Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI

Author:

Yarally Tim1,Cruz Luıs1,Feitosa Daniel2,Sallou June1,van Deursen Arie1

Affiliation:

1. Delft University of Technology,The Netherlands

2. University of Groningen,The Netherlands

Publisher

IEEE

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Green artificial intelligence initiatives: Potentials and challenges;Journal of Cleaner Production;2024-08

2. O Paradoxo da IA para Sustentabilidade e a Sustentabilidade da IA;Anais do V Workshop sobre as Implicações da Computação na Sociedade (WICS 2024);2024-07-21

3. Strategies of Automated Machine Learning for Energy Sustainability in Green Artificial Intelligence;Applied Sciences;2024-07-16

4. Focus on Carbon Dioxide Footprint of AI/ML Model Training;2024 Intelligent Methods, Systems, and Applications (IMSA);2024-07-13

5. Benchmarking Emerging Deep Learning Quantization Methods for Energy Efficiency;2024 IEEE 21st International Conference on Software Architecture Companion (ICSA-C);2024-06-04

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