OPTIMIZING DATA CENTER CONTROLS USING NEURAL NETWORKS

    公开(公告)号:US20180204116A1

    公开(公告)日:2018-07-19

    申请号:US15410547

    申请日:2017-01-19

    Applicant: Google Inc.

    CPC classification number: G06N3/0454

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for improving operational efficiency within a data center by modeling data center performance and predicting power usage efficiency. An example method receives a state input characterizing a current state of a data center. For each data center setting slate, the state input and the data center setting slate are processed through an ensemble of machine learning models. Each machine learning model is configured to receive and process the state input and the data center setting slate to generate an efficiency score that characterizes a predicted resource efficiency of the data center if the data center settings defined by the data center setting slate are adopted t. The method selects, based on the efficiency scores for the data center setting slates, new values for the data center settings.

Patent Agency Ranking