Show HN: [GPU-Pro] Master Your AI Workflow

7 hours ago 1

GPU Pro is the modern solution for NVIDIA GPU monitoring, designed for AI engineers, ML researchers, and GPU cluster administrators. Get real-time insights into your GPU infrastructure with:

  • 🎨 Beautiful Web UI - Sleek, responsive dashboard with real-time updates
  • 💻 Terminal UI - Elegant TUI for SSH sessions and headless servers
  • 📊 Comprehensive Metrics - GPU utilization, memory, temperature, power, processes, and more
  • 🌐 Network Monitoring - Track connections, bandwidth, and geolocation
  • 💾 System Insights - CPU, RAM, disk, and fan monitoring
  • 🔌 Hub Mode - Aggregate multiple GPU nodes into one dashboard
  • 🚀 Zero Setup - Single binary, no Python, no Node.js, no containers required
  • Lightning Fast - Built with Go for maximum performance

  • Real-time Metrics: Utilization, memory usage, temperature, power consumption
  • Process Tracking: See what's running on each GPU with detailed process information
  • Multi-GPU Support: Monitor all GPUs simultaneously
  • Historical Charts: Track performance over time with customizable time ranges
  • NVML & nvidia-smi: Supports both native NVML library and nvidia-smi fallback
  • Network I/O: Real-time bandwidth tracking with historical charts
  • Disk I/O: Monitor read/write operations and throughput
  • Network Connections: Live connection tracking with geolocation on world map
  • Open Files: Track open file descriptors and large files
  • System Resources: CPU, RAM, disk usage, and fan speeds
  • Web Dashboard: Modern, responsive design with glassmorphism effects
  • Terminal UI (TUI): Beautiful colored terminal interface for SSH sessions
  • Dark Theme: Professional tech-inspired design optimized for long sessions
  • Real-time Updates: WebSocket-based live data streaming
  • Mobile Responsive: Works perfectly on phones and tablets
  • Single Binary: Everything embedded - templates, assets, and code
  • Cross-Platform: Linux, Windows, macOS support
  • Multiple Modes: Standalone or hub aggregation mode
  • Easy Deployment: Systemd service, Docker, or bare metal
  • Zero Dependencies: Just NVIDIA drivers required

Stunning real-time GPU monitoring with modern design

https://youtu.be/vwBC54nXOPI

til

Elegant TUI for SSH and headless servers

til


The fastest way to get started:

wget https://raw.githubusercontent.com/ulixcode-labs/GPU-pro/refs/heads/main/install.sh && bash install.sh

or

curl https://raw.githubusercontent.com/ulixcode-labs/GPU-pro/refs/heads/main/install.sh > install.sh && bash install.sh

That's it! The script will run the project and let you choose between Web UI or Terminal UI.


  • NVIDIA GPU with drivers installed
  • Go 1.24+ (for building from source)
  • Linux, Windows, or macOS

Option 1: Quick Start Script (Recommended)

chmod +x start.sh ./start.sh
# Build and run Web UI make run # Build and run Terminal UI make run-cli

# Start with default settings (localhost:1312) ./gpu-pro # Custom port PORT=8080 ./gpu-pro # Enable debug mode DEBUG=true ./gpu-pro # Custom update interval (seconds) UPDATE_INTERVAL=1.0 ./gpu-pro

Access the dashboard at http://localhost:1312 (or your custom port).

# Launch TUI interface ./gpu-pro-cli

Perfect for SSH sessions and headless servers!

Hub Mode (Multi-Node Monitoring)

# Aggregate multiple GPU nodes GPU_PRO_MODE=hub \ NODE_URLS=http://node1:1312,http://node2:1312,http://node3:1312 \ ./gpu-pro

All configuration is done via environment variables:

Variable Default Description
HOST 0.0.0.0 Server bind address
PORT 1312 Server port
DEBUG false Enable debug logging
UPDATE_INTERVAL 0.5 GPU polling interval (seconds)
NVIDIA_SMI_INTERVAL 2.0 nvidia-smi fallback interval (seconds)
NVIDIA_SMI false Force nvidia-smi mode
GPU_PRO_MODE default Mode: default or hub
NODE_NAME hostname Node identifier
NODE_URLS empty Comma-separated node URLs (hub mode)
  • AI/ML Training: Monitor GPU utilization during model training
  • Research Labs: Track multi-GPU workstations and servers
  • GPU Clusters: Aggregate monitoring across multiple nodes
  • Cloud GPU Instances: Monitor AWS, GCP, or Azure GPU VMs
  • Gaming Rigs: Track GPU performance during gaming sessions
  • Crypto Mining: Monitor mining rig performance and temperatures
  • Remote Work: SSH-friendly TUI for remote GPU monitoring

Contributions are welcome! Here's how you can help:

  1. 🐛 Report Bugs: Open an issue with detailed reproduction steps
  2. 💡 Suggest Features: Share your ideas in the issues section
  3. 🔧 Submit PRs: Fork, create a feature branch, and submit a pull request
  4. 📖 Improve Docs: Help us make the documentation better
  5. Star the Project: Show your support!

MIT License - see LICENSE file for details


  • NVIDIA for the NVML library
  • Go NVML bindings by NVIDIA
  • Charm for beautiful TUI components (Bubble Tea, Lipgloss)
  • Fiber for blazing-fast web framework
  • Chart.js for stunning data visualizations

Read Entire Article