文件列表:

LICENSE
baram.py
baram_graphs.py
cpu-gpu_stressTest.py
cpu_stress_log.sh
gpu_temp.md
gpu_temp.sh
stressGraphs.py
testdata
testdata.txt

# Baram: Advanced System Cooling Management Tool A Linux utility designed to manage fans on Tesla Datacenter GPUs mounted in ATX cases. Named after the Korean word for wind, Baram provides an intuitive, CLI-based interface for optimizing cooling performance and noise management in Linux systems. ## Overview Baram is a specialized cooling management tool developed for Nvidia data center GPUs repurposed in ATX-like cases. It enhances thermal performance, extends component longevity, and minimizes noise, making it ideal for enthusiasts and newcomers alike. ## Mission Our mission is to empower users to revitalize used data center GPUs with an advanced, accessible cooling management solution. ## Key Features ### Stage 1: Initial Release - **Profile Management**: Users can create, save, and switch between multiple cooling profiles. - **Dynamic Temperature Monitoring**: Adaptive fan control is based on real-time GPU and system temperatures. ### Stage 2: Logic Enhancement - **System-Wide Fan Identification**: Configures GPU, CPU, and chassis fans for a unified cooling strategy. - **Enhanced Temperature Logic**: Improves temperature monitoring and fan control algorithms. ### Stage 3: Optimization - **Airflow Optimization Profiles**: Balances intake and exhaust to improve cooling and reduce noise. - **Noise Optimization Mode**: Minimizes noise while maintaining effective cooling. ### Stage 4: Data Visualization and Monitoring - **Historical Data Graphing**: Users can generate graphs from historical data for cooling performance over time. - **Live Graphing**: Real-time graphing of temperature and fan speeds for immediate feedback. This will be implemented with the `baram_graphs.py` script. ## Roadmap - **Graphing Function Integration**: The next major feature will be the addition of graphing functionalities through `baram_graphs.py`, which will handle both historical data visualization and real-time monitoring graphing. ## Getting Started ### Installation 1. Ensure Python3 and Pip are installed on your system. 2. Install the required Python libraries: ```bash pip install -r requirements.txt ``` ### Running Baram Execute the following command to start Baram: ```bash python baram.py ``` ### Creating a Service for Ubuntu To ensure Baram runs as a service on Ubuntu, follow these steps: 1. Create a systemd service file: ```bash sudo nano /etc/systemd/system/baram.service ``` 2. Add the following configuration, modifying the `ExecStart` path as necessary: ```ini [Unit] Description=Baram Cooling Management Service After=network.target [Service] Type=simple User=your_user ExecStart=/usr/bin/python3 /path/to/baram.py [Install] WantedBy=multi-user.target ``` 3. Enable and start the Baram service: ```bash sudo systemctl enable baram.service sudo systemctl start baram.service ``` 4. Check the service status with: ```bash sudo systemctl status baram.service ``` ### Usage - To view available commands, use: ```bash python baram.py --help ``` - For creating and managing profiles, consult the Baram documentation or the help command output. ## Contributing We welcome contributions of all kinds, from code to documentation, from all members of the community. Please see our contributing guidelines for more information on how to get involved. ## License Details about the project's license are included here, outlining the permissions and restrictions for using and distributing Baram. ## Acknowledgments Our heartfelt thanks to the community, especially those who have contributed code, feedback, and support to the project.

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