Coca4ai: checking energy behaviors on AI data centers
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916331876515840 |
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| author | Gay, Paul Bilinski, Éric Ligozat, Anne-Laure |
| author_facet | Gay, Paul Bilinski, Éric Ligozat, Anne-Laure |
| contents | Monitoring energy behaviors in AI data centers is crucial, both to reduce their energy consumption and to raise awareness among their users which are key actors in the AI field. This paper shows a proof of concept of easy and lightweight monitoring of energy behaviors at the scale of a whole data center, a user or a job submission. Our system uses software wattmeters and we validate our setup with per node accurate external wattmeters. Results show that there is an interesting potential from the efficiency point of view, providing arguments to create user engagement thanks to energy monitoring. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_15670 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Coca4ai: checking energy behaviors on AI data centers Gay, Paul Bilinski, Éric Ligozat, Anne-Laure Computers and Society Monitoring energy behaviors in AI data centers is crucial, both to reduce their energy consumption and to raise awareness among their users which are key actors in the AI field. This paper shows a proof of concept of easy and lightweight monitoring of energy behaviors at the scale of a whole data center, a user or a job submission. Our system uses software wattmeters and we validate our setup with per node accurate external wattmeters. Results show that there is an interesting potential from the efficiency point of view, providing arguments to create user engagement thanks to energy monitoring. |
| title | Coca4ai: checking energy behaviors on AI data centers |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2407.15670 |