Quantum precision reached in modeling molten salt behavior
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 IEEE 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.
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.