Public FUSE installation on GA's Omega

FUSE module

If you only intend to use FUSE and don't plan to develop the source code, release versions of FUSE have been installed on the Omega cluster. All available versions can be found with module avail fuse. To load the latest version, do:

module load fuse

Once the module is loaded, you can start Julia at the terminal and import the FUSE module.

Running Julia/FUSE via VScode

The simplest way to start using FUSE is with VScode and remote SHH connection to Omega.

To do this:

Open a remote connection to Omega
Install the Julia and the Jupyter VScode extensions in on Omega
Open the Code > Settings... > Settings menu
- Select the Remote [SSH: omega] tab
- Search for julia executable in the search bar
- Edit the julia: Executable Path to /fusion/projects/codes/julia/fuse/julia_with_fuse

Now Julia scripts and notebooks can be run directly from this remote VScode session.

Connecting to a Jupyter-lab server running on OMEGA

Connect to omega and launch screen
Note
You can re-connect to an existing screen session with screen -r
If (and only if) you want to run jupyter-lab on a worker node do as follows:
srun --partition=ga-ird --nodes=1 --time=4-00:00:00 --pty bash -l
Note
Use the queue, time, CPU, and memory limits that make the most sense for your application see these instructions for help
Then start the Jupyter lab server from the screen session (screen will keep jupyter running even when you log out)
```
jupyter lab --no-browser --port 55667
```
Copy the token that you see on this session it should look something like token=1f1e0259cbc1..................

On your computer setup your ~/.ssh/config this way (need to do this only once):

Host cybele cybele.gat.com
Hostname cybele.gat.com
User meneghini
Port 2039

Host omegae omega.gat.com
Hostname omega.gat.com
User meneghini
ProxyCommand ssh -q cybele nc %h %p

# change XX to the worker node number you've been assigned to
Host omegaXX omegaXX.gat.com
Hostname omegaXX.gat.com
User meneghini
ProxyCommand ssh -q cybele nc %h %p

On your computer start a tunnel going through cybele to omega
```
ssh -N -L localhost:33445:localhost:55667 omegae
```
Note
Keep this terminal always open. You may need to re-issue this command whenever you put your laptop to sleep.
On your computer open a web browser tab to localhost:33445 to connect to the Jupyter-lab session on omega. Use the token when prompted.

Three ways to run parallel jobs

Keep in mind that each worker node on Omega has 128 CPUs

Screen + Jupyter on the login node, workers on the worker nodes
OK when the master process will not be doing a lot of work, and we need multiple nodes
Here we will use the FUSE.parallel_environment("omega", ...) call.
Screen on the login node, Jupyter and workers on one worker node
OK when the master process will be doing a lot of work, and we don't need more than one node
Here we will use the FUSE.parallel_environment("localhost", ...) call.
Screen on the login node, Jupyter on a worker node, workers on different worker nodes
OK when the master process will be doing a lot of work, and we need multiple nodes
This is more complex, and finicky. Avoid if possible.
Here we will use the FUSE.parallel_environment("omega", ...) call.

Using Revise on Omega

When working on omega it seems ones need to manually trigger revise to pick up code changes:

import Revise
Revise.revise()  # manual trigger

This is even if setting JULIA_REVISE_POLL=1

Using GACODE on Omega with Julia

Julia may be incompatible with some environments and will crash when launched. This is the case for the GACODE environment on Omega. To be able to run both GACODE and Julia on Omega (eg. to run NEO and TGLF) do the following:

module load atom
module unload gcc
module unload env

How the public installation of FUSE works

The FUSE unix module module load fuse does several things:

The julia unix module is loaded, which gives you access to a public Julia installation with your own private "depot" in which each user can add or develop their own packages. The location of this private depot is given by the environment variable JULIA_USER_DEPOT.
The FUSE codebase has been precompiled and made available to Julia via a sysimage. This greatly reduces the time-to-first-execution (TTFX) for many functions in the FUSE code suite, at the expense of "locking" those packages and functions to the versions with which they were compiled.
FUSE is already available when you launch Julia, so there's no need to do Pkg.add("FUSE"). You can simply do using FUSE and being working.
A custom conda installation is made available to you that has Jupyter notebooks with precompiled Julia kernels that include the FUSE sysimage. You can just do jupyter lab to start a Jupyter session and select the desired kernels. There is a kernel with 10 threads meant for the login nodes and one with 40 threads meant for the worker nodes.
Warning
Problem: There's a bug that occurs when a new user first launches one of these Julia + FUSE Jupyter kernels. In your terminal, you will see output about precompiling IJulia, which is expected. Once the precompilation is done, it will report Starting kernel event loops but then the kernel may hang and your notebook may not work. It is unclear why this happens, but it is only the first time for each user.
Solution: Restart the kernel. Occasionally this needs to be done twice, perhaps if you restart too quickly and the precompilation was not finished. In any case, if the problem does not resolve after restarting the kernel twice, reach out to the FUSE developers.