With the world’s first exascale supercomputer now fully open for scientific business, researchers can thank the early users who helped get the machine up to speed.
As a result of largescale 3D supernova simulations conducted on the Oak Ridge Leadership Computing Facility’s Summit supercomputer by researchers from the University of Tennessee and Oak Ridge National Laboratory, astrophysicists now have the most complete picture yet of what gravitational waves from exploding stars look like.
To support the development of a revolutionary new open fan engine architecture for the future of flight, GE Aerospace has run simulations using the world’s fastest supercomputer capable of crunching data in excess of exascale speed, or more than a quintillion calculations per second.
Simulations performed on the Summit supercomputer at ORNL revealed new insights into the role of turbulence in mixing fluids and could open new possibilities for projecting climate change and studying fluid dynamics.
At the National Center for Computational Sciences, Ashley Barker enjoys one of the least complicated–sounding job titles at ORNL: section head of operations. But within that seemingly ordinary designation lurks a multitude of demanding roles as she oversees the complete user experience for NCCS computer systems.
A trio of new and improved cosmological simulation codes was unveiled in a series of presentations at the annual April Meeting of the American Physical Society in Minneapolis.
A team of researchers from ORNL was recognized by the National Cancer Institute in March for their unique contributions in the fight against cancer.
A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge National Laboratory.
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.