The Web Portal for Hábrók is now available, but some functionality is still lacking. For instance, the interactive apps for TensorFlow and PyTorch are not available yet.
We have implemented a new web portal for Hábrók, based on software developed at the Ohio Supercomputer Center, called OpenOnDemand (affectionately known as OOD). Using your username and password, just as you would do on Hábrók, you can log in to this portal at the following address:
Important to know is that the “Log Out” menu item doesn’t do what you would expect, i.e. log you out. To actually log out, you would have to close the browser session, which is why the developers of OpenOnDemand suggest using the incognito/private mode of your preferred browser.
Once logged in, you will be presented with a dashboard.
Here, in addition to the “Message of the Day” that you see when you ssh
into Hábrók, we will also display messages relevant only to the web portal (such as any planned maintenance of the portal).
The menu has several items, the most useful ones being:
In the Files
menu you have access to your home, /projects
and /scratch
folders, as well as any group folders in /scratch
for groups you belong to, and which are named as hb-<group-name>
. When accessing any of the submenus in Files
, the corresponding folder will be opened in a file explorer in a new browser tab. From here you can navigate, perform file operations (copy, delete, etc.), view and even edit files (the file editor has syntax highlighting for a large number of text file formats).
In the Jobs
menu, there are two subitems: Active Jobs
and Job Composer
. The Job Composer
allows you to define a submit a job directly from the web portal, but at the moment it is a bit cumbersome and counter-intuitive in our opinion, so we do not recommend using it just yet. The Active Jobs
provides an overview of jobs on the cluster, either for yourself or all users. It is similar to the squeue
from the command line.
This menu provides shell access to the Hábrók login and interactive nodes directly in your web browser! There’s not much to say about this, it gives you all the functionality that you have from the command line.
This is where things become more interesting. At the moment we have a single interactive app (with more to come), which you can launch as jobs from this menu:
This app will launch a Jupyter notebook on a compute node and will allow you to connect to it and run notebooks. It currently only supports Python 3.10.4.
You can now also choose which filesystem Jupyter starts in, through a dropdown box. Currently the only options are /scratch/$USER
and any other group directory you have in /scratch
.
Before launching the Jupyter notebook, this interactive app loads the module: IPython (versions vary). Since this is just a basic Python, you might want to build you own virtual environments and have them available in the Jupyter notebook.
Building the Python virtual environment
We suggest you put your Python virtual environment in your home directory, rather than /scratch
, since the number of files can be quite high, particularly if you have several virtual environments. Before building the virtual environment, you need to load the appropriate module:
module load <ipython_version>
where <ipython_version>
should be replaced by the appropriate IPython version. We support the following versions:
<ipython_version> = IPython/8.5.0-GCCcore-11.3.0
for Python 3.10.4
<ipython_version> = IPython/7.26.0-GCCcore-11.2.0
for Python 3.8.16
Now build a virtual environment in $HOME/venvs
:
python3 -m venv $HOME/venvs/my_env
Activate the virtual environment you just built:
source $HOME/venvs/my_env/bin/activate
It is advisable to upgrade the version of pip for you new virtual environment, to suppress the warning that you will get anytime you install a new package. Also installing or updating the wheels
and setuptools
modules is required.
pip install --upgrade pip wheel setuptools
Before you are able to build a Jupyter Notebook kernel for your new virtual environment, there are a few additional packages that you need to install:
pip install tomlkit jupyter-contrib-core
Finally, you can generate a Jupyter Notebook kernel from this virtual environment:
python -m ipykernel install --user --name=my_env
You can check that the kernel has been properly generated by having a look at its file, which is usually in $HOME/.local/share/jupyter/kernels/my_env/kernel.json
. If you see a reference to your virtual environment in this file, something like $HOME/venvs/my_env/bin/python
, this means that everything is properly set up.
That's it! You now have access to the virtual environment you've just built from the Jupyter Notebook (note that you may need to reload the Jupyter web page), through a kernel named my_env
(You can, of course, use any name you please).
Any packages you install in this virtual environment will be available from the Jupyter Notebook immediately. We suggest you use a requirements.txt
file to keep track of the packages you've installed.
The Remote Desktop app will launch a graphical desktop environment (based on (MATE) on a compute node, allowing you to interactively run tools with a graphical user interface with some more resources than what's available on the login/interactive nodes. By submitting to the gpu
partition, you can even make use of a GPU and do OpenGL hardware rendering. The desktop environment itself has some tools like a web browser, text editors, and terminal available, but in a terminal you can also make use of all the modules. This would allow you to run tools like MATLAB, Mathematica, ParaView, or VMD.
The Web Portal is still in the test phase, and we would appreciate if you send any feedback you have to hpc@rug.nl, with the subject line including “OOD Portal”.
Enjoy the Web Portal!