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This ‘brain-inspired’ supercomputer will explore deep learning for the U.S. nuclear program

A new low-power, “brain-inspired” supercomputing platform based on IBM chip technology will soon start exploring deep learning for the U.S. nuclear program.

Lawrence Livermore National Laboratory announced on Tuesday that it has purchased the platform, based on the TrueNorth neurosynaptic chip IBM introduced in 2014. It will use the technology to evaluate machine-learning and deep-learning applications for the National Nuclear Security Administration.

The computer will process data with the equivalent of 16 million neurons and 4 billion synapses and consume roughly as much energy as a tablet PC. Also included will be an accompanying ecosystem consisting of a simulator; a programming language; an integrated programming environment; a library of algorithms and applications; firmware; tools for composing neural networks for deep learning; a teaching curriculum; and cloud enablement.

A single TrueNorth processor consists of 5.4 billion transistors wired together to create an array of 1 million digital neurons that communicate with one another via 256 million electrical synapses.

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