Jupyter Notebook
Getting started with Jupyter Notebook.
A Jupyter notebook server running on ExCL can be accessed via a local web browser through port forwarding the Jupyter notebook's port. By default, this is port 8888 (or the next available port). This port might be in use if someone else is using running a notebook. You can specify the port with the --port flag when launching the Jupyter notebook. To use a different port just replace 8888 with the desired port number. In order to port forward from an internal node, you have to port forward twice, once from your machine to login.excl.ornl.gov and once again from the login node to the internal node (i.e. pcie).
These instructions go over how to access a Jupyter notebook running on the pcie node in the ExCL Cluster. If you want to access a different system, then replace
pcie
with the system you want to access.- 1.Specify the ports that you want to use. Choose a different number from the default so that you don't conflict with other users.export REMOTE_PORT=8888export LOCAL_PORT=8888
- 2.From your local machine connect to pcie using login.excl.ornl.gov as a proxy and local forward the jupyter port.ssh -L $LOCAL_PORT:localhost:$REMOTE_PORT -J [email protected] [email protected]
- 3.(Optional) Load the anaconda module if you don't have jupyter notebook installed locally.module load anaconda3
- 4.Launch the Jupyter server on pcieexport REMOTE_PORT=8888jupyter notebook --port $REMOTE_PORT
- 5.Connect to the Jupyter notebook using a web browser on your local machine. Use the token shown in the output from running the Jupyter server. Url:
http://localhost:<local_port>/?token=<token>
. You can also configure jupyter to use a password withjupyter notebook password
if you don't want to use the access tokens.
If you ssh client is too old for proxyjump to work, you can always break up the process into anouther step.
- 1.From your local machine connect to login.excl.ornl.gov and local port forward port 8888.$ ssh -L 8888:localhost:8888 <username>@login.excl.ornl.gov
- 2.From the login node connect to pcie and local port forward port 8888$ ssh -L 8888:localhost:8888 pcie
- 3.Launch the Jupyter server on pcie$ jupyter notebook
- 4.Connect to the Jupyter notebook using a web browser on your local machine. Use the token shown in the output from running the Jupyter server. Url:
http://localhost:8888/?token=<token>
These instructions go over how to access a Jupyter notebook running on the pcie node in the ExCL Cluster.
- 1.From your local machine connect to login.excl.ornl.gov using MobaXterm.MobaXTerm SSH
- 2.Go to tools and click on MobaSSHTunnel. Use MobaSSHTunnel local forward port 8888.Click on MobaSSHTunnelClick on MobaSSHTunnelClick on New SSH TunnelClick on New SSH TunnelLocal port forward 8888Local port forward 8888Click the play button to start port forwardingClick the play button to start port forwarding
- 3.From the login node connect to pcie and local port forward port 8888$ ssh -L 8888:localhost:8888 pcie
- 4.Launch the Jupyter server on pcie$ jupyter notebook
- 5.Connect to the Jupyter notebook using a web browser on your local machine. Use the token shown in the output from running the Jupyter server. URL:
http://localhost:8888/?token=<token>
These instructions go over how to access a Jupyter notebook running on the quad00 node in the ExCL Cluster using Visual Studio Code to handle port forwarding.
- 1.Open Visual Studio Code
- 2.Make sure you have the Remote - SSH extension installed.SSH Extension VS Code
- 3.Setup .sshNavigate to the remote explorer settings.Navigate to the remote explorer settings.Chose the user .ssh config.Chose the user .ssh config.Add the remote systems to connect to with the proxy command to connect through the login node.Add the remote systems to connect to with the proxy command to connect through the login node.
- 4.Connect to the remote system and open the Jupyter folder.Connect step 1Open FolderOpen Folder
- 5.Run the Jupyter notebook using the built-in terminal.Run Jupyter
- 6.Open the automatically forwarded port.Open Port
Anaconda3 is already installed in ExCL as a module and can be used to run Jupyter notebooks. To load the module use
module load anaconda3
. Now you have access to the jupyter notebook
command.This section is a quick start to installing an anaconda python environment with Jupyter notebook.
- 1.
- 2.Install Jupyter Notebook.$ conda install -c conda-forge notebook
Create conda environment and activate it. Then install
ipykernel
and then install the kernel for use in Jupyter.conda install ipykernel
ipython kernel install --user --name=<any_name_for_kernel>
Use
jupyter kernelspec list
to view all the installed Jupyter kernels.jupyter kernelspec list
To uninstall a Jupyter kernel use uninstall.
jupyter kernelspec uninstall <unwanted-kernel>