b-a66e-a4048a5bfdf7; 9626e649-6802-4396-976d-94c0ead1f835; 6ea0cd56-526c-4966-8f53-7e1721b95a5c; ad00a95c-d066-4158-b361-487abf57dd30; 88162a34-1151-49d3-98ae-afcd963f3105; 125fbbdf-406e-4d7c-9de8-a7536aa1a838; 4017c9dd-373f-431a-b36f-50e4e5c9f0c0; af121387-0b58-498a-8d04-fe0305e4308f; 5b9acd25-06fa-43e1-8b53-c35bceb8515c; af593219-0800-42da-a51d-d13b35f589e1; 9b2eaba5-565f-4cb4-ad9b-6347cfb03e93; 57bb231f-f61b-408e-a0c0-106bddd91019; d27f84a2-53f8-4430-ad15-0eca225cd974
    supported-VGPU-types ( RO): d0e4a116-a944-42ef-a8dc-62a54c4d2d77; 9611a3f4-d130-4a66-a61b-21d4a2ca4663; 7ca2399f-89ab-49dd-bf96-75071ced28fc; 25dbb2d3-a074-4f9f-92ce-b42d8b3d1de2; 739d7b8e-50e2-48a1-ae0d-5047aa490f0e; 67fa06ab-554e-452b-a66e-a4048a5bfdf7; 9626e649-6802-4396-976d-94c0ead1f835; 6ea0cd56-526c-4966-8f53-7e1721b95a5c; ad00a95c-d066-4158-b361-487abf57dd30; 88162a34-1151-49d3-98ae-afcd963f3105; 125fbbdf-406e-4d7c-9de8-a7536aa1a838; 4017c9dd-373f-431a-b36f-50e4e5c9f0c0; af121387-0b58-498a-8d04-fe0305e4308f; 5b9acd25-06fa-43e1-8b53-c35bceb8515c; af593219-0800-42da-a51d-d13b35f589e1; 9b2eaba5-565f-4cb4-ad9b-6347cfb03e93; 57bb231f-f61b-408e-a0c0-106bddd91019; d27f84a2-53f8-4430-ad15-0eca225cd974
    allocation-algorithm ( RW): depth-first
[root@xenserver ~]

8.1.4. vgpu - Virtual GPU

A vgpu object represents a virtual GPU. Unlike the other GPU management objects, vgpu objects are not created automatically by Citrix Hypervisor. Instead, they are created as follows:

  • When a VM is configured through XenCenter or through xe to use a vGPU
  • By cloning a VM that is configured to use vGPU, as explained in Cloning vGPU-Enabled VMs

8.2. Creating a vGPU using xe

Use xe vgpu-create to create a vgpu object, specifying the type of vGPU required, the GPU group it will be allocated from, and the VM it is associated with:

[root@xenserver ~]# xe vgpu-create vm-uuid=e71afda4-53f4-3a1b-6c92-a364a7f619c2 gpu-group-uuid=be825ba2-01d7-8d51-9780-f82cfaa64924 vgpu-type-uuid=3f318889-7508-c9fd-7134-003d4d05ae56b73cbd30-096f-8a9a-523e-a800062f4ca7
[root@xenserver ~]#

Creating the vgpu object for a VM does not immediately cause a virtual GPU to be created on a physical GPU. Instead, the vgpu object is created whenever its associated VM is started. For more details on how vGPUs are created at VM startup, see Controlling vGPU allocation.

Note:

The owning VM must be in the powered-off state in order for the vgpu-create command to succeed.

A vgpu object’s owning VM, associated GPU group, and vGPU type are fixed at creation and cannot be subsequently changed. To change the type of vGPU allocated to a VM, delete the existing vgpu object and create another one.

8.3. Controlling vGPU allocation

Configuring a VM to use a vGPU in XenCenter, or creating a vgpu object for a VM using xe, does not immediately cause a virtual GPU to be created; rather, the virtual GPU is created at the time the VM is next booted, using the following steps:

  • The GPU group that the vgpu object is associated with is checked for a physical GPU that can host a vGPU of the required type (i.e. the vgpu object’s associated vgpu-type). Because vGPU types cannot be mixed on a single physical GPU, the new vGPU can only be created on a physical GPU that has no vGPUs resident on it, or only vGPUs of the same type, and less than the limit of vGPUs of that type that the physical GPU can support.
  • If no such physical GPUs exist in the group, the vgpu creation fails and the VM startup is aborted.
  • Otherwise, if more than one such physical GPU exists in the group, a physical GPU is selected according to the GPU group’s allocation policy, as described in Modifying GPU Allocation Policy.

