Real-time monitoring of CPU, Memory, and GPU resources with modern UI
The System Resource Monitor v2.0 is a comprehensive Python application that provides professional-grade monitoring of system resources. Built with a modern 4-panel dashboard, it offers real-time tracking of CPU, Memory, GPU usage, and GPU memory with intelligent alerting and data export capabilities.
- 🎮 Multi-GPU Support: NVIDIA, AMD Radeon, and Intel Arc GPUs
- 📊 4-Panel Dashboard: Dedicated graphs for CPU, Memory, GPU, and GPU Memory
- 🎨 Modern UI: Professional interface with status indicators and emoji icons
- ⚡ Enhanced Performance: 60-point history with optimized rendering
- 🔧 Smart Detection: Automatic GPU hardware detection with fallbacks
- Real-time CPU tracking with per-core analysis
- Memory usage monitoring with threshold alerts
- GPU utilization tracking for gaming and content creation
- GPU memory monitoring to prevent VRAM overflow
- Top 20 process tracking sorted by CPU usage
- Customizable thresholds for each resource type
- Desktop notifications with Windows 10/11 integration
- Sustained alert logic (CPU: 60s, Memory: 120s, GPU: 60s)
- Visual status indicators with color-coded feedback
- 4-panel dashboard with dedicated resource graphs
- 60-point history for detailed trend analysis
- Professional styling with modern matplotlib themes
- Real-time updates with smooth graph rendering
- Threshold visualization with danger lines
- CSV export functionality with GPU metrics included
- Process list export for system analysis
- Historical data retention for trend analysis
- Configurable monitoring intervals (1-10 seconds)
| GPU Vendor | Support Level | Monitoring Method | Requirements |
|---|---|---|---|
| NVIDIA | ✅ Full | nvidia-ml-py3, GPUtil | Latest NVIDIA drivers |
| AMD | ✅ Full | Windows Performance Counters | Latest AMD drivers |
| Intel Arc | Hardware detection | Intel Arc drivers | |
| Integrated | ℹ️ Detection | System information only | N/A |
- AMD Radeon RX 6800 XT - Full monitoring support ✅
- NVIDIA GeForce RTX Series - Full monitoring support ✅
- NVIDIA GTX Series - Full monitoring support ✅
- Download the latest release from the releases page
- Extract the ZIP file to your preferred location
- Run
install.batto check system compatibility - Launch
SystemResourceMonitor.exe
# Clone the repository
git clone https://github.com/your-username/System-Resource-Monitor.git
cd System-Resource-Monitor
# Install dependencies
pip install -r requirements.txt
# For GPU monitoring (optional)
pip install GPUtil nvidia-ml-py3
# Run the application
python main.py# Install build tools
pip install pyinstaller
# Build executable
python build_system_monitor.py
# Find your executable in the 'release' folder- Control Panel: Set thresholds and monitoring intervals
- 4-Panel Dashboard: View CPU, Memory, GPU, and GPU Memory
- Status Indicator: 🟢 Active / 🔴 Stopped monitoring
- Export Functions: Save data and process lists
- Real-time Process List: Top 20 CPU-intensive processes
- Detailed Information: PID, Name, CPU%, Memory%
- Export Capability: Save process snapshots
- Start Monitoring: Click
▶️ or pressAlt+S - Stop Monitoring: Click ⏹️ or press
Alt+T - Export Data: Click 💾 or press
Ctrl+E
CPU: 85% (Gaming/Workstation)
Memory: 90% (General Use)
GPU: 99.5% (High-performance applications)
- OS: Windows 10 or later (Windows 11 recommended)
- Python: 3.8+ (for development)
- RAM: 100MB minimum, 200MB recommended
- Permissions: Administrator rights for optimal GPU monitoring
├── main.py # Application entry point
├── monitor/
│ ├── system_monitor.py # Core monitoring class
│ ├── gui.py # Modern UI implementation
│ └── monitor.py # Resource monitoring logic
├── utils/
│ └── utils.py # Utility functions & system info
└── build_system_monitor.py # Distribution builder
# Core Requirements
psutil>=5.8.0 # System monitoring
matplotlib>=3.4.3 # Graph rendering
tkinter # GUI framework
plyer>=2.0.0 # Notifications
# GPU Monitoring (Optional)
GPUtil # Cross-platform GPU support
nvidia-ml-py3 # NVIDIA-specific monitoring- Update drivers to latest version
- Run as Administrator for hardware access
- Test with GPU load (run a game or benchmark)
- Run diagnostic:
python gpu_diagnostic.py
- NVIDIA: Install drivers from nvidia.com/drivers
- AMD: Install drivers from amd.com/support
- Integrated Graphics: Normal behavior - not a dedicated GPU
- High CPU usage: Increase monitoring interval to 2-5 seconds
- Memory leaks: Restart application after extended use
- Graph lag: Close other monitoring applications
# Common solutions
pip install --upgrade pyinstaller
pip install --upgrade matplotlib tkinter
python -m pip install --force-reinstall psutil| Setting | Default | Range | Description |
|---|---|---|---|
| CPU Threshold | 85% | 1-100% | CPU usage alert level |
| Memory Threshold | 90% | 1-100% | Memory usage alert level |
| GPU Threshold | 99.5% | 1-100% | GPU usage alert level |
| Update Interval | 1s | 0.5-10s | Monitoring frequency |
| History Length | 60 | 10-300 | Graph data points |
- CPU Alerts: Triggered after 60 seconds of sustained high usage
- Memory Alerts: Triggered after 120 seconds of sustained high usage
- GPU Alerts: Triggered after 60 seconds of sustained high usage
We welcome contributions! Here's how you can help:
- Use the Issues tab to report bugs
- Include system information and GPU model
- Provide steps to reproduce the issue
- Suggest new monitoring capabilities
- Request additional GPU vendor support
- Propose UI/UX improvements
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Test thoroughly with different GPU configurations
- Commit changes (
git commit -m 'Add amazing feature') - Push to branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the Apache License 2.0. See the LICENSE file for details.
- ✅ Commercial use allowed
- ✅ Modification allowed
- ✅ Distribution allowed
- ✅ Private use allowed
- ❗ License and copyright notice required
- Thymester/Tyler - Lead Developer & GPU Specialist
- AMD RX 6800 XT users for testing GPU monitoring
- NVIDIA community for driver compatibility feedback
- Open source community for libraries and inspiration
If this project helped you, please give it a ⭐ on GitHub!
This application is provided "as-is" without any warranty. The authors and contributors are not responsible for any damage, data loss, or system issues caused by the use of this software.
- No data collection: All monitoring data stays on your system
- No network communication: Operates entirely offline
- No user tracking: Your privacy is completely protected
Download System Resource Monitor v2.0 today!
📥 Download Latest Release | 📖 Documentation | 🐛 Report Bug | 💡 Request Feature