A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.
A team of eight scientists won the Association for Computing Machinery’s 2023 Gordon Bell Prize for their study that used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
Waiting for answers surrounding a healthcare condition can be as stressful as the condition itself. Maria Mahbub, a research collaborator at Oak Ridge National Laboratory, is developing technology that could help providers and patients get answers sooner.
Walters is working with a team of geographers, linguists, economists, data scientists and software engineers to apply cultural knowledge and patterns to open-source data in an effort to document and report patterns of human movement through previously unstudied spaces.
A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions.
The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
The Oak Ridge Leadership Computing Facility, a Department of Energy Office of Science user facility at ORNL, is pleased to announce a new allocation program for computing time on the IBM AC922 Summit supercomputer.
The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.