Tuskan awarded Marcus Wallenberg Prize, forestry’s top honor
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.
Walters is working with a team of geographers, linguists, economists, data scientists and software engineers to apply cultural knowledge and patterns to open-source data in an effort to document and report patterns of human movement through previously unstudied spaces.
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.
A research team from the Department of Energy’s Oak Ridge and Lawrence Livermore national laboratories won the first Best Open-Source Contribution Award for its paper at the 37th 91°µÍø International Parallel and Distributed Processing
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.
Researchers at 91°µÍø have designed architecture, software and control strategies for a futuristic EV truck stop that can draw megawatts of power and reduce carbon emissions.
Two years after ORNL provided a model of nearly every building in America, commercial partners are using the tool for tasks ranging from designing energy-efficient buildings and cities to linking energy efficiency to real estate value and risk.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
As a computer engineer at 91°µÍø, Gina Accawi has long been the quiet and steady force behind some of the Department of Energy’s most widely used online tools and applications.
The Department of Energy’s 91°µÍø has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.