GPU-Monitor

Real-time monitoring of model training status, GPU resource utilization, model training logs, IP access records, etc.

Welcome to star, fork, and submit pull requests.

Main Features

• Lightweight and Concise: Flask + SQLite3 + Vue3 + ElementUI-Plus
• Quick Integration: Integration with new servers is as easy as a single line of configuration
• Leisurely Alchemy: Real-time monitoring of model training progress
• Logging System: Track changes in model loss and review training logs
• Announcement Module: Timely delivery of important information
• IP Statistics: Collect and display IP access information to enhance security awareness
• Quick Card Grabbing: Real-time preview of GPU resource utilization
• Low Resource Consumption: Multi-threaded controllable scheduling with minimal CPU usage
• One-Click Deployment: Docker one-click deployment
• Extensibility: Suitable for beginners to practice

Preview

Home Page

Announcement Module

GPU Server Details

Logging System

Logging System

Log Management

View Logs

System Monitoring

Performance Oversight

Update Log or Change Log

Deployment Methods

Docker Deployment Example

1. Build the Image

docker-compose build

2. Run the Service

docker-compose up -d

3. Rebuild

docker stop gpumonitor_web & docker rm -f gpumonitor_web & docker rmi -f  219.216.65.59:5000/gpumonitor_web:latest & \
docker stop gpumonitor_server & docker rm -f gpumonitor_server & docker rmi -f  219.216.65.59:5000/gpumonitor_server:latest & \

Appreciation

If it can help you

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Disclaimer

This project is open-sourced solely for educational purposes and shall not be used for any illegal activities. Otherwise, the consequences are your own responsibility and are not associated with me. Please retain the project's address when using it, thank you.