Teams ready for SKA Science Data Challenge 2

Registration is complete for the SKA Science Data Challenge 2, with around 30 teams taking part from more than 60 institutions all over the world.

The challenge will see teams analyse a 1 terabyte (TB) simulated SKA HI data cube, using their own software tools to identify and determine the properties of galaxies across a distance of four billion light years.

An international network of highperformance computing centres are a crucial element to the challenge, providing access, processing and storage for the data. This is similar to how the SKA Observatory will disseminate the telescopes’ data via SKA Regional Centres (SRCs) in the future.

Eight facilities are involved, including two prototype SRCs: IRIS UK (part of the UK Science and Technology Facilities Council), SKA France, Shanghai proto-SRC, Australia proto-SRC, Italy’s National Institute for Astrophysics - Information and Communications Technologies (ICT), Institute for Astrophysics of Andalucía (IAA) in Spain, ENGAGE-SKA in Portugal, and the Swiss National Supercomputing Centre (CSCS).

“The external SRC network will be how the SKA Observatory interacts with our user community, so beginning to put this idea into practice via the Data Challenge is an important step in demonstrating how this will work effectively as a system,” says SKA Science Director Dr Robert Braun. “It has also strengthened links between these facilities. We’ve had their representatives together in a virtual room discussing provision and access, which is something we have never had before now.”

Through December teams will each be given access to one of the computing facilities, ready for the challenge to formally kick off on 15 January. The results are due to be announced in July 2021. Feedback from participants and the computing centres will be used to further inform work on the SRC model. SKAO is also encouraging best practice by working with the UK-based Software Sustainability Institute to give awards to teams that demonstrate reproducibility (using methods that can be replicated by others to achieve the same results). Reproducibility lies at the heart of the SKA’s Open Science approach to its future operations. Making software processing techniques open in this way means they can also be built on for other, different purposes in the future.

By SKAO

Above: Map of high-performance computing centres involved in SDC2. Eight facilities are involved, including two prototype SRCs.

Credit: SKAO/Philippa Hartley