Lawrence Livermore National Laboratory’s Lori Diachin will take over as director of the Department of Energy’s Exascale Computing Project on June 1, guiding the successful, multi-institutional high-performance computing effort through its final stages.
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.
As renewable sources of energy such as wind and sun power are being increasingly added to the country’s electrical grid, old-fashioned nuclear energy is also being primed for a resurgence.
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.
ORNL has named Michael Parks director of the Computer Science and Mathematics Division within ORNL’s Computing and Computational Sciences Directorate. His hiring became effective March 13.
Natural gas furnaces not only heat your home, they also produce a lot of pollution. Even modern high-efficiency condensing furnaces produce significant amounts of corrosive acidic condensation and unhealthy levels of nitrogen oxides
Hydrologist Jesús “Chucho” Gomez-Velez is in the right place at the right time with the right tools and colleagues to explain how the smallest processes within river corridors can have a tremendous impact on large-scale ecosystems.
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
The Earth System Grid Federation, a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.