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A team led by Oak Ridge National Laboratory researchers used Frontier to explore training strategies for one of the largest artificial intelligence models to date. Credit: Getty Images

A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.
 

Frontier supercomputer sets new standard in molecular simulation

When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.

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.

New research predicts peak groundwater extraction for key basins around the globe by the year 2050. The map indicates groundwater storage trends for Earth’s 37 largest aquifers using data from the NASA Jet Propulsion Laboratory GRACE satellite. Credit: NASA.

Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds. 

: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey

ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.

Prasanna Balaprakash, who leads ORNL’s AI Initiative, participated in events hosted by the White House Office of Science and Technology Policy and the Task Force on American Innovation to discuss the challenges and opportunities posed by AI. Credit: Brian Mosley/Computing Research Association

In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.

The AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE

A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules. 

Frontier’s exascale power enables the Simple Cloud-Resolving E3SM Atmosphere Model to run years’ worth of climate simulations at unprecedented speed and scale. Credit: Ben Hillman/Sandia National Laboratories, U.S. Dept. of Energy

A 19-member team of scientists from across the national laboratory complex won the Association for Computing Machinery’s 2023 Gordon Bell Special Prize for Climate Modeling for developing a model that uses the world’s first exascale supercomputer to simulate decades’ worth of cloud formations.

A Univ. of Michigan-led team used Frontier, the world’s first exascale supercomputer, to simulate a system of nearly 75,000 magnesium atoms at near-quantum accuracy. Credit: SC23

 

A team of eight scientists won the Association for Computing Machinery’s 2023 Gordon Bell Prize for their study that used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.

ORNL researchers are establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.

Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.