Setup and installation of NVIDIA CUDA Suit on GCP

This section describes how to provision and connect to NVIDIA CUDA Suit VM solution on GCP.

1. Open NVIDIA CUDA Suit listing on GCP Marketplace
2. Click Get Started.

It will ask you to enable the API’s if they are not enabled already for your account. Please click on enable as shown in the screenshot.

• It will take you to the agreement page. On this page, you can change the project from the project selector on top navigator bar as shown in the below screenshot.

• Accept the Terms and agreements by ticking the checkbox and clicking on the AGREE button.

• It will show you the successfully agreed popup page. Click on Deploy.

• On deployment page, give a name to your deployment.

• Tick the existing account radio button and select your existing service account from the "Select a service account" dropdown as shown below.

• If you don't see the service account in "Select a service account" drop down, then please follow the below steps to add one. if you can see a service account in the dropdown, skip ahead to the next step to select the region for your deployment.
below steps are one time only and you need appropriate IAM permissions to execute these steps. If you encounter IAM permission errors, reach out to your organization's IAM admin to execute these steps :
1. Note Project id : First note down the project-id of the project where you are deploying our solution . Project id can be found by clicking on the project dropdown and copying id from the poped up window.


2. Activate cloud shell by clicking the shell icon at the top right corner.

3. In the cloud shell, run below command to switch to the project where you are deploying this solution , replace PROJECT_ID with the actual project id copied in step a.

gcloud config set project "PROJECT_ID"

4. Then run below command to create new service account, replace highlighted bold text with suitable values.

gcloud iam service-accounts create "your-service-account-name" --description="service account for your-google-cloud-login-emailid " --display-name="your-service-account-name"

5. Then run below command to associate the newly created service account with your google cloud login id, replace highlighted bold text with values provided in above steps

gcloud iam service-accounts add-iam-policy-binding your-service-account-name@projectid-copied-in-step-a.iam.gserviceaccount.com --member="user:your-google-cloud-login-emailid" --role="roles/iam.serviceAccountUser"

6. Then run below 3 commands one after the other , replace highlighted bold text with your service account name provided in previous steps.

gcloud projects add-iam-policy-binding tcw-project-381520 --member=serviceAccount:your-service-account-name@projectid-copied-in-step-a.iam.gserviceaccount.com --role=roles/config.agent

gcloud projects add-iam-policy-binding tcw-project-381520 --member=serviceAccount:your-service-account-name@projectid-copied-in-step-a.am.gserviceaccount.com --role=roles/compute.admin

gcloud projects add-iam-policy-binding tcw-project-381520 --member=serviceAccount:your-service-account-name@projectid-copied-in-step-a.iam.gserviceaccount.com --role=roles/iam.serviceAccountUser

7. Once the above steps are done, wait for 60 seconds then refresh the deployment page and you should see the newly created service account in "Select a service account". Continue with the next steps below.

• Select a zone where you want to launch the VM(such as us-east1-a)
• Optionally change the number of cores and amount of memory. ( This defaults to 2 vCPUs and 7.5 GB ram)
• The VM can only be deployed with the NVIDIA GPU instance. You can change the Type and number of GPUs from the dropdown. (This defaults to 1 NVIDIA T4 GPU )

Note: GPU availability is limited to certain zones.

• Optionally change the boot disk type and size. (This defaults to ‘Standard Persistent Disk’ and 45 GB respectively)
• Optionally change the network name and subnetwork names. Be sure that whichever network you specify has ports 22 (for ssh) and 3389 (for RDP) exposed.
• Click Deploy when you are done.
• NVIDIA CUDA Suit will begin deploying.

3. A summary page displays when the compute engine is successfully deployed. Click on the Instance link to go to the instance page .

4. On the instance page, click on the “SSH” button, select “Open in browser window”.

5. This will open SSH window in a browser.
6. Run below command to set the password for “ubuntu” user

sudo passwd ubuntu

7. Now the password for ubuntu user is set, you can connect to the VM’s desktop environment from any local windows machine using RDP or linux machine using Remmina.

8. To connect using RDP via Windows machine, first note the external IP of the VM from VM details page as highlighted below

9. Then From your local windows machine, goto “start” menu, in the search box type and select “Remote desktop connection”

10. In the “Remote Desktop connection” wizard, paste the external ip and click connect

11. This will connect you to the VM’s desktop environment. Provide “ubuntu” as the userid and the password set in step 6 to authenticate. Click OK

12. Now you are connected to out of box NVIDIA CUDA Suit environment via Windows machines.

13. To connect using RDP via Linux machine, first note the external IP of the VM from VM details page,then from your local Linux machine, goto menu, in the search box type and select “Remmina”.

    Note: If you don’t have Remmina installed on your Linux machine, firstInstall Remmina as per your linux distribution.

14. In the “Remmina Remote Desktop Client” wizard, select the RDP option from dropdown and paste the external ip and click enter.

15. This will connect you to the VM’s desktop environment. Provide “ubuntu” as the userid and the password set in step 6 to authenticate. Click OK

16. Now you are connected to out of box NVIDIA CUDA Suit environment via Linux machine.

17. The VM comes with various NVIDIA utilities and Cuda utilities installed out of the box. To access the Nvidia Nsight Compute , open the terminal from the RDP desktop window and run below command. This command will launch the Nsight Compute user interface.

ncu-ui

18. To access the Nvidia Nsight System ,open the terminal from the RDP desktop window and run below command. This command will launch the Nsight System user interface.

nsys-ui

19. You can also monitor the GPU utilization of these utilites. To do so, open the new terminal window and run

watch -n 1 nvidia-smi

20. You can find the nsight compute and nsight system setup under /opt/nvidia/ directory.

21. The VM comes with various Nvidia utilies installed out of the box.

22. The VM also comes with various CUDA utilies installed out of the box.

23. Below is the CUDA installation directory

/usr/local/cuda-12.4/

24. All cuda utilities are installed under

/usr/local/cuda-12.4/bin

25. The VM also comes with the “Nsight compute visual studio code Edition” extension installed out of the box.

Please refer to NVIDIA official documentation for more details on how to use these tools.

NVIDIA Official Documentation