[November 16, 2020] "Processing full-scale Square Kilometre Array workflow on the Summit supercomputer", with the participation of Professor Tao An and Mr. Baoqiang Lao of the Shanghai Astronomical Observatory (SHAO), Chinese Academy of Sciences (CAS), is in the finalist for the 2020 Gordon Bell Prize^[1], the highest awards in the field of high performance computing (HPC). The final results of the 2020 Gordon Bell Prize will be announced at the International Conference on Supercomputing, to be held in the United States on 19 November (20 November Beijing Time).

The Square Kilometre Array (SKA) is the largest radio telescope to be built, consisting of more than 2,000 dish antennas, millions of log-periodic antennas and hundreds of dense aperture arrays, which will open up a new era of the exploration of the Universe. The SKA will achieve extremely high sensitivity with its large collecting area, high spatial resolution with a maximum baseline of thousands of kilometers, fine temporal signals with nanosecond sampling, and generate data flow at rates of up to 10 peta bit per second that exceed the total capacity of the current global Internet. One of the key bottlenecks of the SKA is how to properly process the SKA big data, as it is tied to whether the SKA can achieve the expected scientific breakthrough.

The construction of SKA will start in 2021, the first phase of the project (SKA1) is expected to be completed in 2029, and SKA's data processing system has entered the critical engineering validation and implementation stage. The SKA data processing is carried out in a real-time mode, thus requiring the workflow to have a high level of stability, scalability and energy consumption. The pre-processed data is transmitted via high-speed broadband internet to several regional data centers located in major member countries for in-depth analysis, and scientists primarily conduct scientific research based on the regional data centers.

The team exceeded expectations by simulating and processing the complete data processing workflow of the SKA1 low-frequency telescope. That includes a real-time pipeline of observational data generation, acquisition, correlation, calibration, and imaging, using Summit, the world's fastest supercomputer at the time, developed by IBM and operated by Oak Ridge National Laboratory. The Summit’s computation power,  up to 200 peta flops (Pflops for short), is comparable to that of the supercomputer of the SKA1 and is the best platform to validate the SKA data processing system. The paper describes in detail the breakthroughs made in the execution framework, parallelized input/output (I/O) and scaling-up execution of the SKA data processing system.

The experiments are oriented to the key science project of SKA "Exploration of the Era of the Cosmic Re-ionization", using the sky model obtained by combining observational data and theoretical calculations, together with the design configuration of the SKA1 low-frequency telescope array (including 512 stations, each station has 256 antennas, so the total number of antennas is 131,072). The volume of the generated data reaches 2.6 petaByte (PB). This data mimic the observations at the frequency range 46-221MHz, requiring a total of 27,648 GPUs, using 99% of Summit's resources.