Create a virtual GPU-accelerated Linux workstation

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This tutorial shows how to create a virtual Linux workstation running Ubuntu 22.04 with an attached display-capable GPU. Google Cloud offers four display-capable GPUs: NVIDIA L4, NVIDIA T4, NVIDIA P4, and NVIDIA P100.

To create a Windows workstation, see the tutorial for Creating a virtual GPU accelerated Windows workstation.

Note: This tutorial helps you create a virtual workstation that can take advantage of hardware graphics acceleration. For information about other types of virtual workstations that you can create on Google Cloud, see Creating a virtual workstation.

After you create the virtual workstation, you learn how to remotely access it using HP Anyware (formerly Teradici CAS), using PC-over-IP (PCoIP®) technology, a remote desktop protocol widely used in the media and entertainment, game development, architecture, and engineering industries. PCoIP offers features essential to these types of workloads, such as color accuracy, support for multiple monitors, lossless display, and tablet pressure sensitivity.

This tutorial assumes you are familiar with the Linux command line.

Objectives

• Create a Compute Engine instance with a GPU. This instance serves as the foundation for a virtual workstation.
• Install NVIDIA drivers on the virtual workstation.
• Install HP Anyware software on the virtual workstation.
• Connect to the virtual workstation using a PCoIP software client.

Note: This tutorial does not include advanced security features such as fine-grained SSH key management, certificate issuance, or multi-factor authentication (MFA). A full deployment requires a connection broker and domain controller, which help enable a stronger security profile for connecting to virtual workstations.

Costs

This tutorial uses the following billable component of Google Cloud:

• Compute Engine

You can use the pricing calculator to generate a cost estimate based on your projected usage.

The resources that make up the virtual workstation and the factors that affect cost in this tutorial are:

• 8 vCPUs, 32 GB RAM G2 standard machine type which includes an NVIDIA L4 Virtual Workstation GPU.
• 100 GB SSD persistent boot disk
• Internet outbound data transfer costs

Internet data transfer represents data that streams from your virtual workstation to your local display client and is billed at internet outbound data transfer costs. Variables that affect data transfer during a PCoIP session are bandwidth, screen resolution, number of display monitors, applications used, and the type of activity on each monitor. The HP Anyware Session Planning Guide can help you understand different workload requirements.

Note: Costs differ depending on region and connection method. These estimated costs are based on connection over the public internet, with resources located in the us-central1 region (Iowa).

Before you begin

This tutorial uses the Google Cloud CLI, which you can run from a Cloud Shell instance launched from the Google Cloud console . If you want to use gcloud CLI on your local workstation, install the Google Cloud CLI. The tutorial shows you how to run commands in Cloud Shell; if you use the gcloud CLI on your workstation, adjust the instructions accordingly.

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

3. Make sure that billing is enabled for your Google Cloud project.

4. Enable the Compute Engine API.

   Enable the API

5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

6. Make sure that billing is enabled for your Google Cloud project.

7. Enable the Compute Engine API.

   Enable the API

In addition, make sure you have the following:

• A Google Cloud project with quota for NVIDIA L4 Virtual Workstation GPUs in your selected zone. You can get a listing of GPU availability using the gcloud compute accelerator-types list command.
• A Google Chrome browser to access the Google Cloud console.
• The latest PCoIP Client software for Windows, Mac, or Linux to access the virtual workstation.
• An account on help.teradici.com to download the HP Anyware software. Account registration is free.
• An HP Anyware software license. You can request a trial license, or contact your HP representative and ask for a trial registration code to use for this virtual workstation.

Architecture

The following diagram shows the components used in this tutorial to deploy a single virtual workstation. Optional components shown in the diagram include different ways to connect to your virtual workstation, shared storage, an additional instance for serving third-party licenses, and additional infrastructure representing a render or compute farm.

Choose a region

An important factor when you deploy a virtual workstation is the latency between your location and the instance you create. The lower the latency, the better the experience. Therefore, you want to work in a region that's geographically closest to you. To learn more about where the different GPUs are available, see GPU regions and zones availability.

1. Open Cloud Shell. (If you're using the gcloud CLI, open a terminal window on your computer.)

   Go to Cloud Shell

2. Get a list of the zones in which GPUs are available:

   gcloud compute accelerator-types list

   Take note of the region and zone that's physically closest to you.

3. Set the zone that you want to work with:

   gcloud config set compute/zone ZONE

   Replace ZONE with the name of the zone you're using, such as us-west1-b.

