BwUniCluster2.0/Software/Python Dask: Difference between revisions
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After executing this command with e.g. cluster.scale(5), dask will start to request five worker processes each with the specified amount of cores and memory. |
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Revision as of 11:00, 19 April 2020
This guide explains how to use Python Dask and dask-jobqueue on bwUniCluster2.0.
Installation
Use on of our pre-configured Python modules and load them with 'module load ...'. You have to install the packages 'dask' and 'das-jobqueue' if your are using an own conda environment.
Using Dask
In a new interactive shell, execute the following commands in Python:
>>> from dask_jobqueue import SLURMCluster >>> cluster = SLURMCluster(cores=X, memory='X GB', queue='X')
You have to specify how many cores and memory you want for one dask worker. Furthermore a batch queue is required.
>>> cluster.scale (X)
After executing this command with e.g. cluster.scale(5), dask will start to request five worker processes each with the specified amount of cores and memory.
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