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Model-based Performance Characterization of Software Correlators for Radio Interferometer Arrays
by
Fish, V. L.
, Ruszczyk, C. A.
, Elosegui, P.
, Lonsdale, C. J.
, Crew, G. B.
, Vázquez, A. J.
in
Astronomy
/ Astronomy software
/ Correlation
/ Design
/ Distributed computing
/ Field programmable gate arrays
/ Geodesy
/ Interferometers
/ Interferometric correlation
/ Interferometry
/ Modelling
/ Radio astronomy
/ Radio interferometry
/ Software
/ Theoretical models
2022
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Model-based Performance Characterization of Software Correlators for Radio Interferometer Arrays
by
Fish, V. L.
, Ruszczyk, C. A.
, Elosegui, P.
, Lonsdale, C. J.
, Crew, G. B.
, Vázquez, A. J.
in
Astronomy
/ Astronomy software
/ Correlation
/ Design
/ Distributed computing
/ Field programmable gate arrays
/ Geodesy
/ Interferometers
/ Interferometric correlation
/ Interferometry
/ Modelling
/ Radio astronomy
/ Radio interferometry
/ Software
/ Theoretical models
2022
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Do you wish to request the book?
Model-based Performance Characterization of Software Correlators for Radio Interferometer Arrays
by
Fish, V. L.
, Ruszczyk, C. A.
, Elosegui, P.
, Lonsdale, C. J.
, Crew, G. B.
, Vázquez, A. J.
in
Astronomy
/ Astronomy software
/ Correlation
/ Design
/ Distributed computing
/ Field programmable gate arrays
/ Geodesy
/ Interferometers
/ Interferometric correlation
/ Interferometry
/ Modelling
/ Radio astronomy
/ Radio interferometry
/ Software
/ Theoretical models
2022
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Model-based Performance Characterization of Software Correlators for Radio Interferometer Arrays
Journal Article
Model-based Performance Characterization of Software Correlators for Radio Interferometer Arrays
2022
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Overview
Correlation for radio interferometer array applications, including Very Long Baseline Interferometry (VLBI), is a multidisciplinary field that traditionally involves astronomy, geodesy, signal processing, and electronic design. In recent years, however, high-performance computing has been taking over electronic design, complicating this mix with the addition of network engineering, parallel programming, and resource scheduling, among others. High-performance applications go a step further by using specialized hardware like Graphics Processing Units (GPUs) or Field Programmable Gate Arrays (FPGAs), challenging engineers to build and maintain high-performance correlators that efficiently use the available resources. Existing literature has generally benchmarked correlators through narrow comparisons on specific scenarios, and the lack of a formal performance characterization prevents a systematic comparison. This combination of ongoing increasing complexity in software correlation together with the lack of performance models in the literature motivates the development of a performance model that allows us not only to characterize existing correlators and predict their performance in different scenarios but, more importantly, to provide an understanding of the trade-offs inherent to the decisions associated with their design. In this paper, we present a model that achieves both objectives. We validate this model against benchmarking results in the literature, and provide an example for its application for improving cost-effectiveness in the usage of cloud resources.
Publisher
The Astronomical Society of the Pacific,IOP Publishing
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