Jacobson elected Fellow of the American Institute for Medical and Biological Engineering
Scientists at the Department of Energy’s 91°µÍø recently demonstrated an autonomous robotic field monitoring, sampling and data-gathering system that could accelerate understanding of interactions among plants, soil and the environment.
This year’s Association for Computing Machinery’s Gordon Bell Prize in supercomputing goes to researchers led by the University of Melbourne who used the Frontier supercomputer to conduct a quantum molecular dynamics simulation 1,000 times greater in size and speed than any previous simulation of its kind.
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 91°µÍø.
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.
The Department of Energy’s Quantum Computing User Program, or QCUP, is releasing a Request for Information to gather input from all relevant parties on the current and upcoming availability of quantum computing resources, conventions for measuring, tracking, and forecasting quantum computing performance, and methods for engaging with the diversity of stakeholders in the quantum computing community. Responses received to the RFI will inform QCUP on both immediate and near-term availability of hardware, software tools and user engagement opportunities in the field of quantum computing.
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.
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 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.