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The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 51 high-impact computational science projects for 2022 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.

Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.

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The U.S. Department of Energy’s Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program is seeking proposals for high-impact, computationally intensive research campaigns in a broad array of science, engineering and computer science domains. 

Oak Ridge National Laboratory’s Summit supercomputer was named No. 1 on the TOP500 List, a semiannual ranking of the world’s fastest computing systems. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy.

The US Department of Energy’s Oak Ridge National Laboratory is once again officially home to the fastest supercomputer in the world, according to the TOP500 List, a semiannual ranking of the world’s fastest computing systems.

Oak Ridge National Laboratory launches Summit supercomputer.

The U.S. Department of Energy’s Oak Ridge National Laboratory today unveiled Summit as the world’s most powerful and smartest scientific supercomputer.

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.

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