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A team led by the Department of Energy’s Oak Ridge National Laboratory has uncovered how certain soil microbes cope in a phosphorus-poor environment to survive in a tropical ecosystem. Their novel approach could be applied in other ecosystems to study various nutrient limitations and inform agriculture and terrestrial biosphere modeling.
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the
![An example of a spiking neural network shows how data can be classified using the neuromorphic device. Credit: Catherine Schuman and Margaret Drouhard/Oak Ridge National Laboratory, U.S. Dept. of Energy An example of a spiking neural network shows how data can be classified using the neuromorphic device. Credit: Catherine Schuman and Margaret Drouhard/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/Spiking_neural_network_ORNL_2.jpg?itok=CN68Ze_4)
For smarter data management and analysis, researchers have developed a low-power neuromorphic device based on spiking neural networks that can quickly and more efficiently analyze and classify data.