A Chinese team using the world's fastest supercomputer to simulate a devastating earthquake won the 2017 ACM Gordon Bell Prize on Thursday.
The Association for Computing Machinery said using the Sunway TaihuLight, the fastest supercomputer, the team developed software that was able to process data at the speed of 18.9 quadrillion calculations per second, and create 3D visualizations related to a devastating earthquake that occurred in Tangshan, a city in northeastern China, in 1976.
"The team's software included innovations that achieved greater efficiency than had been previously attained running similar programs on the Titan and TaihuLight supercomputers," the association said.
The award was presented at the 2017 Supercomputing Conference in Denver in the U.S. state of Colorado.
"Although earthquake prediction and simulation is an inexact and emerging area of research, we hope that the use of supercomputers may lead to better prediction and preparedness," He Conghui, one of the 12-member Chinese team, told Xinhua.
Chinese supercomputer Sunway TaihuLight, located at the National Supercomputer Center in Wuxi in China's eastern province of Jiangsu, is nearly three times faster than the Tianhe-2, the supercomputer that previously held the world record for speed.
The Gordon Bell Prize, carrying a purse of $10,000 and awarded at the annual supercomputing conference, was established in 1987 by Gordon Bell, an American pioneer in high-performance and parallel computing.
It tracks the progress of parallel computing and rewards innovation in applying high-performance computing to challenges in science, engineering, and large-scale data analytics.
"It was very impressive ... The progress has been very strong and will continue," Bell said, commenting on China's progress in supercomputer applications.
This is the second time that Chinese researchers scooped the "Nobel Prize" of supercomputing applications.
Last year, Chinese researchers won the award for developing a method for calculating atmospheric dynamics that can be used to improve global climate models as well as weather predictions.