Choose a machine type

NVIDIA L4 GPUs are attached to the G2 machine type. Virtual machines with one or more GPUs have a maximum number of vCPUs for each GPU you add to the instance. For example, each NVIDIA L4 GPU lets you have up to 32 vCPUs and up to 128 GB of memory in your instance machine type. To see the available vCPU and memory ranges for different GPU configurations, see the GPUs list.

The example in this tutorial consists of an 8 vCPU G2 virtual workstation, which is well under the limit of 32 vCPUs for a single NVIDIA L4 GPU.

Create the virtual workstation

Note: There are some restrictions to keep in mind when creating a virtual workstation with attached GPUs. Restrictions that apply to this tutorial have been addressed, but it's a good idea to familiarize yourself with these restrictions before you create your virtual workstation.

1. In Cloud Shell, create the Compute Engine virtual workstation instance:

   gcloud compute instances create VM_NAME \
       --zone=ZONE \
       --machine-type=MACHINE_TYPE \
       --accelerator=type=ACCELERATOR,count=NUM-GPUS \
       --maintenance-policy="TERMINATE" \
       --image-project=ubuntu-os-cloud \
       --image-family=ubuntu-2204-lts \
       --boot-disk-size=SIZE \
       --boot-disk-type=TYPE \
       --network=NETWORK
   

   Replace the following:

   • VM_NAME is the name of your workstation.
   • ZONE is the zone in which to create the VM.
   • MACHINE_TYPE is the predefined or custom machine configuration.
   • ACCELERATOR is the type of GPU you want to attach, such as nvidia-l4-vws.
   • NUM-GPUS is the number of GPUs to attach to the VM.
   • SIZE is the size of the boot disk, in gigabytes.
   • TYPE is the type of boot disk. To get a list of available disk types, run gcloud compute disk-types list.
   • NETWORK is the network in which to create the VM.

   For example:

   gcloud compute instances create test-workstation \
       --zone=us-west1-b \
       --machine-type=g2-standard-8 \
       --accelerator=type=nvidia-l4-vws,count=1 \
       --maintenance-policy="TERMINATE" \
       --image-project=ubuntu-os-cloud \
       --image-family=ubuntu-2204-lts \
       --boot-disk-size=100 \
       --boot-disk-type=pd-ssd \
       --network=default
   

   After the virtual workstation is created, the machine status is displayed. The output looks similar to the following:

   NAME: test-workstation
   ZONE: us-west1-b
   MACHINE_TYPE: g2-standard-8
   PREEMPTIBLE:
   INTERNAL_IP: 10.138.XX.XXX
   EXTERNAL_IP: XX.XXX.XXX.XXX
   STATUS: RUNNING
   

   Note the virtual workstation's external IP address. You will use it later in the tutorial.

   You can retrieve the external IP address of your virtual workstation at any time using the Google Cloud console.

Sign in to your virtual workstation

After you create the virtual workstation, you sign in to the machine so that you can configure it.

1. In Cloud Shell, connect to the new virtual workstation:

   gcloud compute ssh VM_NAME

2. Set your account password. Logging into a virtual workstation using the PCoIP software client requires a user password.

   sudo passwd `whoami`

   When you're prompted, enter a password. You will use this password later in the tutorial to log on to your virtual workstation with the HP Anyware PCoIP Client.

Install the base libraries

The default Google Cloud Ubuntu 22.04 image is a minimal installation of Ubuntu. The next step is to install libraries that are necessary to run your virtual workstation as a graphics workstation.

1. Update the software repositories:

   sudo apt update

2. Install the base components:

   sudo apt install -y build-essential
   sudo apt install -y libvulkan1
   

3. Update the gcc version for the NVIDIA driver:

   sudo apt install -y gcc-12
   sudo apt install -y linux-headers-$(uname -r)
   sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 12
   sudo update-alternatives --config gcc
   

Install the NVIDIA driver

NVIDIA L4, NVIDIA T4, NVIDIA P4, and NVIDIA P100 GPUs work on Google Cloud only with qualified NVIDIA RTX Virtual Workstation drivers for visualization workloads. These drivers can be downloaded from a public Google Cloud storage bucket.

1. To install the latest NVIDIA RTX Virtual Workstation driver, follow the instructions (Steps 3 and 4, only).

2. Reboot the workstation:

   sudo reboot

Install the desktop environment

A desktop environment is necessary to run your virtual workstation as a graphics workstation. For this tutorial, you install the KDE Plasma Desktop.

