This is an archive article published on June 2, 2025
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US Energy Department unveils supercomputer that merges with AI

Lawrence Berkeley National Laboratory expects the new machine — to be named for Jennifer Doudna, a Berkeley biochemist.

The Perlmutter supercomputer at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory in Berkeley, Calif., in 2022, in a photo provided by Lawrence Berkeley National Laboratory. The new supercomputer from a Department of Energy lab shows the increasing desire of government labs to adopt more technologies from commercial artificial intelligence systems.The Perlmutter supercomputer at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory in Berkeley, Calif., in 2022, in a photo provided by Lawrence Berkeley National Laboratory. The new supercomputer from a Department of Energy lab shows the increasing desire of government labs to adopt more technologies from commercial artificial intelligence systems. (Lawrence Berkeley National Laboratory via The New York Times)
2 min readNew DelhiJun 2, 2025 09:22 AM IST First published on: Jun 2, 2025 at 09:22 AM IST

Scientific computing and artificial intelligence were once separate worlds, using different kinds of calculations on distinctly different hardware. But the two fields are steadily merging, as shown by a massive new machine coming to Berkeley, California.

On Thursday, the Department of Energy’s laboratory near the University of California, Berkeley, said it had selected Dell Technologies to deliver its next flagship supercomputer in 2026. The system will use Nvidia chips tailored for AI calculations and the simulations common to energy research and other scientific fields.

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Lawrence Berkeley National Laboratory expects the new machine — to be named for Jennifer Doudna, a Berkeley biochemist who shared the 2020 Nobel Prize for chemistry — to offer more than a tenfold speed boost over the lab’s most powerful current system. If fully outfitted, the machine could be the Energy Department’s biggest resource for tasks like training AI models, said Jonathan Carter, associate laboratory director for computing sciences at the Berkeley center.

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