Quantum precision reached in modeling molten salt behavior
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.
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 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.
Huan Zhao, a Eugene P. Wiger Fellow at ORNL, focuses on advancing quantum materials and information technologies, inspired by his grandfather's passion for education. His research in energy-efficient memory devices and sensitive quantum light sources reflects his commitment to scientific progress and education equity.
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.
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.
ORNL and NASA co-hosted the fourth iteration of this invitation-only event, which brings together geospatial, computational, data and engineering experts around a theme. This year’s gathering focused on how artificial intelligence foundation models can enable geospatial digital twins.
Researchers from ORNL have taken a major step forward in using quantum mechanics to enhance sensing devices, a new advancement that could be used in a wide range of areas, including materials characterization, improved imaging and biological and medical applications.
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.