A global weather prediction model built by KAUST researchers has been nominated for the Gordon Bell Prize for outstanding achievements in high-performance computing.
The award honors innovative computing in science, engineering and large-scale data analytics, which is used in environmental modeling. “Climate prediction models require the fastest computers in the world,” says Rabab Alomairy, a specialist in optimizing computer models for scientific applications. As part of her Ph.D. at KAUST, she joined a multidisciplinary team led by KAUST faculty David Keyes, which has built ExoGeoStat, a global weather prediction model powered by the world’s second fastest supercomputer, Fugaku, at RIKEN in Japan.
Before moving into environmental prediction models, Alomairy had worked in acoustic scattering, fluid dynamics and bioinformatics. Her role in this project was to scale up the underlying mathematical models of existing geostatistical models to make them compatible with both current and future supercomputers; Keyes provided invaluable support throughout. “He is an expert in applied mathematics who understands the needs of climate scientists,” says Alomairy. “He connected me with the right people, such as Hatem Ltaief – a specialist in high-performance algorithms who helped me build the linear algebra models – and Sameh Abdullah who built the statistical models.”
Alomairy was one of the few team members entrusted to run their code in Fugaku. “Each run on a supercomputer can cost tens of thousands of dollars in operational costs, facility staff time and electricity bills,” says Keyes, “so each run must be painstakingly prepared and monitored to avoid wasting a precious resource on a failed or irrelevant run.” The latest version of ExoGeoStat can process weather data from 10 million locations in 90 minutes, compared with 18 hours for previous models, and uses it to predict phenomena such as wind, temperature and rainfall.
For Alomairy, submitting the work to the Gordon Bell Prize was an achievement in itself. “Participating in the awards was originally just a dream, but KAUST is a highly motivational place, and people encouraged me to enter,” she says. “It felt like breaking the first barrier of something I thought was impossible, and when I heard we were finalists, I felt like I could challenge myself even further.”
Read the full text at KAUST INSIGHT.