Multi-scale CLEAN memory utilisation challenges at square kilometre array scale

Deconvolution is a very important tool in radio astronomy, used to remove the point spread function from the image produced by an interferometer. Currently popular convolution algorithms are up to 50 years old and were designed for much smaller instruments than are currently being constructed. At im...

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Main Authors: Wright, D, Adamek, K, Armour, W
Format: Conference item
Language:English
Published: IEEE 2024
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author Wright, D
Adamek, K
Armour, W
author_facet Wright, D
Adamek, K
Armour, W
author_sort Wright, D
collection OXFORD
description Deconvolution is a very important tool in radio astronomy, used to remove the point spread function from the image produced by an interferometer. Currently popular convolution algorithms are up to 50 years old and were designed for much smaller instruments than are currently being constructed. At image sizes proposed for the Square Kilometre Array (SKA), in this paper we show that the com- monly used msCLEAN algorithm developed by Cornwell requires up to 13TB of memory to successfully run. We detail the steps of the msCLEAN algorithm and the incremental memory usage for each. We also propose some memory reduction techniques to improve performance.
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spelling oxford-uuid:b3561808-e8ca-4f89-8cad-625da6def5d62024-08-05T10:10:28ZMulti-scale CLEAN memory utilisation challenges at square kilometre array scaleConference itemhttp://purl.org/coar/resource_type/c_5794uuid:b3561808-e8ca-4f89-8cad-625da6def5d6EnglishSymplectic ElementsIEEE2024Wright, DAdamek, KArmour, WDeconvolution is a very important tool in radio astronomy, used to remove the point spread function from the image produced by an interferometer. Currently popular convolution algorithms are up to 50 years old and were designed for much smaller instruments than are currently being constructed. At image sizes proposed for the Square Kilometre Array (SKA), in this paper we show that the com- monly used msCLEAN algorithm developed by Cornwell requires up to 13TB of memory to successfully run. We detail the steps of the msCLEAN algorithm and the incremental memory usage for each. We also propose some memory reduction techniques to improve performance.
spellingShingle Wright, D
Adamek, K
Armour, W
Multi-scale CLEAN memory utilisation challenges at square kilometre array scale
title Multi-scale CLEAN memory utilisation challenges at square kilometre array scale
title_full Multi-scale CLEAN memory utilisation challenges at square kilometre array scale
title_fullStr Multi-scale CLEAN memory utilisation challenges at square kilometre array scale
title_full_unstemmed Multi-scale CLEAN memory utilisation challenges at square kilometre array scale
title_short Multi-scale CLEAN memory utilisation challenges at square kilometre array scale
title_sort multi scale clean memory utilisation challenges at square kilometre array scale
work_keys_str_mv AT wrightd multiscalecleanmemoryutilisationchallengesatsquarekilometrearrayscale
AT adamekk multiscalecleanmemoryutilisationchallengesatsquarekilometrearrayscale
AT armourw multiscalecleanmemoryutilisationchallengesatsquarekilometrearrayscale