Source · Tier A · Peer-reviewed
Single-Node Power Demand During AI Training: Measurements on an 8-GPU NVIDIA H100 System
I. Latif, A. C. Newkirk, M. R. Carbone, A. Munir, Y. Lin, J. Koomey, X. Yu, Z. Dong. 2025. IEEE Access, vol. 13, pp. 61740–61747.
| Link | https://doi.org/10.1109/ACCESS.2025.3554728 |
|---|---|
| DOI | 10.1109/ACCESS.2025.3554728 |
| arXiv | 2412.08602 |
| Version | Published in IEEE Access under a new title. The arXiv preprint (v1 11 December 2024, v2 20 December 2024) is titled "Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node". The published abstract, checked 2026-09-24, states the 8.4 kW peak and the 18% gap to the rated 10.2 kW that citing records use. |
| Accessed | 2026-09-23 |
| Imported from | hodgkins-ai-verification-papers@c71e59ff0e8e |
| Note | Listed under "Power telemetry and side-channel attacks" in the Hodgkins bibliography (CC BY 4.0). |