System and method for managing computing devices
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.
1 . A method for managing a plurality of computing devices, the method comprising:
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 a requested change, the requested change including a selection of one of the plurality of operating modes with the second control for one or more computing devices selected with the first control, simulating the effects of the requested change, and based on the results of the simulation, applying the selected settings to the one or more selected computing devices;
wherein interdependent settings are automatically enforced in the intelligent mode;
wherein, in response to detecting that one or more user selected settings exceed a predetermined safe range, generating a warning in the manual mode;
wherein the simulating includes modeling the requested change for the selected one or more computing devices and providing simulated results that indicate at least one of expected device damage or estimated reduction in remaining device lifespan.
2 . The method of claim 1 , wherein the plurality of operating modes further includes a semi-automated mode in which the one or more selective computing devices are operated according to recommended settings.
3 . The method of claim 2 , further comprising:
obtaining performance data for the one or more selected computing devices; and
in response to selection of the semi-automated mode, determining the recommended settings according to the performance data.
4 . The method of claim 2 , further comprising, in response to selection of the semi-automated mode:
allowing manual adjustment of at least a first parameter of the one or more selected computing devices; and
restricting adjustment of at least a second parameter of the one or more selected computing devices.
5 . The method of claim 1 , wherein the plurality of operating modes further includes a semi-automated mode; and
the method further comprises:
in response to selection of the semi-automated mode, displaying recommended settings and an additional control to apply the recommended settings to the one or more selected computing devices;
operating the one or more selected computing devices according to the recommended settings when a user selects the semi-automated mode via the second control and applies the recommended settings via the additional control; and
operating one or more selected computing devices according to existing settings when said user selects the semi-automated mode via the second control and does not apply the recommended settings via the additional control.
6 . The method of claim 1 , wherein the plurality of operating modes further includes an automated mode in which the one or more selected computing devices are operated via automatically applying recommended settings.
7 . The method of claim 6 , further comprising:
obtaining performance data for the one or more selected computing devices; and
in response to selection of the automated mode, determining the recommended settings according to the performance data.
8 . The method of claim 7 , further comprising, in response to selection of the automated mode:
monitoring performance of the one or more selected computing devices to obtain additional performance data;
determining new recommended settings according to the additional performance data; and
automatically applying the new recommended settings to the one or more selected computing devices.
9 . The method of claim 8 , wherein:
monitoring performance of the one or more selected computing devices includes detecting a degradation in performance; and
the determination of the new recommended settings is initiated in response to detecting the degradation in performance.
10 . The method of claim 8 , further comprising generating a user notification when the new recommended settings are automatically applied.
11 . The method of claim 1 , further comprising, in response to selection of the manual mode, the selected settings include one or a combination of:
chip frequency,
chip voltage, and
fan speed.
12 . The method of claim 1 , further comprising, in response to selection of the intelligent mode:
collecting data related to the one or more selected computing devices; and
dynamically changing one or more parameters of the dynamic settings based on the collected data to increase performance of the one or more selected computing devices.
13 . The method of claim 12 , wherein collecting data related to the one or more selected computing devices includes:
collecting device data for each of the one or more selected computing devices; and
collecting environmental data for each of the one or more selected computing devices.
14 . The method of claim 13 , wherein:
the collected device data includes at least one of fan speed, chip temperature, chip health, chip voltage, hardware errors, hash rate, and share; and
the collected environmental data includes at least one of temperature, humidity, barometric pressure, and dust level.
15 . The method of claim 12 , wherein dynamically changing one or more parameters of the dynamic settings includes applying machine learning to stored data related to the one or more selected computing devices and the collected data.
16 . The method of claim 12 , wherein dynamically changing one or more parameters of the dynamic settings includes modifying the dynamic settings to optimize at least one of hash rate, hash rate efficiency, and net financial return.
17 . A data center, comprising:
a first computer having a processor and a memory; and
a plurality of second computers in communication with the first computer via one or more networks, at least one second computer of the plurality of second computers disposed on a hash board;
wherein the first computer:
periodically reads and stores status information from the plurality of second computers; and
provides a user interface including:
a first control to select one or more of the plurality of second computers; and
a second control to select one of a plurality of different operating modes, including a manual mode, a semi-automated mode, an automated mode, and an intelligent mode; and
in response to a requested change, the requested change including a selection of one of the plurality of operating modes with the second control for one or more of the plurality of second computers selected with the first control, simulates the effects of the requested change, and based on the results of the simulation, applies selected settings to the selected one or more second computers;
wherein dynamic settings that are dependent on a proper configuration of another dynamic setting are automatically enforced in the intelligent mode;
wherein, in response to detecting that one or more user selected settings exceed a predetermined safe range, generating a warning in the manual mode;
wherein the simulating includes modeling the requested change for the selected one or more of the plurality of second computers and providing simulated results that indicate at least one of expected device damage or estimated reduction in remaining device lifespan.
18 . The data center of claim 17 , wherein:
applying the manual mode includes the first computer operating the selected one or more second computers according to settings selected by a user;
applying the semi-automated mode, the automated mode, or the intelligent mode includes the first computer (a) obtaining performance data for the selected one or more second computers and (b) determining recommended settings according to the obtained performance data;
applying the semi-automated mode includes displaying an additional control to the user to apply the recommended settings;
applying the automated mode includes automatically applying the recommended settings; and
applying the intelligent mode includes determining the recommended settings via applying machine learning to the obtained performance data.
19 . The data center of claim 18 , wherein the selected settings include one or more of chip frequency, chip voltage, and fan speed.
20 . The data center of claim 19 , wherein applying the intelligent mode further includes:
obtaining parameters associated with the selected one or more second computers in addition to the obtained performance data, the parameters including one or a combination of humidity, dust level, and chip health; and
determining the recommended settings according to the parameters and via applying machine learning to the obtained performance data.