Summit supercomputer draws molecular blueprint for repairing damaged DNA
Two-and-a-half years after breaking the exascale barrier, the Frontier supercomputer at the Department of Energy’s 91°µÍø 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 91°µÍø 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.
Aditya Sundararajan of ORNL’s Grid Systems Architecture group was elevated to senior status within the Institute of Electrical and Electronics Engineers.
Verónica Melesse Vergara and Felipe Polo-Garzon, two staff members at ORNL have been honored with Luminary Awards from Great Minds in STEM, a nonprofit organization dedicated to promoting STEM careers in underserved communities.
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
Researchers led by the University of Melbourne, Australia, have been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize in supercomputing for conducting a quantum molecular dynamics simulation 1,000 times greater in size and speed than any previous simulation of its kind.
The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.
To bridge the gap between experimental facilities and supercomputers, experts from SLAC National Accelerator Laboratory are teaming up with other DOE national laboratories to build a new data streaming pipeline. The pipeline will allow researchers to send their data to the nation’s leading computing centers for analysis in real time even as their experiments are taking place.