Hewlett Packard Enterprises has announced an AI Ops R&D collaboration with the US Department of Energy’s National Renewable Energy Laboratory (NREL) to develop artificial intelligence (AI) and machine learning (ML) technologies to automate and improve operational efficiency, including resiliency and energy usage, in data centers for the exascale era. The effort is part of NREL’s ongoing mission as a world leader in advancing energy efficiency and renewable energy technologies to create and implement new approaches that reduce energy consumption and lower operating costs.

The project is part of a 3-year collaboration

That introduces monitoring and predictive analytics to power and cooling systems in NREL’s Energy Systems Integration Facility (ESIF) HPC Data Center. HPE and NREL are using more than five years’ worth of historical data, which total more Iraq Phone Number Data than 16 terabytes of data, collected from sensors in NREL’s supercomputers, Peregrine and Eagle, and its facility, to train models for anomaly detection to predict and prevent issues before they occur. The collaboration will also address future water and energy consumption in data centers, that in the US alone will reach approximately 73 billion kWh and 174 billion gallons of water by 2020.

HPE and NREL will focus on monitoring

Energy usage to optimize energy efficiency and sustainability as measured by key metrics such as Power Usage Effectiveness (PUE), Water India WhatsApp Number List Effectiveness (WUE), and Carbon Usage Effectiveness (CUE). Early results based on models trained with historical data have successfully predicted or identified events that previously occurred in NREL’s data center, demonstrating the promise of using predictive analytics in future data centers. The AI Ops project sprung from HPE’s R&D efforts involved with PathForward, a program backed by the US Department of Energy to accelerate the nation’s technology roadmap for exascale computing, which represents the next step in supercomputing.

DOE Turns to Artificial Intelligence to Improve Data Center Efficiency

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