Deep Learning Energy Measurement and Optimization

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Project News ⚡

• [2024/08] Perseus, our optimizer for large model training, was accepted to SOSP'24! Preprint | Blog | Optimizer
• [2024/07] Added AMD GPU, CPU, and DRAM energy measurement support, and preliminary JAX support!
• [2024/05] Zeus is now a PyTorch ecosystem project. Read the PyTorch blog post here!
• [2024/02] Zeus was selected as a 2024 Mozilla Technology Fund awardee!
• [2023/07] We used the ZeusMonitor to profile GPU time and energy consumption for the ML.ENERGY leaderboard & Colosseum.

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Zeus is a library for (1) measuring the energy consumption of Deep Learning workloads and (2) optimizing their energy consumption.

Zeus is part of The ML.ENERGY Initiative.

Documentation Organization

• Getting Started: Instructions on installation and setup.
• Measuring Energy: How to measure time and energy programmatically and on the command line.
• Optimizing Energy: How to optimize energy.
• Research Overview: Overview of the research papers Zeus is rooted on.
• Source Code Reference: Auto-generated source code reference for the entire codebase.

We also provide usage examples in our GitHub repository.

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If you find Zeus relevant to your research, please consider citing:

@inproceedings{zeus-nsdi23,
    title     = {Zeus: Understanding and Optimizing {GPU} Energy Consumption of {DNN} Training},
    author    = {Jie You and Jae-Won Chung and Mosharaf Chowdhury},
    booktitle = {USENIX NSDI},
    year      = {2023}
}

Contact

Jae-Won Chung (jwnchung@umich.edu)