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7 people from ORBIT research team accept their award from Tom Tabor (middle)

ORNL has been recognized in the 21st edition of the HPCwire Readers’ and Editors’ Choice Awards, presented at the 2024 International Conference for High Performance Computing, Networking, Storage and Analysis in Atlanta, Georgia.

Black computing cabinets in a row on a white floor in the data center that houses the Frontier supercomputer at Oak Ridge National Laboratory

Two-and-a-half years after breaking the exascale barrier, the Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory continues to set new standards for its computing speed and performance.

Graphic representation of ai model that identifies proteins

Researchers used the world’s fastest supercomputer, Frontier, to train an AI model that designs proteins, with applications in fields like vaccines, cancer treatments, and environmental bioremediation. The study earned a finalist nomination for the Gordon Bell Prize, recognizing innovation in high-performance computing for science.

Pictured here are 9 scientists standing in a line in front of the frontier supercomputer logo/computer

Researchers at Oak Ridge National Laboratory used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts. This achievement earned them a finalist nomination for the prestigious Gordon Bell Prize for Climate Modeling.

Larry Seiber poses for a photo with a black background

Larry Seiber, an R&D staff member in the Vehicle Power Electronics group at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to senior member of the Institute of Electrical and Electronics Engineers. 

A graphic representation of AI

The Department of Energy announced a $67 million investment in several AI projects from institutions in both government and academia as part of its AI for Science initiative. Six ORNL-led (or co-led) projects received funding.

Larry York is sitting in front of a computer screen showing an image of plant phenotyping

The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.

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. 

ORNL’s Prasanna Balaprakash joined leading computing experts to provide insight into how supercomputing, AI and meteorology can work together to advance weather and climate research as part of a panel for the United States Senate.

Prasanna Balprakash, director of AI programs for ORNL, discussed advancing climate and weather research through high performance computing and artificial intelligence as part of a September 18 panel for the United States Senate. 

155 attendees from all over the world gathered for SMC24 for a wide range of presentations from industry leading experts.

The Smoky Mountain Computational Sciences and Engineering Conference, or SMC24, entered its third decade with the 21st annual gathering in East Tennessee.