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@ml-energy

ML.ENERGY

ml-energy
Ann Arbor, MI

At The ML.ENERGY Initiative, we are working on building efficient ways of measuring, understanding, optimizing, and exposing the energy consumption of modern Machine Learning applications.

We make serious efforts to make all of our research outcomes to be usable in the real world.

2 sponsors have funded ml-energy’s work.

Private Sponsor
@GitHub-SecureOSS-Fund

Featured work

  1. ml-energy/zeus

    Measure and optimize the energy consumption of your AI applications!

    Python 332
  2. ml-energy/leaderboard-v2

    A canonical source of GenAI energy benchmark and meausrements

    Python 50
  3. ml-energy/lowtime

    A time-cost tradeoff problem solver

    Python 11
  4. ml-energy/amdsmi

    Python bindings for ROCm/AMDSMI

    Python 3

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