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甬江数学讲坛196讲(2021年第55讲)
2021-11-04 09:26     (点击:)

报告题目:Learning to Schedule Multi-NUMA Virtual Machines via Reinforcement Learning
人:王祥丰 教授(华东师范大学)

报告时间:2021118 下午2:00开始

报告地点:腾讯会议 366 842 021 会议密码:2021
报告摘要:With the rapid development of cloud computing, the importance of dynamic virtual machine scheduling is increasing. Existing works formulate the VM scheduling as a bin-packing problem and design greedy methods to solve it. However, cloud service providers widely adopt multi-NUMA architecture servers in recent years, and existing methods do not consider the architecture. This paper formulates the multi-NUMA VM scheduling into a novel structured combinatorial optimization and transforms it into a reinforcement learning problem. We propose a reinforcement learning algorithm called SchedRL with a delta reward scheme and an episodic guided sampling strategy to solve the problem efficiently. Evaluating on a public dataset of Azure under two different scenarios, our SchedRL outperforms FirstFit and BestFit on the fulfill number and allocation rate.
报告人简介:王祥丰,华东师范大学计算机科学与技术学院副教授,2009年和2014年分别获得南京大学学士和博士学位;攻读博士学位期间,获得国家留学基金委资助赴美国明尼苏达大学联合培养。毕业后,加入华东师范大学计算机科学与技术学院,主要研究方向是多智能体强化学习、分布式优化、可信机器学习等。已在IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on CyberneticsIEEE Transactions on Signal ProcessingIEEE Transactions on Medical Imaging、《软件学报》等人工智能国际权威期刊以及CVPRIJCAIAAAIAAMASUAIICMRICASSP等人工智能国际权威会议发表论文30余篇;已在Mathematical ProgrammingMathematics of Operations ResearchSIAM Journal on Scientific Computing等运筹学国际权威期刊发表论文。目前担任上海市运筹学会青年委员、上海市计算机学会青工委委员。

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