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EJ committed Dec 5, 2023
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Expand Up @@ -60,6 +60,7 @@ Particularly important papers are highlighted.
- Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training (You et al. 2023) [[Paper]](https://www.usenix.org/conference/nsdi23/presentation/you)
- Chasing Low-Carbon Electricity for Practical and Sustainable DNN Training (Yang et al. 2023) [[Paper]](https://www.climatechange.ai/papers/iclr2023/29)
- LLMCarbon: Modeling the End-To-End Carbon Footprint of Large Language Models (Faiz et al. 2023) [[Paper]](https://arxiv.org/pdf/2309.14393.pdf)
- Power Hungry Processing: Watts Driving the Cost of AI Deployment? (Luccioni et al. 2023) [[Paper]](https://arxiv.org/pdf/2311.16863.pdf)

<!-- - How to shrink AI's ballooning carbon footprint (Gibney et al. 2022) [[Paper]]() -->

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