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