8.3.1. Determining the Physical GPU on Which a Virtual GPU is Resident

The vgpu object’s resident-on parameter returns the UUID of the pgpu object for the physical GPU the vGPU is resident on.

To determine the physical GPU that a virtual GPU is resident on, use vgpu-param-get:

[root@xenserver ~]# xe vgpu-param-get uuid=101fb062-427f-1999-9e90-5a914075e9ca param-name=resident-on
f76d1c90-e443-4bfc-8f26-7959a7c85c68

[root@xenserver ~]# xe pgpu-param-list uuid=f76d1c90-e443-4bfc-8f26-7959a7c85c68
uuid ( RO)                        : f76d1c90-e443-4bfc-8f26-7959a7c85c68
                 vendor-name ( RO): NVIDIA Corporation
                 device-name ( RO): GP102GL [Tesla P40]
              gpu-group-uuid ( RW): 134a7b71-5ceb-8066-ef1b-3b319fb2bef3
        gpu-group-name-label ( RO): 87:00.0 3D controller: NVIDIA Corporation GP102GL [TESLA P40] (rev a1)
                   host-uuid ( RO): b55452df-1ee4-4e4e-bd97-3aee97b2123a
             host-name-label ( RO): xs7.1-krish
                      pci-id ( RO): 0000:87:00.0
                dependencies (SRO):
                other-config (MRW):
        supported-VGPU-types ( RO): 5b9acd25-06fa-43e1-8b53-c35bceb8515c; 88162a34-1151-49d3-98ae-afcd963f3105; 9b2eaba5-565f-4cb4-ad9b-6347cfb03e93; 739d7b8e-50e2-48a1-ae0d-5047aa490f0e; d0e4a116-a944-42ef-a8dc-62a54c4d2d77; 7ca2399f-89ab-49dd-bf96-75071ced28fc; 67fa06ab-554e-452b-a66e-a4048a5bfdf7; 9611a3f4-d130-4a66-a61b-21d4a2ca4663; d27f84a2-53f8-4430-ad15-0eca225cd974; 125fbbdf-406e-4d7c-9de8-a7536aa1a838; 4017c9dd-373f-431a-b36f-50e4e5c9f0c0; 6ea0cd56-526c-4966-8f53-7e1721b95a5c; af121387-0b58-498a-8d04-fe0305e4308f; 9626e649-6802-4396-976d-94c0ead1f835; ad00a95c-d066-4158-b361-487abf57dd30; af593219-0800-42da-a51d-d13b35f589e1; 25dbb2d3-a074-4f9f-92ce-b42d8b3d1de2; 57bb231f-f61b-408e-a0c0-106bddd91019
          enabled-VGPU-types (SRW): 5b9acd25-06fa-43e1-8b53-c35bceb8515c; 88162a34-1151-49d3-98ae-afcd963f3105; 9b2eaba5-565f-4cb4-ad9b-6347cfb03e93; 739d7b8e-50e2-48a1-ae0d-5047aa490f0e; d0e4a116-a944-42ef-a8dc-62a54c4d2d77; 7ca2399f-89ab-49dd-bf96-75071ced28fc; 67fa06ab-554e-452b-a66e-a4048a5bfdf7; 9611a3f4-d130-4a66-a61b-21d4a2ca4663; d27f84a2-53f8-4430-ad15-0eca225cd974; 125fbbdf-406e-4d7c-9de8-a7536aa1a838; 4017c9dd-373f-431a-b36f-50e4e5c9f0c0; 6ea0cd56-526c-4966-8f53-7e1721b95a5c; af121387-0b58-498a-8d04-fe0305e4308f; 9626e649-6802-4396-976d-94c0ead1f835; ad00a95c-d066-4158-b361-487abf57dd30; af593219-0800-42da-a51d-d13b35f589e1; 25dbb2d3-a074-4f9f-92ce-b42d8b3d1de2; 57bb231f-f61b-408e-a0c0-106bddd91019
              resident-VGPUs ( RO): 101fb062-427f-1999-9e90-5a914075e9ca
[root@xenserver ~]#
Note: If the vGPU is not currently running, the resident-on parameter is not instantiated for the vGPU, and the vgpu-param-get operation returns:
<not in database>

8.3.2. Controlling the vGPU types enabled on specific physical GPUs

Physical GPUs support several vGPU types, as defined in Supported GPUs and the “pass-through” type that is used to assign an entire physical GPU to a VM (see Using GPU Pass-Through on Citrix Hypervisor).

