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Perform this task in the VMware vSphere web client by using the Migration wizard. Create each compute instance individually by running the following command. This example creates a MIG 2g. This example confirms that a MIG 2g.

This example confirms that two MIG 1c. Unified memory is disabled by default. If used, you must enable unified memory individually for each vGPU that requires it by setting a vGPU plugin parameter. How to enable unified memory for a vGPU depends on the hypervisor that you are using. On VMware vSphere, enable unified memory by setting the pciPassthru vgpu-id. In advanced VM attributes, set the pciPassthru vgpu-id.

The setting of this parameter is preserved after a guest VM is restarted and after the hypervisor host is restarted. The setting of this parameter is preserved after a guest VM is restarted.

However, this parameter is reset to its default value after the hypervisor host is restarted. By default, only GPU workload trace is enabled. Clocks are locked automatically when profiling starts and are unlocked automatically when profiling ends. The nvidia-smi tool is included in the following packages:. The scope of the reported management information depends on where you run nvidia-smi from:. 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. 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. 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.

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. 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.

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

To monitor the encoder sessions for processes running on multiple vGPUs, run nvidia-smi vgpu with the —es or --encodersessions option. To monitor the FBC sessions for processes running on multiple vGPUs, run nvidia-smi vgpu with the -fs or --fbcsessions option. 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. To view detailed information about the supported vGPU types, add the —v or --verbose option:. 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.

To view detailed information about the vGPU types that can currently be created, add the —v or --verbose option. 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. In guest VMs, 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:.

To use nvidia-smi to retrieve statistics for the total resource usage by all applications running in the VM, run the following command:. The following example shows the result of running nvidia-smi dmon from within a Windows guest VM.

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

Any WMI-enabled application can access these metrics. Under some circumstances, a VM running a graphics-intensive application may adversely affect the performance of graphics-light applications running in other VMs. These schedulers impose a limit on GPU processing cycles used by a vGPU, which prevents graphics-intensive applications running in one VM from affecting the performance of graphics-light applications running in other VMs.

You can also set the length of the time slice for the equal share and fixed share vGPU schedulers. The best effort scheduler is the default scheduler for all supported GPU architectures. For the equal share and fixed share vGPU schedulers, you can set the length of the time slice.

The length of the time slice affects latency and throughput. The optimal length of the time slice depends the workload that the GPU is handling. For workloads that require low latency, a shorter time slice is optimal. Typically, these workloads are applications that must generate output at a fixed interval, such as graphics applications that generate output at a frame rate of 60 FPS.

These workloads are sensitive to latency and should be allowed to run at least once per interval. A shorter time slice reduces latency and improves responsiveness by causing the scheduler to switch more frequently between VMs. If TT is greater than 1E, the length is set to 30 ms. This example sets the vGPU scheduler to equal share scheduler with the default time slice length.

This example sets the vGPU scheduler to equal share scheduler with a time slice that is 3 ms long. This example sets the vGPU scheduler to fixed share scheduler with the default time slice length.

This example sets the vGPU scheduler to fixed share scheduler with a time slice that is 24 0x18 ms long. Get the current scheduling behavior before changing the scheduling behavior of one or more GPUs to determine if you need to change it or after changing it to confirm the change.

The scheduling behavior is indicated in these messages by the following strings:. If the scheduling behavior is equal share or fixed share, the scheduler time slice in ms is also displayed.

The value that sets the GPU scheduling policy and the length of the time slice that you want, for example:. 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. Look in the vmware. When filing a bug report with NVIDIA, capture relevant configuration data from the platform exhibiting the bug in one of the following ways:.

The nvidia-bug-report. Run nvidia-bug-report. This example runs nvidia-bug-report. These vGPU types support a maximum combined resolution based on the number of available pixels, which is determined by their frame buffer size. You can choose between using a small number of high resolution displays or a larger number of lower resolution displays with these vGPU types.

The maximum number of displays per vGPU is based on a configuration in which all displays have the same resolution. GPU Pass-Through. Bare-Metal Deployment. Additional vWS Features. How this Guide Is Organized. Windows Guest VM Support. Linux Guest VM support. Since Configuring a Licensed Client on Windows.

Configuring a Licensed Client on Linux. Monitoring GPU Performance. Getting vGPU Details. Monitoring vGPU engine usage. Monitoring vGPU engine usage by applications. Monitoring Encoder Sessions. Troubleshooting steps.

Verifying that nvidia-smi works. Capturing configuration data for filing a bug report. Capturing configuration data by running nvidia-bug-report. Allocation Strategies. Maximizing Performance. Configuring the Xorg Server on the Linux Server.

Installing and Configuring x11vnc on the Linux Server. Opening a dom0 shell. Accessing the dom0 shell through XenCenter.

Accessing the dom0 shell through an SSH client. Copying files to dom0. Copying files by using an SCP client. Copying files by using a CIFS-mounted file system. Changing dom0 vCPU Default configuration. Changing the number of dom0 vCPUs. Pinning dom0 vCPUs. How GPU locality is determined. Management objects for GPUs. Listing the pgpu Objects Present on a Platform.

Viewing Detailed Information About a pgpu Object. Listing the vgpu-type Objects Present on a Platform. Viewing Detailed Information About a vgpu-type Object. Listing the gpu-group Objects Present on a Platform. Viewing Detailed Information About a gpu-group Object.

Creating a vGPU Using xe. Controlling vGPU allocation. Citrix Hypervisor Performance Tuning. Citrix Hypervisor Tools. Using Remote Graphics. Disabling Console VGA. Configure the platform for remote access. Note: Citrix Hypervisor provides a specific setting to allow the primary display adapter to be used for GPU pass through deployments. Figure 1. These tools are supported only in Linux guest VMs.

Note: Unified memory is disabled by default. Additional vWS Features In addition to the features of vPC and vApps , vWS provides the following features: Workstation-specific graphics features and accelerations Certified drivers for professional applications GPU pass through for workstation or professional 3D graphics In pass-through mode, vWS supports multiple virtual display heads at resolutions up to 8K and flexible virtual display resolutions based on the number of available pixels.

The Ubuntu guest operating system is supported. Troubleshooting provides guidance on troubleshooting. Figure 2. Figure 3. Figure 4. Tyler Technologies. DTE Energy. Citizens Financial. MGM Resorts International. Teledyne Technologies. Raymond James Financial. Broadridge Financial Solutions.

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