The researchers from ORNL have developed a new and faster algorithm for the graph all-pair shortest-path (APSP) problem.
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Researchers built a deep neural network to estimate the compressibility of scientific data.
A team of ORNL researchers has used the DCA++ application, a popular code for predicting the performance of quantum materials, to verify two performance-enhancing strategies.
Kokkos is a programming model and library for writing performance-portable code in C++.
Researchers at ORNL have developed new solvers for implicit time discretization of a simplified Boltzmann-Poisson system.
The upcoming Square Kilometre Array (SKA) will be the largest radio telescope in the world. An international team recently used Summit, the world’s most powerful supercomputer, to simulate the massive amounts of data the SKA will produce.
A learning-based approximation strategy has been developed to accelerate parameter studies for non-classical models of diffusion.