8.3.2.1. Controlling vGPU types enabled on specific physical GPUs by using XenCenter

To limit the types of vGPU that may be created on a specific physical GPU:
  1. Open the server’s GPU tab in XenCenter.
  2. Select the box beside one or more GPUs on which you want to limit the types of vGPU.
  3. Select Edit Selected GPUs.
    Figure 30. Editing a GPU’s enabled vGPU types using XenCenter

    Screen capture showing how to edit a GPU’s enabled vGPU types using XenCenter

8.3.2.2. Controlling vGPU Types Enabled on Specific Physical GPUs by Using xe

The physical GPU’s pgpu object’s enabled-vGPU-types parameter controls the vGPU types enabled on specific physical GPUs.

To modify the pgpu object’s enabled-vGPU-types parameter , use xe pgpu-param-set:

[root@xenserver ~]# xe pgpu-param-list uuid=cb08aaae-8e5a-47cb-888e-60dcc73c01d3
uuid ( RO)	                : cb08aaae-8e5a-47cb-888e-60dcc73c01d3
             vendor-name ( RO): NVIDIA Corporation
			 device-name ( RO): GP102GL [Tesla P40]
             domO-access ( RO): enabled
is-system-display-device ( RO): false
          gpu-group-uuid ( RW): bfel603d-c526-05f3-e64f-951485ef3b49
	gpu-group-name-label ( RO): 87:00.0 3D controller: NVIDIA Corporation GP102GL [Tesla P40] (rev al)
	           host-uuid ( RO): fdeb6bbb-e460-4cfl-ad43-49ac81c20540
		 host-name-label ( RO): xs-72
                  pci-id ( RO): 0000:87:00.0
			dependencies (SRO): 
			other-config (MRW):
    supported-VGPU-types ( RO): 23e6b80b-le5e-4c33-bedb-e6dlae472fec; f5583e39-2540-440d-a0ee-dde9f0783abf; al8e46ff-4d05-4322-b040-667ce77d78a8; adell9a9-84el-435f-b0e9-14cl62e212fb; 2560d066-054a-48a9-a44d-3f3f90493a00; 47858f38-045d-4a05-9blc-9128fee6b0ab; Ifb527f6-493f-442b-abe2-94a6fafd49ce; 78b8e044-09ae-4a4c-8a96-b20c7a585842; 18ed7e7e-f8b7-496e-9784-8ba4e35acaa3; 48681d88-c4e5-4e39-85ff-c9bal2e8e484 ; cc3dbbfb-4b83-400d-8c52-811948b7f8c4; 8elad75a-ed5f-4609-83ff-5f9bca9aaca2; 840389a0-f511-4f90-8153-8a749d85b09e; a2042742-da67-4613-a538-ldl7d30dccb9; 299e47c2-8fcl-4edf-aa31-e29db84168c6; e95c636e-06e6-4 47e-8b49-14b37d308922; 0524a5d0-7160-48c5-a9el-cc33e76dc0de; 09043fb2-6d67-4443-b312-25688f13e012
      enabled-VGPU-types (SRW): 23e6b80b-le5e-4c33-bedb-e6dlae472fec; f5583e39-2540-440d-a0ee-dde9f0783abf; al8e46ff-4d05-4322-b040-667ce77d78a8; adell9a9-84el-435f-b0e9-14cl62e212fb; 2560d066-054a-48a9-a44d-3f3f90493a00; 47858f38-045d-4a05-9blc-9128fee6b0ab; Ifb527f6-493f-442b-abe2-94a6fafd49ce; 78b8e044-09ae-4a4c-8a96-b20c7a585842; 18ed7e7e-f8b7-496e-9784-8ba4e35acaa3; 48681d88-c4e5-4e39-85ff-c9bal2e8e484 ; cc3dbbfb-4b83-400d-8c52-811948b7f8c4; 8elad75a-ed5f-4609-83ff-5f9bca9aaca2; 840389a0-f511-4f90-8153-8a749d85b09e; a2042742-da67-4613-a538-ldl7d30dccb9; 299e47c2-8fcl-4edf-aa31-e29db84168c6; e95c636e-06e6-4 47e-8b49-14b37d308922; 0524a5d0-7160-48c5-a9el-cc33e76dc0de; 09043fb2-6d67-4443-b312-25688f13e012
	      resident-VGPUs ( RO):

[root@xenserver-vgx-test ~]#  xe pgpu-param-set uuid=cb08aaae-8e5a-47cb-888e-60dcc73c01d3 enabled-VGPU-types=23e6b80b-le5e-4c33-bedb-e6dlae472fec
      

8.3.3. Creating vGPUs on Specific Physical GPUs

To precisely control allocation of vGPUs on specific physical GPUs, create separate GPU groups for the physical GPUs you wish to allocate vGPUs on. When creating a virtual GPU, create it on the GPU group containing the physical GPU you want it to be allocated on.

