Quantum precision reached in modeling molten salt behavior
Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.
Researchers from ORNL have developed a new application to increase efficiency in memory systems for high performance computing. Rather than allow data to bog down traditional memory systems in supercomputers and impact performance, the team from ORNL, along with researchers from the University of Tennessee, Knoxville, created a framework to manage data more efficiently with memory systems that employ more complex structures.
To bridge the gap between experimental facilities and supercomputers, experts from SLAC National Accelerator Laboratory are teaming up with other DOE national laboratories to build a new data streaming pipeline. The pipeline will allow researchers to send their data to the nation’s leading computing centers for analysis in real time even as their experiments are taking place.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
Integral to the functionality of ORNL's Frontier supercomputer is its ability to store the vast amounts of data it produces onto its file system, Orion. But even more important to the computational scientists running simulations on Frontier is their capability to quickly write and read to Orion along with effectively analyzing all that data. And that’s where ADIOS comes in.
To support the development of a revolutionary new open fan engine architecture for the future of flight, GE Aerospace has run simulations using the world’s fastest supercomputer capable of crunching data in excess of exascale speed, or more than a quintillion calculations per second.
Climate change often comes down to how it affects water, whether it’s for drinking, electricity generation, or how flooding affects people and infrastructure. To better understand these impacts, ORNL water resources engineer Sudershan Gangrade is integrating knowledge ranging from large-scale climate projections to local meteorology and hydrology and using high-performance computing to create a holistic view of the future.
The Earth System Grid Federation, a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades.
ORNL has provided hydropower operators with new data to better prepare for extreme weather events and shifts in seasonal energy demands caused by climate change.
Researchers across the scientific spectrum crave data, as it is essential to understanding the natural world and, by extension, accelerating scientific progress.