Abstract
Unlike optical telescopes, radio interferometers do not image the sky directly but require specialized image formation algorithms. For the Square Kilometre Array (SKA), the computational requirements of this image formation are extremely demanding due to the huge data rates produced by the telescope. This processing will be performed by the SKA Science Data Processor facilities and a network of SKA Regional Centres, which must not only deal with SKA-scale data volumes but also with stringent science-driven image fidelity requirements.This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.
Highlights
Typical images will have spatial axes with pixels on a side and up to frequency channels, more often this frequency axis will be compressed to three Taylor term coefficients which can concisely express the continuum frequency behaviour of astrophysical radio emission mechanisms. This dimensionality results in petabyte scale volumes for individual data products, and when the data products required for the Square Kilometre Array (SKA) high-priority science objectives are considered on average they are expected to result in outputs equivalent to approximately 300 PB per telescope per year during full science operations, resulting in an archive of approximately 8.5 Exabytes over the 15-year lifespan of the initial high-priority science programmes [1]
Even without considering the added complexities in the calibration and imaging process that are described in the previous section, the Fourier nature of the measurements in radio interferometry makes SKA data processing computationally challenging
The refinements to the basic imaging process such as iterative direction-dependent calibration, deconvolution and convolutional gridding increase the number of Fourier transforms required to create science ready data products, and add in additional processing
Summary
Cite this article: Scaife AMM. 2020 Big telescope, big data: towards exascale with the Square Kilometre Array. 2020 Big telescope, big data: towards exascale with the Square Kilometre Array. One contribution of 15 to a discussion meeting issue ‘Numerical algorithms for high-performance computational science’. For the Square Kilometre Array (SKA), the computational requirements of this image formation are extremely demanding due to the huge data rates produced by the telescope. This processing will be performed by the SKA Science Data Processor facilities and a network of SKA Regional Centres, which must deal with SKA-scale data volumes and with stringent science-driven image fidelity requirements. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’
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