computing

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With expertise in high-energy physics, advanced computing, accelerator and quantum technologies, and microelectronics design, Fermilab is well-equipped to be a central contributor to the Genesis Mission’s goals. Credit: Ryan Postel/JJ Starr, Fermilab

Fermilab drives progress for national AI Genesis Mission

The Genesis Mission is leveraging the strength of the U.S. Department of Energy’s 17 national laboratories, including Fermilab, alongside American research universities and industry partners. The collaborative effort aims to supercharge innovation by integrating the transformative power of artificial intelligence across the national research landscape.

U.S. Department of Energy announces $54 million to increase energy efficiency in microelectronics technology

    From the DOE Office of Science, Aug. 25: The DOE Office of Science announced 10 DOE national laboratory projects, including one led by Fermilab, have been selected to receive funding as part of research related to microelectronics co-design. Senior engineer Davide Braga’s work on hybrid cryogenic detector architectures for sensing and edge computing enabled by new fabrication processes was chosen as one of the 10 awards.

    Tackling big data challenges for next-generation experiments

      From UKRI, Feb. 22, 2021: UKRI scientists are developing vital software to exploit the large data sets collected by the next-generation experiments in high-energy physics. The new software will have the capability to crunch the masses of data that the LHC at CERN and next-generation neutrino experiments, such as the Fermilab-hosted Deep Underground Neutrino Experiment, will produce this decade.

      Coffea speeds up particle physics data analysis

      The prodigious amount of data produced at the Large Hadron Collider presents a major challenge for data analysis. Coffea, a Python package developed by Fermilab researchers, speeds up computation and helps scientists work more efficiently. Around a dozen international LHC research groups now use Coffea, which draws on big data techniques used outside physics.