Abstract: A method and a system for scheduling a virtual machine are disclosed. The method includes: obtaining energy consumption data of a rack and energy consumption data of host computers, wherein the rack is used to place the host computers; determining power consumption data of a virtual machine; determining a target host computer corresponding to the virtual machine according to the energy consumption data of the rack, the energy consumption data of the host computers, and the power consumption data of the virtual machine; and dispatching the virtual machine to the target host computer. The present disclosure solves the technical problems of unbalanced power consumption scheduling caused by virtual machine scheduling methods that are implemented only according to CPU parameters in the existing technologies.

Abstract: Systems and methods for a hybrid system-on-chip usable for predicting performance and power requirements of a host server include a big cores module, including central processing units, for receiving and pre-processing performance and power metrics data of the host server and to allocate computing resources, a small cores module, including massively parallel processing units, for mapping each instance associated with host server in the performance and power metrics data to a corresponding massively parallel processing unit based on the allocated computing resources for a per-instance metrics calculation, and an artificial intelligence (AI) accelerator for calculating performance and power prediction results based on the per-instance calculations from the small cores module.

Abstract: A method and a system for scheduling a virtual machine are disclosed. The method includes: obtaining energy consumption data of a rack and energy consumption data of host computers, wherein the rack is used to place the host computers; determining power consumption data of a virtual machine; determining a target host computer corresponding to the virtual machine according to the energy consumption data of the rack, the energy consumption data of the host computers, and the power consumption data of the virtual machine; and dispatching the virtual machine to the target host computer. The present disclosure solves the technical problems of unbalanced power consumption scheduling caused by virtual machine scheduling methods that are implemented only according to CPU parameters in the existing technologies.

Abstract: A method and an apparatus for scheduling a virtual machine are disclosed in. The method includes predicting resource data required by a virtual machine in a next time period to obtain a prediction result; obtaining used resource data and available resource data of candidate host machines; adding the prediction result to used resource data of each candidate host machine to obtain a superimposition result of each candidate host machine; and separately comparing the superimposition result of each candidate host machine with available resource data of each host machine, and selecting a target host machine corresponding to the virtual machine from the candidate host machines. The present disclosure solves the technical problem of a large waste of resources caused by the needs of a host machine to reserve resources for respective peaks of each virtual machine in the existing technologies.

Abstract: Systems and methods for a hybrid system-on-chip usable for predicting performance and power requirements of a host server include a big cores module, including central processing units, for receiving and pre-processing performance and power metrics data of the host server and to allocate computing resources, a small cores module, including massively parallel processing units, for mapping each instance associated with host server in the performance and power metrics data to a corresponding massively parallel processing unit based on the allocated computing resources for a per-instance metrics calculation, and an artificial intelligence (AI) accelerator for calculating performance and power prediction results based on the per-instant calculations from the small cores module.

Abstract: A virtual machine dispatching method is disclosed. The method includes selecting host machines having performance parameters satisfying preset allocation conditions of a virtual machine to be dispatched from a host pool; determining whether respective available spaces of disk blocks of the host machines are greater than or equal to a space of a virtual machine disk mounted to the virtual machine to be dispatched, and filtering to obtain one or more host machines of which one or more disk blocks have available spaces greater than or equal to the space of the virtual machine disk; and selecting a host machine as an available host machine from among the one or more host machines, allocating the virtual machine to be dispatched to the available host machine, and creating the virtual machine disk mounted to the virtual machine to be dispatched on a corresponding disk block of the available host machine.