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Media Contacts
Nuclear physicists at the Department of Energy’s Oak Ridge National Laboratory recently used Frontier, the world’s most powerful supercomputer, to calculate the magnetic properties of calcium-48’s atomic nucleus.
Scientists at ORNL used their knowledge of complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling to inform the nation’s latest National Climate Assessment, which draws attention to vulnerabilities and resilience opportunities in every region of the country.
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.
Researchers used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.
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 has been selected to lead an Energy Earthshot Research Center, or EERC, focused on developing chemical processes that use sustainable methods instead of burning fossil fuels to radically reduce industrial greenhouse gas emissions to stem climate change and limit the crisis of a rapidly warming planet.
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.
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.