Abstract: A method for automated switching of workloads on computing devices to increase returns such as rewards or transaction fees in a cryptocurrency blockchain network is disclosed. A plurality of signals impacting the profitability of mining for a plurality of different cryptocurrencies and plurality of different mining pools are monitored. In response to the plurality of signals indicating a different cryptocurrency and mining pool combination is more profitable, the computing device workload is automatically switched. Switching cost may be calculated and used to prevent unprofitable switches. The signals may be used to train a machine learning model that may be used to predict future profitability for automatic switching.

Abstract: A method for managing a plurality of computing devices comprises: periodically collecting status information from the plurality of computing devices; providing a user interface including: a first control to select one or more of the plurality of computing devices; and a second control to select one of a plurality of operating modes, the plurality of operating modes including: a manual mode in which the one or more selected computing devices are operated according to user selected settings; and an intelligent mode in which the one or more selected computing devices are operated according to dynamic settings; and in response to one or more of the plurality of computing devices being selected with the first control and one of the plurality of operating modes being selected with the second control, applying the selected operating mode to the one or more selected computing devices.

Abstract: A system and method for easily managing a data center with multiple computing devices such as cryptocurrency miners from different manufactures is disclosed. A first computer includes a management application to manage the selected computing devices and periodically read and store status information from them into a database. Controls are presented to enable selection of one or more of the devices and to apply an operating mode, including manual, semi-automatic, automatic, and intelligent modes. Machine learning may be used to determine recommended settings for the selected set of computing devices.

Abstract: A system and method for managing large numbers of computing devices such as cryptocurrency miners in a data center are disclosed. A three-dimensional (3D) model of the data center is created using machine-readable codes. The 3D model includes device and bin location information. Status data is captured from the computing devices, associated with location, stored in a database, and used to populate the 3D model, which is rendered in various two-dimensional and 3D views to provide the user with information helpful in managing the data center.