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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. 

This is a simulated image of the project to build a new network that artificial intelligence and machine learning to steer experiments and analyze data faster and more accurately. will enable

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. 

Man in blue shirt and grey pants holds laptop and poses next to a green plant in a lab.

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.

Architects of the Adaptable IO System, seen here with Frontier's Orion file system: Scott Klasky, left, heads the ADIOS project and leads ORNL's Workflow Systems group, and Norbert Podhorszki, an ORNL computer scientist, oversees ADIOS's continuing development. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

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.

CFM’s RISE open fan engine architecture. Image: GE Aerospace

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.

A simulation of the planet from the DOE Energy Exascale Earth System Model, one of the large-scale models incorporated in the Earth System Grid Federation led by DOE’s Oak Ridge, Argonne and Lawrence Livermore national laboratories. Credit: LLNL, U.S. Dept. of Energy

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.

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Researchers across the scientific spectrum crave data, as it is essential to understanding the natural world and, by extension, accelerating scientific progress.

An artist rendering of the SKA’s low-frequency, cone-shaped antennas in Western Australia. Credit: SKA Project Office.

For nearly three decades, scientists and engineers across the globe have worked on the Square Kilometre Array (SKA), a project focused on designing and building the world’s largest radio telescope. Although the SKA will collect enormous amounts of precise astronomical data in record time, scientific breakthroughs will only be possible with systems able to efficiently process that data.

At the salt–metal interface, thermodynamic forces drive chromium from the bulk of a nickel alloy, leaving a porous, weakened layer. Impurities in the salt drive further corrosion of the structural material. Credit: Stephen Raiman/Oak Ridge National Labora

Oak Ridge National Laboratory scientists analyzed more than 50 years of data showing puzzlingly inconsistent trends about corrosion of structural alloys in molten salts and found one factor mattered most—salt purity.