Researchers at Oak Ridge National Laboratory used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts.
Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii – and used a machine learning model to predict how extreme weather such as thunderstorms, floods and
The bigger the swirl, the bigger the problem — and the bigger the computing power needed to solve it.
We developed a novel uncertainty-aware framework MatPhase to predict material phases of electrodes from low contrast SEM images.
Researchers at the U.S. Department of Energy’s Oak Ridge National Laboratory are part of a multi-institutional team that will receive nearly $14 million over five years to tackle sparse computational problems in high-performance computing.
Researchers at Oak Ridge National Laboratory developed a new parallel performance portable algorithm for solving the Euclidean minimum spanning tree problem (EMST), capable of processing tens of millions of data points a second.
After nearly seven years of intense development, the URBAN-NET infrastructure quantification tool is being made available to users.
A graph convolutional neural network (GCNN) was trained with millions of molecules to accurately predict molecular photo-optical properties by scaling data loading and training to over 1,500 GPUs on the Summit and Perlmutter supercomputers at the OLCF a
Olivera Kotevska, a research scientist in Oak Ridge National Laboratory’s Computing and Computational Sciences Directorate, has been awarded senior membership by the Institute of Electrical and Electronics Engineers, the world’s largest association for
Piyush Sao, a research scientist in Oak Ridge National Laboratory’s Computing and Computational Sciences Directorate, has received the Best Paper Prize from the Society for Industrial and Applied Mathematics (SIAM) Activity Group on Supercomputing.