1. Install the desktop environment:

   sudo apt update
   sudo apt -y install kubuntu-desktop
   sudo apt -y install dialog
   

2. Reboot the workstation:

   sudo reboot

Install HP Anyware software

HP Anyware software provides a graphics agent that runs on your virtual workstation, delivering the desktop to your hardware or software client.

Note: Installation may differ if you choose a different Linux distribution. For more information, see HP Anyware Graphics Agent for Linux Installation Guide.

1. When the virtual workstation has restarted, in Cloud Shell, reconnect to the virtual workstation:

   gcloud compute ssh VM_NAME

2. Add the Teradici software repository:

   curl -1sLf \
       https://dl.anyware.hp.com/TOKEN/pcoip-agent/cfg/setup/bash.deb.sh \
       | sudo -E distro=ubuntu codename=jammy bash
   

   Replace the following:

   • TOKEN is the download token you can retrieve from the HP Anyware Graphics Agent for Linux page under Downloads and scripts.

3. Update the software repositories:

   sudo apt update

4. Optional: Install USB dependencies, if you need to support USB devices other than keyboards, mice, and pointer devices.

   Note: If you skip this step, USB redirection is disabled. That means you can't use bridged USB devices.

   sudo apt -y install usb-vhci-dkms

5. Install the HP Anyware software:

   sudo apt -y install pcoip-agent-graphics

Register the Anyware Graphics Agent

To use the Anyware Graphics Agent, you must have an HP Anyware license.

1. In Cloud Shell, activate your HP Anyware software license:

   pcoip-register-host --registration-code=REGISTRATION-CODE

   Replace REGISTRATION-CODE with the code provided to you by HP Teradici in the form ABCDEFGHIJKL@0123-4567-89AB-CDEF.

2. Reboot the virtual workstation:

   sudo reboot

Create a firewall rule

The PCoIP client communicates with your virtual workstation using several ports. You must set firewall rules that allow traffic to your virtual workstation.

• In Cloud Shell (not on the virtual workstation), create a firewall rule that opens the required ports:

  gcloud compute firewall-rules create allow-pcoip \
      --action=ALLOW \
      --rules=tcp:443,tcp:4172,udp:4172 \
      --source-ranges=0.0.0.0/0
  

  Note: This firewall rule allows traffic from anywhere on the internet to access your VM instance. Always follow best practices for firewall rules to restrict traffic to your instance.

Sign in to your virtual workstation using the PCoIP client

1. On your local computer, go to the PCoIP Clients section on the HP Anyware support page, and then download, install, and launch the PCoIP Software Client application for your operating system.

2. In the Host Address or Registration Code field, enter the external IP address of your virtual workstation. If you want, you can enter a name for the connection.

   Note: By default, PCoIP traffic is encrypted using AES-256. However, HP Anyware Software uses a self-signed certificate that's issued by Teradici. This might trigger a verification warning when you connect. You can remove this warning by creating and installing your own custom security certificates. Or, you can suppress the warning by changing the client security mode for your client OS. For the purposes of this tutorial, you can ignore this warning by clicking Connect Insecurely in the dialog.

3. When you are connected, authenticate by entering the username and password that you created earlier for the virtual workstation.

   In a few seconds, your Linux desktop appears.

Test your virtual workstation

After you've deployed your virtual workstation, you can test performance and interactivity using a number of tools:

• Run GPU benchmark tools, such as glxgears, glmark2, or UNIGINE, which are programs to test graphics performance on a Linux workstation.
• Install Unreal Engine, Unity Editor, Blender, or any content creation application.
• Run render benchmarking tools for popular renderers such as V-Ray, Octane, or Maxon.
• Use Google Chrome to browse your favorite sites or play YouTube videos.

You can also learn more about PCoIP performance optimization based on your workload.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used in this tutorial, either delete the project that contains the resources, or keep the project and delete the individual resources.

After you've finished the tutorial, clean up the resources you created on Google Cloud so you won't be billed for them in the future.

Stop your virtual workstation

Stopped virtual workstations incur costs for persistent disk, but can be restarted at any time. To stop your virtual workstation, run the following command in Cloud Shell:

gcloud compute instances stop VM_NAME

Delete all the components

1. Delete the virtual workstation.
2. Delete the firewall rule.

Delete the project

Caution: Deleting a project has the following effects:
• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.
1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

What's next

• Learn how to create a virtual GPU-accelerated Windows workstation.
• Learn more about NVIDIA RTX Virtual Workstations on Google Cloud.
• Learn more about NVIDIA RTX Virtual Workstation technology.
• Learn more about HP Anyware software.
• Learn more about how PCoIP differs from other remote desktop software.