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| Paper: |
Radio Astronomy Application Parallelism with Dask and Numba |
| Volume: |
532, ASTRONOMICAL DATA ANALYSIS SOFTWARE AND SYSTEMS XXX |
| Page: |
605 |
| Authors: |
Perkins, S.; Masoka, S.; 1; Bester, 3. L.; 1; Smirnov, 3. O.; 1; 3; Marais, P. |
| Abstract: |
Dask is a lightweight Python parallelisation and distribution framework
that seamlessly integrates with the PyData ecosystem to provide
a rich framework for developing Parallel and Distributed Radio Astronomy Applications.
In this paper, we describe three simulations performed during a live demonstration in which a Radio Astronomy “Dirty” image is created from three different sources of visibility data on a ten node cluster. |
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