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The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
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.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
Scientists’ increasing mastery of quantum mechanics is heralding a new age of innovation. Technologies that harness the power of nature’s most minute scale show enormous potential across the scientific spectrum
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.