Posts tagged jupyterhub
- 05 January 2021
Slurm config on Mistral has been updated to fix an issue related to memory use.
Prior the update, some Slurm jobs continue consuming the available
memory (and even swap) of the allocated node and exceed the allocated
memory (set in
srun). If this occurs, it also affect
- 16 November 2020
According to the official Web site,
Dask jobqueue can be used to
deploy deploy Dask on job queuing systems like PBS, Slurm, MOAB, SGE,
LSF, and HTCondor. Since the queuing system on Mistral is Slurm, we are
going to show how to start a Dask cluster there. The idea is simple as
described here. The difference is that the workers can be distributed
through multiple nodes from the same partition. Using Dask jobqueue will
Dask cluster as a Slurm jobs.
In this case, Jupyterhub will often play an interface role and the Dask can use more than the allocated resources to your jupyterhub session (profiles).
- 13 November 2020
Extensions bring additional interesting features to Jupyter*. Depending on the workflow in the notebook, users can install/enable extensions when required. Although is easy to add extensions to both Jupyter notebook an lab, the process can be sometimes annoying based on where jupyter is served from.
In general, installing and enabling extensions in your laptop or using
start-jupyter script is straightforward, especially when the
developers well describe their extensions. There should be no
restrictions or permissions issues, just follow the instructions.
- 05 November 2020
can’t use NCL (Python) as kernel in Jupyter
This tutorial won’t work
- 07 October 2020
created your own conda env
- 05 October 2020
We introduced a new feature to the preset and advanced options form.
This is a nice feature especially for the advanced options form, which
contain many fields. You can also reset the options to their initial
values by clicking on
reset. The form options are saved in the
client’s browser every 10 seconds and are not lost if:
the browser crashes
- 25 September 2020
Each Jupyter notebook is running as a SLUM job on MIstral. By default,
stderr of the SLURM batch job that is spawned by
Jupyterhub is written to your
HOME directory on the HPC system. In
order to make it simple to locate the log file:
if you use the
preset options form: the log file is named
- 18 September 2020
There are multiple ways to create a dask cluster, the following is only an example. Please consult the official documentation. The Dask library is installed and can be found in any of the python3 kernels in jupyterhub. Of course, you can use your own python environment.
The simplest way to create a Dask cluster is to use the distributed module: