In their study, Kemp et al. explore the use of commercial high-performance computing (HPC) for processing large-scale radio astronomy data, specifically from the GASKAP-Hi pilot surveys. They outline a four-step process for porting workflows from public facilities to commercial providers, and demonstrate how they optimised the pipeline to minimise cost and processing time. Their work highlights the advantages of immediate access and high availability provided by commercial HPC, although they note that a higher level of HPC expertise is required to fully leverage these resources. The findings aim to assist other researchers in using commercial supercomputing for radio astronomy imaging.

The image above displays fields from the GASKAP-Hi Pilot Surveys. Cyan boxes indicate the approximate ASKAP PAF footprint for the pilot phase I fields (20-hour integration), while yellow boxes represent the footprint for the pilot phase II fields (10-hour integration).