Abdulaziz, A.

Dabbech, A.

Jackson, A.

Jiang, M.

Repetti, A.

Thiran, J.-P.

Thouvenin, P.-A.

Wiaux, Y.

English

Upcoming radio interferometers are aiming to image the sky at new levels of resolution and sensitivity, with wide- band image cubes reaching close to the Petabyte scale for SKA. Modern proximal optimization algorithms have shown a potential to significantly outperform CLEAN thanks to their ability to inject complex image models to regularize the inverse problem for image formation from visibility data. They were also shown to be paralleliz- able over large data volumes thanks to a splitting functionality enabling the decomposition of data into blocks, for parallel processing of block-specific data-fidelity terms involved in the objective function. In this work, the split- ting functionality is further exploited to decompose the image cube into spatio-spectral facets, and enable parallel processing of facet-specific regularization terms in the objective. The resulting “Faceted HyperSARA” algorithm is implemented in MATLAB (code available on the Puri-Psi webpage [1]). Simulation results on synthetic image cubes confirm that faceting can provide a major increase in parallelization capability when compared to the origi- nal HyperSARA approach, at a negligible cost in imaging quality. A proof-of-concept reconstruction of a 15 GB image of Cyg A from 7.4 GB of JVLA data, utilizing 496 CPU cores on a HPC system for 53 hours, illustrates the reconstruction performance of the proposed approach on real data. We also demonstrate that Faceted HyperSARA can be combined with a dimensionality reduction technique, enabling utilizing only 31 CPU cores for approxi- mately the same time to form the Cyg A image from the same data, while preserving reconstruction quality. This abstract summarizes a full paper by the authors [2].<br/

Thouvenin, Pierre-Antoine

Abdulaziz, Abdullah

Jiang, Ming

Dabbech, Arwa

Repetti, Audrey

Jackson, Adrian

Thiran, Jean-Philippe

Wiaux, Yves

Heriot Watt Pure

Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA)

Edinburgh Research Explorer

     Edinburgh Research Explorer                                      Parallel faceted imaging in radio interferometry via proximalsplitting (Faceted HyperSARA)Citation for published version:Thouvenin, P-A, Abdulaziz, A, Jiang, M, Dabbech, A, Repetti, A, Jackson, A, Thiran, J-P & Wiaux, Y 2021,'Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA)', 34th GeneralAssembly and Scientific Symposium of the International Union of Radio Science, Rome, Italy, 28/08/21 -4/09/21.Link:Link to publication record in Edinburgh Research ExplorerDocument Version:Peer reviewed versionGeneral rightsCopyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)and / or other copyright owners and it is a condition of accessing these publications that users recognise andabide by the legal requirements associated with these rights.Take down policyThe University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorercontent complies with UK legislation. If you believe that the public display of this file breaches copyright pleasecontact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately andinvestigate your claim.Download date: 23. Feb. 2022URSI GASS 2021, Rome, Italy, 28 August - 4 September 2021Parallel faceted imaging in radio interferometry via proximal splitting (FacetedHyperSARA)P.-A. Thouvenin(1), A. Abdulaziz(2), M. Jiang(3), A. Dabbech(2), A. Repetti(2), A. Jackson(4), J.-P. Thiran(5), andY. Wiaux*(2)(1) Univ. Lille, CNRS, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France(2) Institute of Sensors, Signals and Systems, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom(3) National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China(4) EPCC, University of Edinburgh, Edinburgh EH8 9BT, United Kingdom(5) Signal Processing Laboratory, École Polytechnique Fédérale de Lausanne, CH-1015, Lausanne, SwitzerlandUpcoming radio interferometers are aiming to image the sky at new levels of resolution and sensitivity, with wide-band image cubes reaching close to the Petabyte scale for SKA. Modern proximal optimization algorithms haveshown a potential to significantly outperform CLEAN thanks to their ability to inject complex image models toregularize the inverse problem for image formation from visibility data. They were also shown to be paralleliz-able over large data volumes thanks to a splitting functionality enabling the decomposition of data into blocks, forparallel processing of block-specific data-fidelity terms involved in the objective function. In this work, the split-ting functionality is further exploited to decompose the image cube into spatio-spectral facets, and enable parallelprocessing of facet-specific regularization terms in the objective. The resulting “Faceted HyperSARA” algorithmis implemented in MATLAB (code available on the Puri-Psi webpage [1]). Simulation results on synthetic imagecubes confirm that faceting can provide a major increase in parallelization capability when compared to the origi-nal HyperSARA approach, at a negligible cost in imaging quality. A proof-of-concept reconstruction of a 15 GBimage of Cyg A from 7.4 GB of JVLA data, utilizing 496 CPU cores on a HPC system for 53 hours, illustrates thereconstruction performance of the proposed approach on real data. We also demonstrate that Faceted HyperSARAcan be combined with a dimensionality reduction technique, enabling utilizing only 31 CPU cores for approxi-mately the same time to form the Cyg A image from the same data, while preserving reconstruction quality. Thisabstract summarizes a full paper by the authors [2].References[1] https://basp-group.github.io/Puri-Psi/.[2] P.-A. Thouvenin, A. Abdulaziz, M. Jiang, A. Dabbech, A. Repetti, A. Jackson, J.-P. Thiran, and Y. Wiaux,“Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA),” submitted toMonthly Notices of the Royal Astronomical Society, February 2020, preprint arXiv:2003.07358 [astro-ph.IM].

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Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA)

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