计算机技术与发展2025，Vol.35Issue(10)：81-88,8.DOI:10.20165/j.cnki.ISSN1673-629X.2025.0142
基于强化学习的负载感知CPU资源分配和管理方法
Workload-aware CPU Resource Allocation and Management Based on Reinforcement Learning
摘要
Abstract
With the increase of the number of CPU cores,rational allocation of CPU cores is of great significance to reduce the power con-sumption for system.How to accurately allocate and manager CPU resources according to the workload of a system at runtime is a key problem.Although the current processor design provides a lot of power optimization(such as dynamic voltage frequency adjustment DVFS),it is not enough to make these mechanisms work only relying on the chips.The integrated design of software and hardware is needed.However,currently there is no way to maximally adopt these hardware mechanisms through software.In recent years,the machine learning technique has shown great potential in various fields,and a lot of research work based on machine learning has emerged.Among them,reinforcement learning is suitable for system environment awareness and system resource management because of its strong adaptability.Therefore,a load-aware CPU resource allocation and management method based on reinforcement learning and scalability of the proposed method.关键词
负载感知/强化学习/多核系统/CPU资源分配管理/绑核调频Key words
workload-aware/reinforcement learning/multi-core system/CPU resource allocation and management/bind core and frequency adjust分类
信息技术与安全科学引用本文复制引用
许荣飞,苏志远,麻付强,吴保锡..基于强化学习的负载感知CPU资源分配和管理方法[J].计算机技术与发展,2025,35(10):81-88,8.基金项目
山东省自然科学基金创新发展联合基金项目(ZR2022LZH013) （ZR2022LZH013）
泰山产业领军人才工程资助(2023TSCYCX-5) （2023TSCYCX-5）
