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https://github.com/swetoast/nvidia-gpu-monitoring-server
NVIDIA GPU Monitoring Server is a specialized server designed to monitor and provide detailed statistics about your NVIDIA GPU. It leverages the power of Flask, a lightweight web server framework, to create multiple endpoints. Each endpoint corresponds to a specific type of data related to the GPU
https://github.com/swetoast/nvidia-gpu-monitoring-server
automation home-assistant monitoring openhab2
Last synced: 30 days ago
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NVIDIA GPU Monitoring Server is a specialized server designed to monitor and provide detailed statistics about your NVIDIA GPU. It leverages the power of Flask, a lightweight web server framework, to create multiple endpoints. Each endpoint corresponds to a specific type of data related to the GPU
- Host: GitHub
- URL: https://github.com/swetoast/nvidia-gpu-monitoring-server
- Owner: swetoast
- License: unlicense
- Created: 2024-01-13T09:02:43.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-07-07T16:38:48.000Z (6 months ago)
- Last Synced: 2024-07-07T17:59:35.108Z (6 months ago)
- Topics: automation, home-assistant, monitoring, openhab2
- Language: Python
- Homepage:
- Size: 38.1 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# NVIDIA GPU Monitoring Server
Welcome to the NVIDIA GPU Monitoring Server! This server is designed to work with NVIDIA GPUs and provides a RESTful API to monitor various GPU parameters in real-time.
## Features
- Real-time monitoring of GPU parameters.
- Easy integration with Home Assistant.
- RESTful API for easy access and compatibility.
## API Endpoints
The server provides the following endpoints, each returning a specific GPU parameter:
- `/powerusage`: Current power usage in watts.
- `/temperature`: Current temperature in degrees Celsius.
- `/fanspeed`: Current fan speed as a percentage of its maximum speed.
- `/memoryusage`: Current memory usage in MiB.
- `/gpuutil`: Current GPU utilization as a percentage.
## Configuration
Before starting the application, ensure you edit your configuration file `nvidia-endpoint-server.conf`. The configuration file should be located in the same directory as the script. Here's an example of what the configuration file should look like:
```conf
[DEFAULT]
HOST = 127.0.0.1
PORT = 5000
USE_HTTPS = False
CERTIFICATE_PATH = /path/to/your/certificate.crt
KEY_PATH = /path/to/your/key.key
```
## Docker Container
This docker container uses the Official Docker image from NVIDIA and has python installed.
Before starting the container you can edit the docker-compose.yaml and change the exposed ports.
To start the container, execute the following command:
```bash
docker-compose up -d
```
## Home Assistant Integration
This server can be integrated with Home Assistant using the RESTful sensor. Here are some examples of how to set up the sensors in your Home Assistant configuration:
```yaml
sensor:
- platform: rest
resource: http://IP_ADDRESS:PORT/powerusage
name: GPU Power Usage
value_template: '{{ value_json.power_usage }}'
unit_of_measurement: 'W'
device_class: energy
state_class: measurement
- platform: integration
source: sensor.gpu_power_usage
name: 'Example Energy Usage'
unit_prefix: k
unit_time: h
- platform: rest
name: GPU Temperature
resource: http://IP_ADDRESS:PORT/temperature
value_template: '{{ value_json.temperature }}'
unit_of_measurement: '°C'
- platform: rest
name: GPU Fan Speed
resource: http://IP_ADDRESS:PORT/fanspeed
value_template: '{{ value_json.fan_speed }}'
unit_of_measurement: '%'
- platform: rest
name: GPU Memory Usage
resource: http://IP_ADDRESS:PORT/memoryusage
value_template: '{{ value_json.memory_usage }}'
unit_of_measurement: 'MiB'
- platform: rest
name: GPU Utilization
resource: http://IP_ADDRESS:PORT/gpuutil
value_template: '{{ value_json.gpu_util }}'
unit_of_measurement: '%'
```
Please replace `IP_ADDRESS` and `PORT` with the actual IP address and port of your server.
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