For example, to create a new GPU group for the physical GPU at PCI bus ID 0000:87:00.0, follow these steps:

  1. Create the new GPU group with an appropriate name:
    [root@xenserver ~]# xe gpu-group-create name-label="GRID P40 87:0.0" 3f870244-41da-469f-71f3-22bc6d700e71
    [root@xenserver ~]#
  2. Find the UUID of the physical GPU at 0000:87:0.0 that you want to assign to the new GPU group:
    [root@xenserver ~]# xe pgpu-list pci-id=0000:87:00.0
    uuid ( RO)              : f76d1c90-e443-4bfc-8f26-7959a7c85c68
           vendor-name ( RO): NVIDIA Corporation
           device-name ( RO): GP102GL [Tesla P40]
        gpu-group-uuid ( RW): 134a7b71-5ceb-8066-ef1b-3b319fb2bef3
    [root@xenserver ~]
    Note: The pci-id parameter passed to the pgpu-list command must be in the exact format shown, with the PCI domain fully specified (for example, 0000) and the PCI bus and devices numbers each being two digits (for example, 87:00.0).
  3. Ensure that no vGPUs are currently operating on the physical GPU by checking the resident-VGPUs parameter:
    [root@xenserver ~]# xe pgpu-param-get uuid=f76d1c90-e443-4bfc-8f26-7959a7c85c68 param-name=resident-VGPUs
    [root@xenserver ~]#
  4. If any vGPUs are listed, shut down the VMs associated with them.
  5. Change the gpu-group-uuid parameter of the physical GPU to the UUID of the newly-created GPU group:
    [root@xenserver ~]# xe pgpu-param-set uuid=7c1e3cff-1429-0544-df3d-bf8a086fb70a gpu-group-uuid=585877ef-5a6c-66af-fc56-7bd525bdc2f6
    [root@xenserver ~]#

Any vgpu object now created that specifies this GPU group UUID will always have its vGPUs created on the GPU at PCI bus ID 0000:05:0.0.

Note: You can add more than one physical GPU to a manually-created GPU group – for example, to represent all the GPUs attached to the same CPU socket in a multi-socket server platform - but as for automatically-created GPU groups, all the physical GPUs in the group must be of the same type.

In XenCenter, manually-created GPU groups appear in the GPU type listing in a VM’s GPU Properties. Select a GPU type within the group from which you wish the vGPU to be allocated:

Figure 31. Using a custom GPU group within XenCenter

Screen capture showing how to use a custom GPU group in XenCenter

8.4. Cloning vGPU-Enabled VMs

The fast-clone or copying feature of Citrix Hypervisor can be used to rapidly create new VMs from a “golden” base VM image that has been configured with NVIDIA vGPU, the NVIDIA driver, applications, and remote graphics software.

When a VM is cloned, any vGPU configuration associated with the base VM is copied to the cloned VM. Starting the cloned VM will create a vGPU instance of the same type as the original VM, from the same GPU group as the original vGPU.

8.4.1. Cloning a vGPU-enabled VM by using xe

To clone a vGPU-enabled VM from the dom0 shell, use vm-clone:

[root@xenserver ~]# xe vm-clone new-name-label="new-vm" vm="base-vm-name" 7f7035cb-388d-1537-1465-1857fb6498e7
[root@xenserver ~]#

8.4.2. Cloning a vGPU-enabled VM by using XenCenter

To clone a vGPU-enabled VM by using XenCenter, use the VM’s Copy VM command as shown in Figure 32.
Figure 32. Cloning a VM using XenCenter

Screen capture showing how to clone a VM by using XenCenter

9. Citrix Hypervisor Performance Tuning

This chapter provides recommendations on optimizing performance for VMs running with NVIDIA vGPU on Citrix Hypervisor.

9.1. Citrix Hypervisor Tools

To get maximum performance out of a VM running on Citrix Hypervisor, regardless of whether you are using NVIDIA vGPU, you must install Citrix Hypervisor tools within the VM. Without the optimized networking and storage drivers that the Citrix Hypervisor tools provide, remote graphics applications running on NVIDIA vGPU will not deliver maximum performance.

