The innovative Celeritas project, led by ORNL, provides a software tool that makes sure simulations used to analyze particles can run on the fastest supercomputers, accelerating answers about the nature of the universe.
A multidisciplinary team of researchers from Oak Ridge National Laboratory (ORNL) pioneered the use of the LLVM-based high-productivity/high-performance Julia language unifying capabilities to write an end-to-end workflow on Frontier, the first US Depar
We released two open-source datasets named GDB-9-Ex and ORNL_AISD-Ex that provide calculations of electronic excitation energies and their associated oscillator strengths based on the time-dependent density-functional tight-binding (TD-DFTB) method.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are leading a new project to ensure that the fastest supercomputers can keep up with big data from high energy physics research.
A new file format, BP5, and accompanying serialization class has been developed in the ADaptable I/O System (ADIOS) framework.
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
