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Media Contacts
![Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database. Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2018-P00005_r3_0.jpg?itok=FrGhhOuK)
Oak Ridge National Laboratory provided significant contributions and coordination in the development of the Nuclear Energy Agency’s (NEA’s) recently released Spent Fuel Isotopic Composition (SFCOMPO) 2.0—the world’s largest open database for spent
![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