Skip to main content

A simple monitor for NVIDIA GPUs

Project description

GPUDashboard

A simple dashboard for NVIDIA GPU flowchart

Demo

Example

Requirement

  • Python 2.7 or 3.6
  • NVIDIA-sim
  • A Firebase realtime database
  • Linux-like OS

Setup

  1. Create a Firebase Realtime database
  1. Set the rules to
{
  "rules": {
    ".read": true,
    ".write": true
  }
}
  1. Go to Project overview click Add Firebase to your web app and copy following part.
  var config = {
    apiKey: "XXXXXXXXXXXXXXXXXXXXXXXXXXXX",
    authDomain: "XXXXX.firebaseapp.com",
    databaseURL: "https://XXXXXX.firebaseio.com",
    projectId: "XXXXXXX",
    storageBucket: "XXXXXXX.appspot.com",
    messagingSenderId: "XXXXXXXXXXX"
  };
  1. On the servers that have NVIDIA GPU(s) installed.
pip install GPUDashboard
GPUDashboard -n your_server_name -i 20 -u your_databaseURL > GPUDashboard.log 

# your_server_name is the name you want to give your server e.g. MyFirstServer
# -i is the interval of GPU information updating
# your_databaseURL is the databaseURL obtained froom Firebase as shown above

Now, the server GPU information is post to the firebase. *If you have many servers, all of them can make use of the same database you created in Firebase. You only need to specify different names for "your_server_name" when you start the GPUDashboard in the command line on the different servers.

  1. Download ViewStatus.html and open with text editor then replace the "config".
<html>
    <header>
      <script>
        var config = {
            apiKey: "XXXXXXXXXXXXXXXXXXXXXXXXXXXX",
            authDomain: "XXXXX.firebaseapp.com",
            databaseURL: "https://XXXXXX.firebaseio.com",
            projectId: "XXXXXXX",
            storageBucket: "XXXXXXX.appspot.com",
            messagingSenderId: "XXXXXXXXXXX"
          };
      </script>
      <link rel="stylesheet" href="https://fonts.googleapis.com/icon?family=Material+Icons"/>
  1. Open the "modified ViewStatus.html" with browser.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gpu-monitor-isi-0.0.5.tar.gz (6.9 kB view details)

Uploaded Source

Built Distribution

gpu_monitor_isi-0.0.5-py3-none-any.whl (9.2 kB view details)

Uploaded Python 3

File details

Details for the file gpu-monitor-isi-0.0.5.tar.gz.

File metadata

  • Download URL: gpu-monitor-isi-0.0.5.tar.gz
  • Upload date:
  • Size: 6.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.17

File hashes

Hashes for gpu-monitor-isi-0.0.5.tar.gz
Algorithm Hash digest
SHA256 bb8a9bd1a6618701783b958cf8f1d2f1d467b9be8eff5b8603cda863b5b74637
MD5 96dbcb9feeac1918d43d0e51535b9c86
BLAKE2b-256 c656dfee676b17d845a99e99016c1e45c682fe9c8ae7bfd636f8b5d7ad1eccf6

See more details on using hashes here.

File details

Details for the file gpu_monitor_isi-0.0.5-py3-none-any.whl.

File metadata

File hashes

Hashes for gpu_monitor_isi-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 8a681f20ad76f637ce16e858290c4d5228b619ff0aa0eb54b3bb55d33da6a335
MD5 18bc88ca28f9c1f8f5f9c24e1784d9b0
BLAKE2b-256 eba9b63f1678e62c2a67c9f3d5c7eb6467e57dae3a2cc3ce9f44a98f76759407

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page