Robert Hettich: Decoding biological complexity with next-gen mass spectrometry
The Department of Energy’s Quantum Computing User Program, or QCUP, is releasing a Request for Information to gather input from all relevant parties on the current and upcoming availability of quantum computing resources, conventions for measuring, tracking, and forecasting quantum computing performance, and methods for engaging with the diversity of stakeholders in the quantum computing community. Responses received to the RFI will inform QCUP on both immediate and near-term availability of hardware, software tools and user engagement opportunities in the field of quantum computing.
The Quantum Computing User Forum welcomed attendees for a dynamic event at ORNL. The annual user meeting brought the cohort together to highlight results and discuss common practices in the development of applications and software for quantum computing systems.
Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid.
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%.
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 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 Oak Ridge National Laboratory, 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 Oak Ridge National Laboratory 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.