Data Center Facility Monitoring with Physics Aware Approach

Research output: Contribution to conferencePaperpeer-review


U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) hosts one of the world’s most energy-efficient HPC data centers; this system uses component-level warm-water liquid cooling to efficiently remove heat from the data center and capture it for reuse in the building or rejection to the atmosphere. Given the complexity of this system, building data-driven tools for holistically monitoring and operating the entire data center is a priority for ensuring maximal efficiency and resiliency. In this advanced smart facility, over one million metrics are recorded per minute using state-of-the-art streaming data architecture and software to capture and process the state of the system in real time. Here we detail two efforts to effectively analyze, visualize, and interpret this large volume streaming data. We have developed a novel, flexible system for identifying and visualizing individual metric anomalies and component performance across the data center through automatic metadata extraction and physically-motivated visualization for quick interpretation. Additionally, to directly connect system maintenance to data stream processing we explore a physics informed multi-metric drift and anomaly detection application to detect scale-build up in heat exchangers.

Original languageAmerican English
Number of pages11
StatePublished - 2022
Event37th International Conference on High Performance Computing , ISC High Performance 2022 - Hamburg, Germany
Duration: 29 May 20222 Jun 2022


Conference37th International Conference on High Performance Computing , ISC High Performance 2022

Bibliographical note

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

NREL Publication Number

  • NREL/CP-2C00-84123


  • Anomaly detection
  • Data center monitoring
  • Visualization


Dive into the research topics of 'Data Center Facility Monitoring with Physics Aware Approach'. Together they form a unique fingerprint.

Cite this