Quantum precision reached in modeling molten salt behavior
Scientists at ORNL have developed a first-ever urban heat wave simulation that takes into account the compounding effects from building infrastructure. The method provides a more accurate picture of the impacts from excessive heat on at-risk
Scientists at the Department of Energy’s Oak Ridge National Laboratory recently demonstrated an autonomous robotic field monitoring, sampling and data-gathering system that could accelerate understanding of interactions among plants, soil and the environment.
ORNL researchers reached a significant milestone by building an entire 6.5-foot turbine blade tip using novel materials. The team then tested it against the forces of simulated lightning in a specialized lab at Mississippi State University, where the blade tip emerged pristine after tests that isolate the effects of high voltage.
In early November, researchers at the Department of Energy’s Argonne National Laboratory used the fastest supercomputer on the planet to run the largest astrophysical simulation of the universe ever conducted. The achievement was made using the Frontier supercomputer at Oak Ridge National Laboratory.
Two-and-a-half years after breaking the exascale barrier, the Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory continues to set new standards for its computing speed and performance.
Researchers used the world’s fastest supercomputer, Frontier, to train an AI model that designs proteins, with applications in fields like vaccines, cancer treatments, and environmental bioremediation. The study earned a finalist nomination for the Gordon Bell Prize, recognizing innovation in high-performance computing for science.
Researchers at Oak Ridge National Laboratory used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts. This achievement earned them a finalist nomination for the prestigious Gordon Bell Prize for Climate Modeling.
A research team led by the University of Maryland has been nominated for the Association for Computing Machinery’s Gordon Bell Prize. The team is being recognized for developing a scalable, distributed training framework called AxoNN, which leverages GPUs to rapidly train large language models.
A team of researchers used the Frontier supercomputer and a new methodology for conducting a genome-wide association study to earn a finalist nomination for the Association for Computing Machinery’s 2024 Gordon Bell Prize for outstanding
A multi-institutional team of researchers led by the King Abdullah University of Science and Technology, or KAUST, Saudi Arabia, has been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize for Climate Modelling.