US Federal News Bureau

NOAA Invests $100 mn on New Supercomputer Rhea to boost AI-ML Usage

Rhea is expected to play a significant role in advancing NOAA’s research on weather, climate, ocean, and ecosystem prediction.

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Written by: CDO Magazine Bureau

Updated 6:39 PM UTC, Thu September 5, 2024

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NOAA Rhea

The U.S. Department of Commerce and the National Oceanic and Atmospheric Administration (NOAA) have recently announced their plan to invest $100 million to develop a new high-performance computer (HPC) system.

Called Rhea, it will be installed in a new modular facility as part of the NOAA Environmental Security Computing Center (NESCC) in Fairmont, West Virginia. 

The fund has been allocated to General Dynamics Information Technology. Rhea is expected to play a significant role in advancing NOAA’s research on weather, climate, ocean, and ecosystem prediction. 

“The Rhea high-performance computer system adds needed computing capacity for NOAA to expand critical research that supports the nation’s climate resilience. The new system will strengthen NOAA’s exploration and application of artificial intelligence and machine learning (AI/ML) capabilities, which will ultimately improve weather, ocean, and climate forecasting, ecosystem modeling, and the use of satellite Earth observations to understand climate changes,” Assistant Secretary of Commerce Michael C. Morgan, Ph.D., said.

Once functional, Rhea will be part of NOAA’s Research and Development High-Performance Computing System, which includes four other research and development (R&D) HPC centers located in Boulder, Colorado; Princeton, New Jersey; Oak Ridge, Tennessee; and on the campus of Mississippi State University in Starkville, Mississippi. 

With Rhea, the computing speed and capacity of NOAA’s existing R&D HPC is expected to reach 43 petaflops from 35 petaflops.

According to NOAA, Rhea features graphics processing units that will accelerate its use of AI/ML in a range of areas, including monitoring marine life species, weather forecasting, and modeling of specific environmental phenomena such as atmospheric rivers, fire weather, and hurricane intensification using Earth observations.

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