Digital Twins for Data Centers

Journal Article · 23 September 2024 · Computer

DOI: https://doi.org/10.1109/mc.2024.3436945 · OSTI ID:2479039

Athavale, Jyotika  ^[1]; Bash, Cullen  ^[2]; Brewer, Wesley  ^[3]; Maiterth, Matthias  ^[3]; Milojicic, Dejan  ^[2]; Petty, Harry  ^[4]; Sarkar, Soumyendu  ^[2]

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1. Synopsys, Inc., Sunnyvale, CA (United States)
2. Hewlett Packard Labs, Milpitas, CA (United States)
3. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
4. NVIDIA, Santa Clara, CA (United States)

Fueled by an unprecedented adoption of AI (Artificial Intelligence), data centers are becoming the largest growing consumers of energy. Digital Twins provide living digital models of physical systems that enable data-driven analysis and application of AI to better manage selective aspects of the data center and drive efficiency for sustainability. Digital twins have emerged as a way to create virtual prototypes of physical artifacts, which may be used in a variety of contexts. Physical artifacts include airplanes, factories, or even static objects, such as bridges or dams. Digital twin helps monitor changes and assist in predicting planned or unplanned behaviors of physical objects. In this paper, we discuss digital twins for data centers.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 2479039
• Journal Information: Computer, Journal Name: Computer Journal Issue: 10 Vol. 57; ISSN 0018-9162
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English