🤖
Machine Learning Workstation
  • Main page
  • Connection
    • Connection through VPN
  • Usage
    • Python/Conda
    • Edge Impulse
    • Common packages
    • Tmux (persistent sessions)
    • Sharing code base
    • GPU usage
  • Data transfer
    • To or from the host machine
    • To or from the Internet
  • Useful links
    • Linux
    • Python
    • Machine Learning
      • Classifiers
      • Natural Language Processing
      • Unsupervised Learning
      • Data Generation
      • Autoencoders
    • Evaluating Neural Networks
    • Recurrent Neural Network
  • Administration
    • Introduction
      • TLJH mamba/pip installations for ALL users
      • TLJH: IDLE-CULLER - Disabled TODO need a sane value
      • Allowing user to log in to your JupyterHub without server user name
    • Connect to the machine via SSH
      • Add SSH Keys
      • Port forwarding
      • X forwarding (running software with GUI)
      • Run Jupyter remotely
    • Managing users
    • System maintenance
    • Other tasks
Powered by GitBook
On this page
  • Setup and tutorial
  • iTerm2 integration

Was this helpful?

  1. Usage

Tmux (persistent sessions)

PreviousCommon packagesNextSharing code base

Last updated 1 year ago

Was this helpful?

Tmux allows you to host multiple persistent terminal sessions on a single connection.

Setup and tutorial

  • Connect to the workstation, and create a new session by typing:

    tmux

  • Add a new tab (called "window" within tmux): ctrl + B, C

  • Move to previous or next tab: ctrl + B, P and ctrl + B, N

  • Quit (detach) tmux session: ctrl + B, D

  • Once you re-connect to the workstation, you can attach to the existing session by typing:

    tmux a

For more information, consult the manual by typing man tmux or this .

iTerm2 integration

If you use iTerm2 on OS X, you can navigate all of your tmux tabs using native interface and shortcuts. Connect to the workstation by typing:

ssh ml_workstation -t 'tmux -CC a -t 0'

For more information, refer to .

cheatsheet
iTerm2 docs