There is a newer version of daskDask provides multi-core execution on larger-than-memory datasets using blocked algorithms and task scheduling.
Accessing dask 2.3.0-foss-2019a-Python-3.7.2
To load the module for dask 2.3.0-foss-2019a-Python-3.7.2 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load dask/2.3.0-foss-2019a-Python-3.7.2
There is a GPU enabled version of this module: dask 2.3.0-fosscuda-2019a-Python-3.7.2
BEAR Apps Version
EL8-cascadelake — EL8-haswell — Ubuntu20.04-haswell
The listed architectures consist of two part: OS-CPU.
- BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
- BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.
- cloudpickle 1.2.1
- dask 2.3.0
- distributed 2.3.0
- docrep 0.2.7
- fsspec 0.4.1
- HeapDict 1.0.0
- locket 0.2.0
- msgpack 0.6.1
- partd 1.0.0
- sortedcontainers 2.1.0
- tblib 1.4.0
- toolz 0.10.0
- zict 1.0.0
For more information visit the dask website.
This version of dask has a direct dependency on: bokeh/1.3.4-foss-2019a-Python-3.7.2 foss/2019a Python/3.7.2-GCCcore-8.2.0 PyYAML/5.1-GCCcore-8.2.0 SciPy-bundle/2019.03-foss-2019a
This version of dask is a direct dependent of: scikit-image/0.15.0-foss-2019a-Python-3.7.2 xESMF/0.2.1-foss-2019a-Python-3.7.2
These versions of dask are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.
Last modified on 21st August 2019