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Media Contacts
Scientists at ORNL have developed 3D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments
How do you get water to float in midair? With a WAND2, of course. But it’s hardly magic. In fact, it’s a scientific device used by scientists to study matter.
The team that built Frontier set out to break the exascale barrier, but the supercomputer’s record-breaking didn’t stop there.
Making room for the world’s first exascale supercomputer took some supersized renovations.
The world’s first exascale supercomputer will help scientists peer into the future of global climate change and open a window into weather patterns that could affect the world a generation from now.
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
As Frontier, the world’s first exascale supercomputer, was being assembled at the Oak Ridge Leadership Computing Facility in 2021, understanding its performance on mixed-precision calculations remained a difficult prospect.
The Department of Energy’s Oak Ridge National Laboratory hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.
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.
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.