JLab adapts internet TV approach to filter, calibrate and analyze accelerator data in real time.
An Oak Ridge-led group combines algorithms and supercomputers to reveal information that scientists missed.
An Early Career awardee wants to automate the most vexing aspects of traditional scientific software development for supercomputers.
Argonne computer scientist works on power and processor efficiency while diversifying the workforce.
At Los Alamos, novel container software is accelerating innovative science while ensuring supercomputer reliability and uptime.
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.