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daskserver

Utility to fire up a dask array on computecanada infrastructure. Works with kpy from kslurm to manage python environments.

Instructions

First, start up a job with multiple tasks. Don't use krun for this, as that only starts a job with one task. You want multiple to take full advantage of parallelism. The following command serves as a template, adapt the values to suit your needs:

salloc --nodes 2 --tasks-per-node=2 --mem=16000M --cpus-per-task=3 --time=0-01:00

Then run

daskserver <name of venv>

The venv must be one previously saved via kpy. It needs to have dask and distributed already installed, otherwise this routine will fail. You also need bokeh if you want the dashboard. You can install both via:

pip install 'dask[distributed]' bokeh

The jupyter notebook or python script that will interact with the server should have the exact same venv installed as the dask server to avoid problems. For kjupyter, just use the same venv:

kjupyter --venv <same venv as dask>

Note that the server and workers will run in the background. You'll get control over the terminal back without killing them, but they'll continue to spit output onto the screen. To shut the server down, just exit the slurm job.

exit

Installation

The app is set up to work with pipx:

pipx install git+https://github.com/pvandyken/daskserver

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script to start dask server on graham

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