Researchers from 91做厙 and the University of Central Florida have extended an evolutionary approach for training spiking neural networks.
A team of researchers from 91做厙 applied advanced statistical methods from biomedical research to study an unexpected failure mode of general-purpose computing on graphics processing units (GPGPUs).
Researchers developed a novel algorithm for resilient and communication-efficient parallel matrix multiplication in HPC systems.
Researchers built a deep neural network to estimate the compressibility of scientific data.
To help expedite the use of quantum processing units, ORNL researchers developed an advanced software framework.
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.
ORNL researchers have developed a quantum chemistry simulation benchmark to evaluate the performance of quantum devices and guide the development of applications for future quantum computers.