Imaging SKA-Scale data in three different computing environments

TL;DR

This study evaluates the performance and costs of three different computing environments—cluster, HPC, and cloud—for processing large-scale radio astronomy data in preparation for SKA, highlighting their respective strengths and limitations.

Contribution

It provides a comparative analysis of three computing platforms for SKA-scale data imaging, demonstrating the feasibility of using HPC and cloud solutions for large-scale radio astronomy data processing.

Findings

All platforms successfully completed imaging pipeline processing.

HPC and cloud platforms show potential for SKA data processing.

Performance and cost trade-offs are critical for planning.

Abstract

We present the results of our investigations into options for the computing platform for the imaging pipeline in the CHILES project, an ultra-deep HI pathfinder for the era of the Square Kilometre Array. CHILES pushes the current computing infrastructure to its limits and understanding how to deliver the images from this project is clarifying the Science Data Processing requirements for the SKA. We have tested three platforms: a moderately sized cluster, a massive High Performance Computing (HPC) system, and the Amazon Web Services (AWS) cloud computing platform. We have used well-established tools for data reduction and performance measurement to investigate the behaviour of these platforms for the complicated access patterns of real-life Radio Astronomy data reduction. All of these platforms have strengths and weaknesses and the system tools allow us to identify and evaluate them in a quantitative manner. With the insights from these tests we are able to complete the imaging pipeline processing on both the HPC platform and also on the cloud computing platform, which paves the way for meeting big data challenges in the era of SKA in the field of Radio Astronomy. We discuss the implications that all similar projects will have to consider, in both performance and costs, to make recommendations for the planning of Radio Astronomy imaging workflows.