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Frontier’s exascale power enables the Energy, Exascale and Earth System Model-Multiscale Modeling Framework — or E3SM-MMF — project to run years’ worth of climate simulations at unprecedented speed and scale. Credit: Mark Taylor/Sandia National Laboratories, U.S. Dept. of Energy

The world’s first exascale supercomputer will help scientists peer into the future of global climate change and open a window into weather patterns that could affect the world a generation from now.

The ORNL DAAC gathers, processes, archives and distributes information on key land processes, including the shifting ecological and geomorphological features of the U.S. Atchafalaya and Terrebonne basins gathered by the NASA Delta-X mission shown here. Credit: NASA Delta-X

In 1993 as data managers at ORNL began compiling observations from field experiments for the National Aeronautics and Space Administration, the information fit on compact discs and was mailed to users along with printed manuals.

 A group of ORNL staff standing in a long corridor with flags hanging from the ceiling

For 25 years, scientists at Oak Ridge National Laboratory have used their broad expertise in human health risk assessment, ecology, radiation protection, toxicology and information management to develop widely used tools and data for the U.S. Environmental Protection Agency as part of the agency’s Superfund program.

Members of the Analytics and AI Methods at Scale group in the National Center for Computational Sciences at ORNL developed the mixed-precision performance benchmarking tool OpenMxP. From left are group leader Feiyi Wang, technical lead Mike Matheson and research scientist Hao Lu. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

As Frontier, the world’s first exascale supercomputer, was being assembled at the Oak Ridge Leadership Computing Facility in 2021, understanding its performance on mixed-precision calculations remained a difficult prospect.

Chathuddasie Amarasinghe explains her research poster, “Using Microfluidic Mother Machine Devices to Study the Correlated Dynamics of Ribosomes and Chromosomes in Escherichia Coli.” Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Speakers, scientific workshops, speed networking, a student poster showcase and more energized the Annual User Meeting of the Department of Energy’s Center for Nanophase Materials Sciences, or CNMS, Aug. 7-10, near Market Square in downtown Knoxville, Tennessee.

Oak Ridge National Laboratory entrance sign

The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.

A rendering of the CFM RISE program’s open fan architecture. (bottom) A GE visualization of turbulent flow in the tip region of an open fan blade using the Frontier supercomputer at ORNL. Credit: CFM, GE Research (CFM is a 50­–50 joint company between GE and Safran Aircraft Engines)

Outside the high-performance computing, or HPC, community, exascale may seem more like fodder for science fiction than a powerful tool for scientific research. Yet, when seen through the lens of real-world applications, exascale computing goes from ethereal concept to tangible reality with exceptional benefits.

Madhavi Martin portrait image

Madhavi Martin brings a physicist’s tools and perspective to biological and environmental research at the Department of Energy’s Oak Ridge National Laboratory, supporting advances in bioenergy, soil carbon storage and environmental monitoring, and even helping solve a murder mystery.

The OpeN-AM experimental platform, installed at the VULCAN instrument, features a robotic arm that prints layers of molten metal to create complex shapes. Credit: Jill Hemman/ORNL, U.S Dept. of Energy

Technologies developed by researchers at ORNL have received six 2023 R&D 100 Awards.  

Diagram of faults affecting a conventional power system.

Researchers at the Department of Energy’s Oak Ridge National Laboratory are leading the way in understanding the effects of electrical faults in the modern U.S. power grid.