Setup and installation of NVIDIA CUDA Suit on AWS

This section describes how to launch and connect to NVIDIA CUDA Suit on Amazon Web Services (AWS).

1. Open NVIDIA CUDA Suit VM listing on AWS marketplace

2. Click on Continue to subscribe.

• Login with your credentials and follow the instruction.

• Subscribe to the product and click on Continue to configuration button.

• Select a Region where you want to launch the VM(such as US East (N.Virginia))

• Click on Continue to Launch Button.
• Choose Action: You can launch it through EC2 or from Website.(Let’s choose Launch from website)

• Optionally change the EC2 instance type. (This defaults to g4dn.xlarge instance type with 4 vCPUs and 16 GB RAM, plus 1 x NVIDIA T4 GPU (16GB)).

• 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 network name and subnetwork names.

• Select the Security Group. Be sure that whichever Security Group you specify have ports 22 (for ssh) and 3389 (for RDP) exposed. Or you can create the new SG by clicking on “Create New Based On Seller Settings” button. Provide the name and description and save the SG for this instance.

• Be sure to download the key-pair which is available by default, or you can create the new key-pair and download it.

Click on Launch.

NVIDIA CUDA Suit by Techlatest.net will begin deploying.

3. A summary page displays. To see this instance on EC2 Console click on EC2 Console link.

4. On the EC2 Console page, instance is up and running. To connect to this instance through putty, copy the IPv4 Public IP Address

5. Open putty, paste the IP address and browse your private key you downloaded while deploying the VM, by going to SSH- >Auth ->Credentials, click on Open. Enter ubuntu as userid

6. Once connected, change the password for ubuntu user using below command

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 protocol or Linux Machine using Remmina.

From your local windows machine, goto “start” menu, in the search box type and select “Remote desktop connection”. In the “Remote Desktop connection” wizard, copy the public IP address and click connect

8. This will connect you to the VM’s desktop environment. Provide the username (e.g “ubuntu”) and the password set in the above “Reset password” step to authenticate. Click OK

9. Now you are connected to the out of box NVIDIA CUDA Suit by Techlatest.net environment via Windows Machine.

10. 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, first Install Remmina as per your linux distribution.

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

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

13. Now you are connected to out of box NVIDIA CUDA Suit by Techlatest.net environment via Linux machine.

14. 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

15. 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

16. 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

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

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

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

20. Below is the CUDA installation directory

/usr/local/cuda-12.4/

21. All cuda utilities are installed under

/usr/local/cuda-12.4/bin

22. 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