9.2. Using Remote Graphics

NVIDIA vGPU implements a console VGA interface that permits the VM’s graphics output to be viewed through XenCenter’s console tab. This feature allows the desktop of a vGPU-enabled VM to be visible in XenCenter before any NVIDIA graphics driver is loaded in the virtual machine, but it is intended solely as a management convenience; it only supports output of vGPU’s primary display and isn’t designed or optimized to deliver high frame rates.

To deliver high frames from multiple heads on vGPU, NVIDIA recommends that you install a high-performance remote graphics stack such as Citrix Virtual Apps and Desktops with HDX 3D Pro remote graphics and, after the stack is installed, disable vGPU’s console VGA.

CAUTION:
Using Windows Remote Desktop (RDP) to access Windows 7 or Windows Server 2008 VMs running NVIDIA vGPU will cause the NVIDIA driver in the VM to be unloaded. GPU-accelerated DirectX, OpenGL, and the NVIDIA control panel will be unavailable whenever RDP is active. Installing a VNC server in the VM will allow for basic, low-performance remote access while leaving the NVIDIA driver loaded and vGPU active, but for high performance remote accesses, use an accelerated stack such as Citrix Virtual Apps and Desktops.

9.2.1. Disabling console VGA

The console VGA interface in vGPU is optimized to consume minimal resources, but when a system is loaded with a high number of VMs, disabling the console VGA interface entirely may yield some performance benefit.

Once you have installed an alternate means of accessing a VM (such as Citrix Virtual Apps and Desktops or a VNC server), its vGPU console VGA interface can be disabled by specifying disable_vnc=1 in the VM’s platform:vgpu_extra_args parameter:

[root@xenserver ~]# xe vm-param-set uuid=e71afda4-53f4-3a1b-6c92-a364a7f619c2 platform:vgpu_extra_args="disable_vnc=1"
[root@xenserver ~]#

The new console VGA setting takes effect the next time the VM is started or rebooted. With console VGA disabled, the XenCenter console will display the Windows boot splash screen for the VM, but nothing beyond that.

CAUTION:

If you disable console VGA before you have installed or enabled an alternate mechanism to access the VM (such as Citrix Virtual Apps and Desktops), you will not be able to interact with the VM once it has booted.

You can recover console VGA access by making one of the following changes:

  • Removing the vgpu_extra_args key from the platform parameter
  • Removing disable_vnc=1 from the vgpu_extra_args key
  • Setting disable_vnc=0, for example:
    [root@xenserver ~]# xe vm-param-set uuid=e71afda4-53f4-3a1b-6c92-a364a7f619c2 platform:vgpu_extra_args="disable_vnc=0"

9.3. Allocation Strategies

Strategies for pinning VM CPU cores to physical cores on Non-Uniform Memory Access (NUMA) platforms and for allocating VMs to CPUs and vGPUs to physical GPUs can improve performance for VMs running with NVIDIA vGPU.

9.3.1. NUMA considerations

Server platforms typically implement multiple CPU sockets, with system memory and PCI Express expansion slots local to each CPU socket, as illustrated in Figure 33:

Figure 33. A NUMA server platform

Diagrm showing a Non-Uniform Memory Access (NUMA) server platform in which physical memory is attached to two CPU sockets and two GPUs connect over PCIe to each CPU socket

These platforms are typically configured to operate in Non-Uniform Memory Access (NUMA) mode; physical memory is arranged sequentially in the address space, with all the memory attached to each socket appearing in a single contiguous block of addresses. The cost of accessing a range of memory from a CPU or GPU varies; memory attached to the same socket as the CPU or GPU is accessible at lower latency than memory on another CPU socket, because accesses to remote memory must additionally traverse the interconnect between CPU sockets.

To obtain best performance on a NUMA platform, NVIDIA recommends pinning VM vCPU cores to physical cores on the same CPU socket to which the physical GPU hosting the VM’s vGPU is attached. For example, using as a reference, a VM with a vGPU allocated on physical GPU 0 or 1 should have its vCPUs pinned to CPU cores on CPU socket 0. Similarly, a VM with a vGPU allocated on physical GPU 2 or 3 should have its vCPUs pinned to CPU cores on socket 1.

See Pinning VMs to a specific CPU socket and cores for guidance on pinning vCPUs, and How GPU locality is determined for guidance on determining which CPU socket a GPU is connected to. Controlling the vGPU types enabled on specific physical GPUs describes how to precisely control which physical GPU is used to host a vGPU, by creating GPU groups for specific physical GPUs.

