Active Physics & Astronomy Engineering

SKA Science Data Handling & Processing

In plain English

AI plain-English summary

The Square Kilometre Array (SKA) telescope will produce more raw data each day than the entire global internet traffic, and this project builds the computer system that will make sense of it. The SKA is a massive radio telescope under construction across South Africa and Australia. Its antennas will generate torrents of raw data that are useless without processing. This project funds the Science Data Processor (SDP)—the supercomputing system that will convert that raw data into calibrated images and catalogues, store them for decades, and deliver them to scientists worldwide. Without the SDP, the telescope would produce noise, not science. This is fundamental science infrastructure. The SDP is not a single computer but a distributed system of pipelines that must run reliably at extreme scale. The project covers construction, integration, testing, and commissioning of the hardware and software, plus the ongoing development of faster, more capable processing pipelines. If successful, the SDP will enable the SKA to map the universe in unprecedented detail—tracking galaxy formation, testing gravity, and searching for the first stars. There is no immediate practical application; the value lies in the fundamental discoveries this processing power will unlock.

View original technical description
This project is to support the Science Data Processor (SDP) component of the SKA. The SDP is the element of the telescope responsible for processing various observed data into required data products (which consists of combined and processed raw data together with metadata), long-term preservation of these data products, and delivery of these products to SKAO and scientists working in SKA Regional Centres (SRCs). This project deals with the construction of the SDP system, its support in integration, testing and commissioning, and the development and demonstration of increasingly capable SDP pipeline performance are the key components of this project.

View the original record at the funder ↗

Researchers

Eloy De Lera Acedo (Principal Investigator)Jeremy Coles (Co-Investigator)

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Original classification

Research and Innovation

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