BwUniCluster2.0/Software/Python Dask: Difference between revisions
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This guide explains how to use Python Dask and dask-jobqueue on bwUniCluster2.0. |
This guide explains how to use Python Dask and dask-jobqueue on bwUniCluster2.0. |
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== Installation == |
== Installation and Usage == |
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Please have a look at our [https://github.com/hpcraink/workshop-parallel-jupyter Workshop] on how to use Dask on bwUniCluster2.0 (2_Grundlagen: Environment erstellen and 6_Dask). This is currently only available in German. |
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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 yousing an own conda environment. |
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== Using Dask == |
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In a new interactive shell, execute the following commands in Python: |
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<pre> |
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>>> from dask_jobqueue import SLURMCluster |
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>>> cluster = SLURMCluster(cores=X, memory='X GB', queue='X') |
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</pre> |
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You have to specify how many cores and memory you want for one dask worker. |
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<pre> |
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>>> cluster.scale (X) |
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</pre> |
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Replace |
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[[Category:bwUniCluster_2.0|Access]][[Category:Access|bwUniCluster 2.0]] |
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Latest revision as of 11:46, 27 February 2024
This guide explains how to use Python Dask and dask-jobqueue on bwUniCluster2.0.
Installation and Usage
Please have a look at our Workshop on how to use Dask on bwUniCluster2.0 (2_Grundlagen: Environment erstellen and 6_Dask). This is currently only available in German.