9.3.2. Maximizing performance

To maximize performance as the number of vGPU-enabled VMs on the platform increases, NVIDIA recommends adopting a breadth-first allocation: allocate new VMs on the least-loaded CPU socket, and allocate the VM’s vGPU on an available, least-loaded, physical GPU connected via that socket.

Citrix Hypervisor creates GPU groups with a default allocation policy of depth-first. See Modifying GPU Allocation Policy on Citrix Hypervisor for details on switching the allocation policy to breadth-first.

Note: Due to vGPU’s requirement that only one type of vGPU can run on a physical GPU at any given time, not all physical GPUs may be available to host the vGPU type required by the new VM.

10. Troubleshooting

This chapter describes basic troubleshooting steps for NVIDIA vGPU on Citrix Hypervisor, Red Hat Enterprise Linux KVM, Red Hat Virtualization (RHV), and VMware vSphere, and how to collect debug information when filing a bug report.

10.1. Known issues

Before troubleshooting or filing a bug report, review the release notes that accompany each driver release, for information about known issues with the current release, and potential workarounds.

10.2. Troubleshooting steps

If a vGPU-enabled VM fails to start, or doesn’t display any output when it does start, follow these steps to narrow down the probable cause.

10.2.1. Verifying the NVIDIA Kernel Driver Is Loaded

  1. Use the command that your hypervisor provides to verify that the kernel driver is loaded:
    • On Citrix Hypervisor, Red Hat Enterprise Linux KVM, and RHV, use lsmod:
      [root@xenserver ~]# lsmod|grep nvidia
      nvidia               9604895  84
      i2c_core               20294  2 nvidia,i2c_i801
      [root@xenserver ~]#
    • On VMware vSphere, use vmkload_mod:
      [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 (see Examining NVIDIA kernel driver output).
  3. On Citrix Hypervisor, Red Hat Enterprise Linux KVM, and RHV, also use the rpm -q command to verify that the NVIDIA GPU Manager package is correctly installed.
    rpm -q vgpu-manager-rpm-package-name
    vgpu-manager-rpm-package-name
    The RPM package name of the NVIDIA GPU Manager package, for example NVIDIA-vGPU-xenserver-7.0-430.46 for Citrix Hypervisor.

    This example verifies that the NVIDIA GPU Manager package for Citrix Hypervisor is correctly installed.

    [root@xenserver ~]# rpm –q NVIDIA-vGPU-xenserver-7.0-430.46
    [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-xenserver-7.0-430.46.x86_64 conflicts with file from package NVIDIA-vGPU-xenserver-7.0-430.27.x86_64
            file /usr/lib/libnvidia-ml.so from install of NVIDIA-vGPU-xenserver-7.0-430.46.x86_64 conflicts with file from package NVIDIA-vGPU-xenserver-7.0-430.27.x86_64
            ...

10.2.2. Verifying that nvidia-smi works

If the NVIDIA kernel driver is correctly loaded on the physical GPU, run nvidia-smi and verify that all physical GPUs not currently being used for GPU past-through are listed in the output. For details on expected output, see NVIDIA System Management Interface nvidia-smi.

If nvidia-smi fails to report the expected output, check dmesg for NVIDIA kernel driver messages.

10.2.3. Examining NVIDIA kernel driver output

Information and debug messages from the NVIDIA kernel driver are logged in kernel logs, prefixed with NVRM or nvidia.

Run dmesg on Citrix Hypervisor, Red Hat Enterprise Linux KVM, RHV, and VMware vSphere and check for the NVRM and nvidia prefixes:

[root@xenserver ~]# dmesg | grep -E "NVRM|nvidia"
[   22.054928] nvidia: module license 'NVIDIA' taints kernel.
[   22.390414] NVRM: loading
[   22.829226] nvidia 0000:04:00.0: enabling device (0000 -> 0003)
[   22.829236] nvidia 0000:04:00.0: PCI INT A -> GSI 32 (level, low) -> IRQ 32
[   22.829240] NVRM: This PCI I/O region assigned to your NVIDIA device is invalid:
[   22.829241] NVRM: BAR0 is 0M @ 0x0 (PCI:0000:00:04.0)
[   22.829243] NVRM: The system BIOS may have misconfigured your GPU.

10.2.4. Examining NVIDIA Virtual GPU Manager Messages

Information and debug messages from the NVIDIA Virtual GPU Manager are logged to the hypervisor’s log file