How To Create A NVIDIA H100 GPU Cloud Server To Run And Train AI, ML, And LLMs Apps On DigitalOcean
21In this video, you will learn how to setup a NVIDIA H100 Graphics Processing Unit (GPU) Virtual Private Server (VPS) also known as a cloud server to run and train Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs) applications on DigitalOceans GPU droplet service. DigitalOcean GPU droplets come configured with all the necessary NVIDIA drivers and software preinstalled to help you get started on your AI/ML journey. DigitalOceans GPU droplets AI/ML ready images, come preinstalled with the Ubuntu Linux Operating System (OS).
🔵 Free $200 DigitalOcean GPU cloud credits using my referral link: https://digitalocean.pxf.io/c/1245219/1373759/15890
Steps To Setup GPU Droplets On DigitalOcean:
1. Go to https://digitalocean.pxf.io/c/1245219/1373759/15890 and create a free DigitalOcean account. The above link is my referral link granting you $200 in free cloud credit for 60 days as a new user
2. Once you have created your DigitalOcean account, you will be taken to your DigitalOcean project dashboard. Click Create.
3. Click GPU Droplets
4. Configure your droplet to your liking ensuring to select DigitalOceans AI/ML Ready image
5. Add a Public SSH Key for authentication, and for logging into your GPU droplet via SSH. You will need to download and install PuTTY you can do so here https://www.putty.org/ or follow this step by step video of mine
6. Once you got PuTTY and all its complementary software, open PuTTYgen (PuTTY Key Generator)
7. Click Generate and move your mouse randomly to generate your public and private key pair
8. Copy and paste your public key into DigitalOcean, click add SSH Key and and select your added public key for use with the droplet you're creating
9. In PuTTYgen save your Private key on your local machine and also save your Public key as a backup
10. Go back to your DigitalOcean and click Create GPU Droplet
11. Once your GPU droplet is active, copy the IPV4 address of your GPU droplet in the Overview tab under connection details and open up the PuTTY program
12. Paste in your GPU droplets IP address into the hostname section of PuTTY
13. Click the + symbol next to the SSH category in PuTTY
14. Click Auth
15. Click Browse and find your Pirate SSH key that you generated using PuTTYgen and saved on your local device.
16. Click Open to select it and then click Open again on PuTTY
17. The PuTTY command line terminal terminal will then open and you should see Login as at the top left of the terminal
18. Type root and press Enter on your keyboard
19. You have now logged into your GPU droplet and can now begin training and running your AI/ML/LLM apps through the terminal.
Commands to check NVIDIA GPU Specs (in order from least information to most):
nvidia-smi -L
nvidia-smi
nvidia-smi -q
Congratulations, you have successfully created a NVIDIA GPU droplet that's AI/ML ready!
DigitalOcean NVIDIA H100 Droplet Specs (Single GPU):
1 GPU
80 GB VRAM
20 vCPU
240 GB RAM
Boot disk: 720 GB NVMe
Scratch disk: 5 TB NVMe
DigitalOceans AI/ML-ready image is Ubuntu 22.04 based and includes at the time of recording of this video:
nvidia-container-toolkit=1.16.2-1
cuda-keyring_1.1-1
cuda-drivers-535
cuda-toolkit-12-1
bzip2 (8 GPU Droplets only)
MLNX_OFED_LINUX-23.10-1.1.9.0-ubuntu22.04-x86_64 (8 GPU Droplets only)
nvidia-fabricmanager-535 (8 GPU Droplets only)
Timestamps:
0:00 - Intro & Context
0:29 - Create DigitalOcean GPU Droplet (Cloud Server)
2:25 - Generate SSH Private And Public Key Pair For Authentication
6:56 - Log Into Your GPU Droplet Using Your Private Key
8:37 - Check GPU Specifications
9:47 - Closing & Outro
Grow your YouTube Channel with vidIQ https://vidiq.com/70s
More DigitalOcean Server Guides (Playlist) • DigitalOcean Cloud Computing Guides
Ubuntu Linux Tutorials (Playlist) • Ubuntu Linux Tutorials
Artificial Intelligence (AI), Machine Learning (ML), And Large Language Models (LLMs) Tutorials (Playlist) • Artificial Intelligence (AI), Machine...
NVIDIA Graphics Card (GPU) Guides (Playlist) • NVIDIA Graphics Card (GPU) Guides
Social Media
SUBSCRIBE / @websplaining
Instagram (Thumbnail Collection) https://www.instagram.com/websplaining
X (For Newest uploads) https://x.com/websplaining
Reddit (Discussions) https://www.reddit.com/r/Websplaining
Personal Website https://www.websplaining.com/
#NVIDIA #GPU #DigitalOcean
DONT FORGET TO LIKE, COMMENT, AND SUBSCRIBE!