Focus on
SKAO Science Data Challenge 2 MAP OF WORLDWIDE P ARTICIPATION
IRIS (STFC) UK
CSCS Lugano, Switzerland
INAF Rome, Italy
GENCIIDRIS Orsay,France
THE CHALLENGE IN NUMBERS Teams analysing
1TB
ENGAGE SKA - UCLCA Aveiro & Coimbra, Portugal
of astronomical data
280
registered participants in
22
countries
8
China SRC-proto Shanghai, China
IAA-CSIC Granada, Spain
supercomputing centres
15 million
AusSRC & Pawsey Perth, Australia
CPU core hours* and 15 TB RAM available for teams
Participants
Computing facilities
1–5 6–10 11–20 20+
The challenge’s 3D data cube is a series of stacked radio images, each reflecting a different frequency. It shows galaxies across a distance of 4 billion light years. *A core hour refers to the number of processor units (cores) used, multiplied by the duration of the job in hours.
A closer look at the Science Data Challenge 2 BY CASSANDRA CAVALLARO (SKAO)
Late last year, 280 participants in 22 countries registered for the SKAO’s Science Data Challenge 2 (SDC2). Supported by the resources of eight supercomputing facilities around the world, teams were tasked with using computer algorithms to find and analyse nearly 250,000 galaxies in a simulated SKAO data cube.
What was the motivation behind this second Science Data Challenge?
telescopes will provide. Every observatory’s observations have their own characteristics, so these challenges will help people to become familiar with SKAO data and develop their own analysis pipelines to extract science from it in a reasonable time. It will also help astronomers to plan what kind of observations they might do; the sooner they can understand what SKA data will look like, the better they can design their experiments.
PHILIPPA: It’s part of a series we’re running to prepare the community for the huge and complex data sets the SKA
JAMES: The much larger data volumes mean SKAO data will have to be analysed in the cloud through a network of SKA
As the challenge heads towards its conclusion in July, we spoke to two members of the SKAO team involved in organising it, Postdoctoral Fellow for Radio Astronomy Simulations Dr Philippa Hartley and Operations Data Scientist Dr James Collinson, to hear more about its goals.
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