Adaptive scheduling host system and scheduling method of GPU virtual resources in cloud game

Abstract

An adaptive scheduling host system of GPU (Graphics Processing Unit) virtual resources in a cloud game comprises a scheduling control module, as well as an agent module, an image application programming interface analysis module and a virtual machine list which are connected with the scheduling control module respectively, wherein the agent module consists of a scheduling module and a monitoring module; all the modules are allocated in a host; the scheduling control module is responsible for information communication among the other modules; and the scheduling control module obtains information of all running virtual machines from the virtual machine list and transmits the information to the requiring module. The system realizes scientific management of the GPU resources in the virtual machines, and increases the utilization ratio of the GPU resources, the enough GPU resources are distributed to all the running virtual machines based on a fair QoS (Quality of Service) adaptive scheduling method in a fair distribution manner, the QoS requirements are met, and the utilization ratio of a whole GPU is maximized.

Description

technical field [0001] The invention relates to a resource self-adaptive scheduling host system in the field of GPU virtualization, which is applied to a cloud game platform, and is specifically a scheduling system that intervenes in an operating system image API. Background technique [0002] The gradual maturity of GPU virtualization technology has promoted the development of cloud game applications, so cloud game applications in cloud services are popular. However, due to the poor performance of the current default GPU resource sharing mechanism, the user experience of cloud games is inevitably damaged by some real-time uncertain factors, such as rendering complex game scenes. [0003] In video stream quality analysis, FPS (Frames Per Second) is defined as the number of frames per second, which measures the amount of information used to save and display dynamic video, that is, the number of frames of animation or video. [0004] In the user experience of cloud games, QoS...

AI Technical Summary

Problems solved by technology

But they all have the following shortcomings, GERM does not consider QoS requirements and the fixed frame rate method cannot effectively use hardware resources

TimeGraph cannot guarantee that all virtual machines meet the QoS requirements, especially when the important load is less

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