Japanese Supercomputer Shows How Coronavirus Spreads in Humid Conditions
Fugaku reveals how humidity can affect the spread of the coronavirus
A few weeks ago, a Japanese computer revealed how local conditions influence the spread of coronavirus. Scientists used the world’s most powerful supercomputer, the Arm-based Fugaku system at Japan’s Riken Center for Computational Science, to find that humidity plays an important role in spreading the COVID-19. The study found that fewer droplets are dispersed when humidity is higher, which suggests that the use of humidifiers in indoor settings may help limit infections if window ventilation is not possible. Since the virus spreads much more quickly in drier, indoor conditions, it means more infection rates during the upcoming winter months.
According to the study published in mid-October by Riken in collaboration with Japan’s Kobe University, the supercomputer was used to simulate the flow of virus-like particles under varying indoor conditions some pretty interesting new information about the nature of the novel coronavirus. As per the findings, an air humidity level of less than 30% resulted in more than double the amount of aerosols carrying the virus to spread around the room when compared to levels of 60% or higher. Earlier, an MIT study in March had also suggested that higher humidity could slow the novel coronavirus’s spread.
Fugaku research also revealed that while dining, people are at more risk of contracting COVID-19 from others on the side, not to their front. The airflow simulations also revealed that face shields are actually much less effective at keeping the coronavirus aerosols at bay than face masks are. Fugaku is the product of a $1 billion, decade-long mission by several thousand developers from the government-run Riken Center for Computational Science and computer maker Fujitsu. It was ranked no.1 last June on the Top500 listing of the world’s fastest supercomputers turning in a LINPACK benchmark result of 415.5 petaflops, outperforming Summit, the former no. 1 (now no. 2) system housed at the U.S. Dept. of Energy’s Oak Ridge National Lab, by a factor of 2.8x. The system is powered by Fujitsu’s 48-core A64FX SoC and is the first ARM-based system to take the no. 1 ranking. Fugaku, which has 158,976 nodes, blew through the exascale milestone in single-precision calculations often used in machine learning and AI applications.