XLEAP Beamtime - User Guide

New User Overview

What to expect: typical startup sequence

Checking Beam Status

CHESS status page: http://new-status.chess.cornell.edu/

CESR status page: https://cesrwww.lepp.cornell.edu/docs/statpanel/fullscore_auto.html

Remote access to data

More details on these steps can be found in the CHESS user guide: https://www.chess.cornell.edu/user-guide

Getting started: checklist

1. Do you have a CLASSE ID?

This is the same ID you would use to access the BeamPASS user portal.

• If you have a Cornell affiliation, your CLASSE ID is probably the same as your NetID
  

If you will be a CHESS user and do not have a CLASSE ID or if you forgot CLASSE ID password, visit BeamPASS and follow the appropriate link.

2. Is your CLASSE account active?

If you don't remember the last time you logged in to your CLASSE account: activate your account or reset your password.

3. Are you enrolled in CLASSE Duo?

Most CHESS computing resources require CLASSE Duo two-factor authentication. Please follow the instructions here: https://wiki.classe.cornell.edu/Computing/CLASSEDuo

NoMachine

If you haven't connected to CHESS resources via NoMachine before, please install the client and test your connection by following the instructions here: https://wiki.classe.cornell.edu/CHESS/RemoteUserGuide ("Test your connection to a station computer").

JupyterHub

For convenience, CHESS offers the option of remote interaction with data, including complext data analysis, through a web-based interface called JupyterHub: https://jupyterhub.classe.cornell.edu/

Step 1: Set up an XLEAP-specific "kernel" for your JupyterHub environment.

This an XLEAP-specifc version of the "Adding new environments" on the CLASSE page (JupyterHub).

1. Log onto a linux terminal window on the CLASSE cluster. This can be done in several ways:
   • Launch a terminal window within a NoMachine session
   • If you are on-site, find a terminal window (e.g. on the station computer of lnx-id3b-1) and type ssh [your-classe-id]@lnx201, and follow the steps to complete logon
   • Launch JupyterHub using a default environment, and launch a Terminal within JupyterHub
2. Make sure you're in your own user directory: cd /nfs/user/yourCLASSEID

3. Activate the XRF workflow environment:

   • source /nfs/chess/user/lmb327/miniconda3/bin/activate; conda activate xrfplots

4. Run: python -m ipykernel install --user --name=xrfplots --display-name “xrfplots”

Step 2: Launching JupyterHub

1. Open a browser on your computer (on or off site), then follow the ste
2. Follow the steps documented here: Jupyter Hub: https://wiki.classe.cornell.edu/Computing/JupyterHub
3. When opening a new or existing notebook, the "xrfplots" kernel should appear as an option.

When you connect to JupyterHub, generally you'll want to connect to the CLASSE Compute Farm server, using the option with the 32 CPUs if you plan to do batch processing.

-- LouisaSmieska - 08 Apr 2025