Energy and carbon-aware distributed machine learning tasks scheduling scheme for the multi-renewable energy-based edge-cloud continuum
As an increasing number of Distributed Machine Learning (DML) tasks are hosted on cloud platforms in the edge-cloud continuum, Data Centers (DCs) with massive data and computational requirements have become one of the world’s largest energy consumers, leading to significant carbon emissions. Reducin...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | Science and Technology for Energy Transition |
| Subjects: | |
| Online Access: | https://www.stet-review.org/articles/stet/full_html/2024/01/stet20240197/stet20240197.html |
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