哔咔漫画

A team of computational physicists and computer scientists led by researchers from the 哔咔漫画 has reached a new milestone in supercomputing and was selected as a finalist for the field鈥檚 most prestigious award.

The , presented annually by the at the , recognizes outstanding achievement in high-performance computing and is often referred to as the 鈥淣obel Prize of supercomputing.鈥� The purpose of the award is to recognize outstanding achievements in innovative applications of high-performance computing to problems in science, engineering and large-scale data analytics.

The team, led by Ivan Oleynik, , along with Kien Nguyen Cong and Jonathan Willman, both of whom recently completed doctoral degrees at USF, utilized , the fastest supercomputer in the U.S., to explore how carbon atoms behave at extremely high pressures and temperatures.

鈥淭his is one of the most significant fundamental problems that exists in material science today,鈥� Oleynik said. 鈥淔urthering our understanding of carbon behavior inside of or upon enormous compression during inertial confinement fusion implosions is paramount to advancing our knowledge of the structure of exoplanets or unlocking limitless fusion energy sources. Making impact through such grand simulations is something we could have never dreamed of.鈥�

For the first time, researchers were able to conduct cutting-edge molecular dynamics simulations of several billion carbon atoms with extreme quantum accuracy. To accomplish this, USF researchers worked with partners from , the , the and  to develop novel machine learning interatomic potentials describing interactions between carbon atoms with ultimate fidelity as well as to implement them in very efficient GPU-enabled computational algorithms.

By combining this novel methodology with access to , the nation鈥檚 most powerful supercomputer, researchers were able to run a 24-hour simulation that uncovered a long sought-after synthesis of high-pressure post-diamond crystalline phase of carbon under extreme conditions. This transformative discovery was made possible not only through access to Summit, but through the use of the team鈥檚 combined expertise in innovative atomic-scale machine learning simulation methodology and its algorithmic implementation that helped unlock the enormous predictive power of computer simulations on one of the most powerful supercomputers in the world.

鈥淭his was an enormous simulation that has revealed previously unknown behavior of carbon at the atomic scale in billion atom simulations at experimental time and length scales,鈥� Oleynik said. 鈥淣ot only have we made this discovery, but in the process, of quantum accurate molecular dynamics by running our simulation 23 times faster. This is an immense leap forward in computational materials science.鈥�

The team is now working to publish its science findings from this simulation while awaiting the Nov. 18 announcement of the Gordon Bell Prize winner.

To learn more about the team鈥檚 work, read their .