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Artificial Intelligence for Data Center Operations (AI Ops)

Technical Report ·
DOI:https://doi.org/10.2172/1783088· OSTI ID:1783088
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  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Hewlett-Packard Enterprise, Palo Alto, CA (United States)
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HPC data centers such as the one at NREL's ESIF will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence (AI) and machine learning (ML) approaches provide the means to improve HPC data center efficiency (energy, operational, and managerial efficiency) and resiliency by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. The goal of coupled improvement of data center resiliency and energy efficiency through automated data collection and AI has led to a multi-year, multi-staged collaboration between NREL and Hewlett-Packard Enterprise's Advanced Technology Group, referred to as Artificial Intelligence for Data Center Operations (AIOps). The extended efforts within the AIOps project include a common goal of building capabilities for an advanced smart facility and demonstration of data collection and AI modeling techniques in the ESIF data center.
Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE); Hewlett Packard Enterprise
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1783088
Report Number(s):
NREL/TP-2C00-79712; MainId:36932; UUID:df7cad2a-f24f-4255-b36f-9aef927922aa; MainAdminId:22375
Country of Publication:
United States
Language:
English

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Related Subjects

97 MATHEMATICS AND COMPUTING
AI
data center
energy efficiency
machine learning
operations
supercomputer