GPU Pro

Master Your AI Workflow

Professional GPU & System Monitoring Platform

Real-time GPU monitoring with stunning web interface and terminal UI • Zero dependencies • Single binary • Cross-platform

🚀 Quick Start • ✨ Features • 📸 Screenshots • 🛠️ Installation • 📚 Full Documentation

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🎯 Why GPU Pro?

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

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✨ Features

🖥️ GPU Monitoring

• 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

🌐 System Monitoring

• 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

🎨 User Interface

• 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

🏗️ Deployment

• 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

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📸 Screenshots

Web UI Dashboard

Stunning real-time GPU monitoring with modern design

https://youtu.be/vwBC54nXOPI

Terminal UI

Elegant TUI for SSH and headless servers

![IMAGE ALT TEXT HERE]

Network Monitoring

Live connection tracking with global geolocation

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🚀 Quick Start

The fastest way to get started:

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

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

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🛠️ Installation

Prerequisites

• 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

Option 2: Using Make

# Build and run Web UI
make run

# Build and run Terminal UI
make run-cli

Option 3: Manual Build

# Build Web UI version
go build -o gpu-pro

# Build Terminal UI version
go build -o gpu-pro-cli ./cmd/gpu-pro-cli

# Run Web UI (access at http://localhost:1312)
./gpu-pro

# Run Terminal UI
./gpu-pro-cli

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📚 Usage

Web UI Mode (Default)

# 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).

Terminal UI Mode

# 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

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⚙️ Configuration

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)

🏗️ Building from Source

Standard Build

make build-all-docker

🎯 Use Cases

• 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

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🤝 Contributing

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!

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📄 License

MIT License - see LICENSE file for details

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🙏 Acknowledgments

• 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

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