JLab computing for JAM

  • Get a JLab account

  • Contact N. Sato to give you access to the unix JAM group as well as to additional computing resources at the lab.

Getting started

From your local machine ssh into Jlab systems

ssh -4 -XY  <username>@login.jlab.org
ssh -XY     jlabl1
ssh -XY     thypc21

After this you have landed inside thypc21. As usual you need to customize your shell enviroiment.

cd  ~
cp ../.cshrc  ./
cp ../.tmux-completion.tcsh  ./
cp ../.tmux.conf ./
cp ../.vimrc ./
cp -r ../.vim  ./

Fireup a tmux session

tmux new-session -s test

Next, access to JAM’s working directory

cd /work/JAM

Create a folder under your name if is not present and use this space for all of your work.

ATTENTION: DO NOT execute any heavy computing on thypc21. Use this machine to use tmux and other simple things as vim.

Running heavy programs

As mentioned before, use thypc21 as your portal to JLab computing systems. You should have access to

  1. ifarm: ssh ifarm

  2. vertex: ssh vertex

The optimal workflow is to use ssh into any of these systems from a tmux window launched from thypc21

When sshing into ifarm, you land on arbitrary machine. However all the machines will use the same shell setups. In contrast when sshing into vertex, you land on a different home directory hence you need to makesure to adjust the shell setups accordingly.

Getting a node from the farm

The ifarm is shared by many users who might be running lots of programs. Also the cpu usage is limited. For instance the system will kill your jam script python execution if running it with 20 slaves.

To access to more cpu resorces you need to use salloc

salloc --partition theory -n 1
srun --pty csh

For more option, consult the page https://slurm.schedmd.com/salloc.html.

In addition you can access to gpu resources via

salloc --partition gpu  --gres gpu:1
srun --pty csh

Again, make sure your tmux session/windows/panels are all launched from thypc21.