Dataset of the HazardNet: A Thermal Hazard Prediction Framework for Datacenters
Dataset of the HazardNet: A Thermal Hazard Prediction Framework for Datacenters
This dataset entry showcases a comprehensive collection obtained from the Tier-0 supercomputer, Marconi A2, hosted at CINECA (https://www.hpc.cineca.it/). The dataset records inlet and outlet temperatures along with power consumption data from 3312 computing nodes, spanning from January 14, 2019, to December 31, 2019. The data is generated through ExaMon, a sophisticated monitoring datacenter infrastructure. The primary objective of this dataset is to support the research and development of HazardNet, an innovative thermal hazard prediction framework tailored specifically for datacenters. HazardNet integrates a comprehensive pipeline of machine-learning models. Researchers and enthusiasts interested in exploring our work further can find the complete set of codes and machine-learning models at our GitHub repository: https://github.com/MSKazemi/HazardNet
- ETH Zurich Switzerland
- Alma Mater Studiorum University of Bologna Italy
Datacenter Thermal hazard Predictive model Thermal anomaly detection Deep learning Temporal convolutional network
Datacenter Thermal hazard Predictive model Thermal anomaly detection Deep learning Temporal convolutional network
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