An Automated Scalable Framework for Distributing Radio Astronomy Processing Across Clusters and Clouds
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The Low Frequency Array (LOFAR) radio telescope is an international aperture synthesis radio telescope used to study the Universe at low frequencies. One of the goals of the LOFAR telescope is to conduct deep wide-field surveys. Here we will discuss a framework for the processing of the LOFAR Two Meter Sky Survey (LoTSS). This survey will produce close to 50 PB of data within five years. These data rates require processing at locations with high-speed access to the archived data. To complete the LoTSS project, the processing software needs to be made portable and moved to clusters with a high bandwidth connection to the data archive. This work presents a framework that makes the LOFAR software portable, and is used to scale out LOFAR data reduction. Previous work was successful in pre-processing LOFAR data on a cluster of isolated nodes. This framework builds upon it and and is currently operational. It is designed to be portable, scalable, automated and general. This paper describes its design and high level operation and the initial results processing LoTSS data.
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Mechev, A.P.; Shimwell, T.W.; Plaat, A.; Intema, Huib ; Varbanescu, A.L.; Rottgering, H.J.A. (2019)LOFAR is a leading aperture synthesis telescope operated in the Netherlands with stations across Europe. The LOFAR Two-meter Sky Survey (LoTSS) will produce more than 3000 14 TB data sets, mapping the entire northern sky ...
De Gasperin, F.; Dijkema, T.J.; Drabent, A.; Mevius, M.; Rafferty, D.; Van Weeren, R.; Brüggen, M.; Callingham, J.R.; Emig, K.L.; Heald, G.; Intema, Huib ; Morabito, L.K.; Offringa, A.R.; Oonk, R.; Orrù, E.; Röttgering, H.; Sabater, J.; Shimwell, T.; Shulevski, A.; Williams, W. (2019)Context. New generation low-frequency telescopes are exploring a new parameter space in terms of depth and resolution. The data taken with these interferometers, for example with the LOw Frequency ARray (LOFAR), are often ...
Mechev, A.; Plaat, A.; Oonk, J.; Intema, Hubertus; Röttgering, H. (2018)Modern astronomical data processing requires complex software pipelines to process ever growing datasets. For radio astronomy, these pipelines have become so large that they need to be distributed across a computational ...