A Case for Adaptive Resource Management in Alibaba Datacenter Using Neural Networks
文献类型：期刊论文
| 作者 | Wang, Sa1,2,3; Zhu, Yan-Hai4; Chen, Shan-Pei4; Wu, Tian-Ze1,2; Li, Wen-Jie1,2; Zhan, Xu-Sheng1,2; Ding, Hai-Yang4; Shi, Wei-Song5; Bao, Yun-Gang1,2,3 |
| 刊名 | JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
 |
| 出版日期 | 2020 |
| 卷号 | 35期号:1页码:209-220 |
| 关键词 | resource management neural network resource efficiency tail latency |
| ISSN号 | 1000-9000 |
| DOI | 10.1007/s11390-020-9732-x |
| 英文摘要 | Both resource efficiency and application QoS have been big concerns of datacenter operators for a long time, but remain to be irreconcilable. High resource utilization increases the risk of resource contention between co-located workload, which makes latency-critical (LC) applications suffer unpredictable, and even unacceptable performance. Plenty of prior work devotes the effort on exploiting effective mechanisms to protect the QoS of LC applications while improving resource efficiency. In this paper, we propose MAGI, a resource management runtime that leverages neural networks to monitor and further pinpoint the root cause of performance interference, and adjusts resource shares of corresponding applications to ensure the QoS of LC applications. MAGI is a practice in Alibaba datacenter to provide on-demand resource adjustment for applications using neural networks. The experimental results show that MAGI could reduce up to 87.3% performance degradation of LC application when co-located with other antagonist applications. |
| 资助项目 | National Key Research and Development Program of China[2016YFB1000201] ; National Natural Science Foundation of China[61420106013] ; National Natural Science Foundation of China[61702480] ; Youth Innovation Promotion Association of Chinese Academy of Sciences and Alibaba Innovative Research (AIR) Program |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000512098800013 |
| 出版者 | SCIENCE PRESS |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/14689]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Zhu, Yan-Hai |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Peng Cheng Lab, Shenzhen 518055, Peoples R China 4.Alibaba Inc, Hangzhou 311121, Peoples R China 5.Wayne State Univ, Dept Comp Sci, Detroit, MI 48202 USA |
| 推荐引用方式 GB/T 7714 | Wang, Sa,Zhu, Yan-Hai,Chen, Shan-Pei,et al. A Case for Adaptive Resource Management in Alibaba Datacenter Using Neural Networks[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2020,35(1):209-220. |
| APA | Wang, Sa.,Zhu, Yan-Hai.,Chen, Shan-Pei.,Wu, Tian-Ze.,Li, Wen-Jie.,...&Bao, Yun-Gang.(2020).A Case for Adaptive Resource Management in Alibaba Datacenter Using Neural Networks.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,35(1),209-220. |
| MLA | Wang, Sa,et al."A Case for Adaptive Resource Management in Alibaba Datacenter Using Neural Networks".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 35.1(2020):209-220. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。