An interactive parallelization framework which is especially useful in configuring data science workload distribution. Eg. supports openMIP, MPI runs on High Performance Clusters
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Interactive Parallel Computing with IPython
ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scripts for controlling clusters for Jupyter.
ipyparallel contains the following CLI scripts:
- ipcluster - start/stop a cluster
- ipcontroller - start a scheduler
- ipengine - start an engine
pip install ipyparallel
To enable the
IPython Clusters tab in Jupyter Notebook:
ipcluster nbextension enable
To disable it again:
ipcluster nbextension disable
See the documentation on configuring the notebook server
to find your config or setup your initial
To install for all users on JupyterHub, as root:
jupyter nbextension install --sys-prefix --py ipyparallel jupyter nbextension enable --sys-prefix --py ipyparallel jupyter serverextension enable --sys-prefix --py ipyparallel
Start a cluster:
Use it from Python:
import os import ipyparallel as ipp rc = ipp.Client() ar = rc[:].apply_async(os.getpid) pid_map = ar.get_dict()
See the docs for more info.