Wai Worker Node

We earn W points by running a worker node and contributing GPUs to the WAI Protocol's distributed AI inference system. W points track your contributions and are likely to convert to rewards in the future.

Requirement

Hardware:

• Any M-Series (Apple Silicon) chip:
  • Macbook/Mac Mini M1, M2, M3, M4
• NVIDIA GPUs: Compute capability of 5.0+
  • GTX 1050, RTX 2060, RTX 3070, RTX 4080, etc.

Software:

• Recommended Nvidia driver (Local PC)
• CUDA Toolkit 12.4 (only supports this version)

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Signup Wai Node Dashboard

• 1- Signup your email in Wai Dashboard
• 2- Create a new Key in API Keys section.

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Installation Method

• Desktop Users: (Linux, Windows, MacOS)

  • Install GUI Application on your local PC from the Download section of the dashboard.
  • If you don't want to install applications on your system, I recommend go through Windows CLI version.

• CLI (Windows):

  • Windows: Install Ubuntu WSL on your Windows using this guide
  • A good internet connection is needed.

• CLI (Rent QuickPod GPU):

  • Signup on QuickPod using email and verify it.
  • Fund your QuickPod with crypto by clicking on +Add on top-right.
  • In Template section, Choose CUDA 12.4.
  • Now in GPU selection, you can buy a cheap one for this node (You find some for $0.05/hr)
  • But more more miners need more vRAM.
  • Click on Create POD to rent GPU.
  • Choose at least 100GB Disk.
  • Press Connect on your Pod.
  • You can Connect to Web Terminal or just copy the SSH Command to connect through your own client like Windows Powershell, VScode, Termius, etc.
  • In QuickPod method , you don't need to create SSH-key and all the steps are as above.

• CLI (Rent Vast GPU):

  • Alternatively, you can follow this Rent and Setup GPU Guide if you want to rent Vast GPUs.
  • I personally use both QuickPod and Vast, choosing based on my needs and the server's price.

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Method: CLI

Step 1. Install Dependecies

# Update System Packages
apt update && apt upgrade -y

# Install General Utilities and Tools
apt install nano screen curl iptables build-essential git wget lz4 jq make gcc nano automake autoconf tmux htop nvme-cli libgbm1 pkg-config libssl-dev libleveldb-dev tar clang bsdmainutils ncdu unzip libleveldb-dev  -y

# Install Python
apt install python3 python3-pip python3-venv python3-dev -y

# Install NodeJS
apt update
curl -fsSL https://deb.nodesource.com/setup_22.x | bash -
apt install -y nodejs
node -v
npm install -g yarn
yarn -v

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Step 2. Install Nvidia & 12.4 CUDA Toolkit

• Verify Cuda version is 12.4 by running nvidia-smi and nvcc --version.
• If you've rented a GPU, then there's no need to install this step since you initially could choose Cuda 12.4 Templates.
• Only if you are a local pc user or with custom sepecification, then follow this to make sure your system is compatible with Cuda 12.4.
• This step is only for Windows (WSL Users) and NOT for native-Linux users.

Install the NVIDIA Driver

• Download and Install the NVIDIA driver version 550.90.07 from this link.
• Note: No need to install a new driver if you think your current NVIDIA driver is 5+ and compatible with Cuda 12.4.

Install CUDA 12.4:

Follow if you don't have any version of Cuda Toolkits installed:

• For Windows users

wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda-repo-wsl-ubuntu-12-4-local_12.4.0-1_amd64.deb
sudo dpkg -i cuda-repo-wsl-ubuntu-12-4-local_12.4.0-1_amd64.deb
sudo cp /var/cuda-repo-wsl-ubuntu-12-4-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda-toolkit-12-4

echo 'export PATH=/usr/local/cuda-12.4/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-12.4/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc

• Check NVIDIA driver version: nvidia-smi
  • Look for Driver Version: 550+ and CUDA Version: 12.4.
• Check the CUDA version with: nvcc --version
  • Should show Cuda release 12.4.

Upgrading or Downgrading to CUDA 12.4:

Follow if you have a different CUDA version installed

# Uninstall the existing CUDA version:
sudo apt remove --purge cuda
sudo apt autoremove

• Now, Follow Install CUDA 12.4 step above.

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Step 3. Install Wai CLI

curl -fsSL https://app.w.ai/install.sh | bash

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Step 4. Run wai Worker

# Add API key
export W_AI_API_KEY=your key here

# Run worker
wai run

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Step 5. Run multiple workers

After you ensure your worker's running good, you can try running multiple workers in the background to mine more coins.

Install PM2

npm install -g pm2

Create a PM2 Configuration File

Create wai.config.js file:

nano wai.config.js

Paste the following configuration in it:

module.exports = {
  apps : [{
    name: 'wai-node', // A name for your process
    script: 'wai',   // The command to run
    args: 'run',     // Arguments for the command
    instances: 4,    // Updated number of instances
    autorestart: true, // Automatically restart if it crashes
    watch: false,    // Don't watch for file changes to restart
    max_memory_restart: '1G', // Restart if memory usage exceeds 1GB (adjust as needed)
    // Combine all environment variables into a single env block
    env: {
      NODE_ENV: 'production',
      W_AI_API_KEY: 'your-key-here'
    }
  }]
};

• Replace your-key-here with your API key.
• You can adjust the instances number based on how many concurrent wai worker nodes your GPU server can handle effectively.

Run workers

pm2 start wai.config.js

• PM2 will read the configuration file and start the specified number of wai run instances. They will run in the background.

Check logs

pm2 logs wai-node

• Takes a few minutes until you get rid of errors and checking for update..

• Wait...

• Still wait...

• BOOM! You are mining coins now!

Useful Commands

# Status of all workers
pm2 list

# Logs of all workers
pm2 logs wai-node

# Logs of a specific worker
pm2 logs 0   # To see logs for the worker with ID 0

# Stop workers
pm2 stop wai.config.js

# Restart workers
pm2 delete wai-node
pm2 restart wai.config.js

# Kill & Wipe all the workers instances
pm2 kill

• If you made any modification to wai.config.js config, you need to run Stop and Restart workers commands above.

Monitor Hardwares

# Monitor GPU vRAM usage
nvidia-smi

# Monitor Disk usage
du -sh /root/.wombo

# Monitor CPU and RAM (it's shared in rented GPUs)
htop

I'm curretly running 9 worker instances on this GPU ($0.06/hr):