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Interactive Supercomputing with Jupyter and DASK

Anderson Banihirwe from NCAR

In this video from SciPy 2019, Anderson Banihirwe from NCAR presents: Interactive Supercomputing with Jupyter and DASK.

This talk demonstrates how to use Dask and Jupyter on large high-performance computing (HPC) systems to scale and accelerate large interactive data analysis tasks — effectively turning HPC systems into interactive big-data platforms. We will introduce dask-jobqueue which allows users to seamlessly deploy and scale dask on HPC clusters that use a variety of job queuing systems such as PBS, Slurm, SGE, and LSF. We will also introduce dask-mpi, a Python package that makes deploying Dask easy from within a distributed MPI environment.

SciPy is a community dedicated to the advancement of scientific computing through open source Python software for mathematics, science, and engineering. The annual SciPy Conference allows participants from all types of organizations to showcase their latest projects, learn from skilled users and developers, and collaborate on code development.

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