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SC20_pyHPC

  • SC'2020
  • pyHPC workshop
  • distributed computing on HPC systems and the cloud
  • dask, jupyter, itk, scikit-image, xarray, zarr, itkwidgets
  • applications and best practices for using such libraries

- Ushizima, McCormick, Parkinson Accelerating Microstructural Analytics with Dask for Volumetric X-ray Images [preprint]

- Explore Code Samples [code]

- Attention: conda install -c conda-forge jupyterlab=2.0

- 3D Data Specimens:

  • [Concrete]
  • [Fibers]
  • [Beads]

    - Python Cluster Configuration:

  • [NERSC MPI]
  • [Coiled.io Cloud]

    • Please reference us:

    @InProceedings{SC:2020,
author = {Daniela Ushizima and Matthew McCormick and Dilworth Parkinson},
title = {Accelerating Microstructural Analytics with Dask for Volumetric X-ray Images},
booktitle = {2020 IEEE/ACM 9th Workshop on Python for High-Performance and Scientific Computing (PyHPC) at Super Computing},
month = {Nov},
year = {2020},
pages = {41-48},
}

    Organizing Committee

    • William Scullin, Laboratory for Laser Energetics, University of Rochester
    • Neelofer Banglawala, EPCC, University of Edinburgh (EPCC)
    • Rosa M. Badia, Barcelona Supercomputing Centre
    • James Clark, Hartree Centre - UK Research and Innovation