A Harvard DOE early-career awardee says scientific big-data management needs a major structural reorganization.
An Argonne researcher upgrades supercomputer optimization algorithms to boost reliability and resilience in U.S. power systems.
An Argonne National Laboratory computer scientist finds efficiencies for extracting knowledge from a data explosion.
Los Alamos researchers develop code to distribute computation more efficiently and across increasing numbers of supercomputer processors.
A Sandia researcher applies his DOE early-career award to improving predictive reliability in high-performance computing.
A Purdue University professor is using a DOE early-career award to bridge gaps in high-performance computing languages.
The cosmological search in the dark is no walk in the park. With help from Berkeley Lab’s NERSC, Fermilab aims open-source software at data from high-energy physics.
Los Alamos experiments with a quantum-physics device that could boost computation to the next level.
Oak Ridge National Laboratory is testing a ‘deep-learning supercomputer in a box’ as it looks ahead to machines that automatically find insights in data.
Biologically inspired architectures create opportunities and obstacles.