{"title":"计算力网络中基于 RAR 的可靠高效分布式模型训练","authors":"Ling Chen;Yajie Li;Carlos Natalino;Yongcheng Li;Boxin Zhang;Yingbo Fan;Wei Wang;Yongli Zhao;Jie Zhang","doi":"10.1364/JOCN.511165","DOIUrl":null,"url":null,"abstract":"The computing power network (CPN) is a novel network technology that integrates computing power from the cloud, edge, and terminals using IP/optical cross-layer networks for distributed computing. CPNs can provide an effective solution for distributed model training (DMT). As a bandwidth optimization architecture based on data parallelism, ring all-reduce (RAR) is widely used in DMT. However, any node or link failure on the ring can interrupt or block the requests deployed on the ring. Meanwhile, due to the resource competition of batch RAR-based DMT requests, inappropriate scheduling strategies will also lead to low training efficiency or congestion. As far as we know, there is currently no research that considers the survivability of rings in scheduling strategies for RAR-based DMT. To fill this gap, we propose a scheduling scheme for RAR-based DMT requests in CPNs to optimize the allocation of computing and wavelength resources considering the time dimension while ensuring reliability. In practical scenarios, service providers may focus on different performance metrics. We formulate an integer linear programming (ILP) model and a RAR-based DMT deployment algorithm (RDDA) to solve this problem considering four optimization objectives under the premise of the minimum blocking rate: minimum computing resource consumption, minimum wavelength resource consumption, minimum training time, and maximum reliability. Simulation results demonstrate that our model satisfies the reliability requirements while achieving corresponding optimal performance for DMT requests under four optimization objectives.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 5","pages":"527-540"},"PeriodicalIF":4.0000,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reliable and efficient RAR-based distributed model training in computing power network\",\"authors\":\"Ling Chen;Yajie Li;Carlos Natalino;Yongcheng Li;Boxin Zhang;Yingbo Fan;Wei Wang;Yongli Zhao;Jie Zhang\",\"doi\":\"10.1364/JOCN.511165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The computing power network (CPN) is a novel network technology that integrates computing power from the cloud, edge, and terminals using IP/optical cross-layer networks for distributed computing. CPNs can provide an effective solution for distributed model training (DMT). As a bandwidth optimization architecture based on data parallelism, ring all-reduce (RAR) is widely used in DMT. However, any node or link failure on the ring can interrupt or block the requests deployed on the ring. Meanwhile, due to the resource competition of batch RAR-based DMT requests, inappropriate scheduling strategies will also lead to low training efficiency or congestion. As far as we know, there is currently no research that considers the survivability of rings in scheduling strategies for RAR-based DMT. To fill this gap, we propose a scheduling scheme for RAR-based DMT requests in CPNs to optimize the allocation of computing and wavelength resources considering the time dimension while ensuring reliability. In practical scenarios, service providers may focus on different performance metrics. We formulate an integer linear programming (ILP) model and a RAR-based DMT deployment algorithm (RDDA) to solve this problem considering four optimization objectives under the premise of the minimum blocking rate: minimum computing resource consumption, minimum wavelength resource consumption, minimum training time, and maximum reliability. Simulation results demonstrate that our model satisfies the reliability requirements while achieving corresponding optimal performance for DMT requests under four optimization objectives.\",\"PeriodicalId\":50103,\"journal\":{\"name\":\"Journal of Optical Communications and Networking\",\"volume\":\"16 5\",\"pages\":\"527-540\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Optical Communications and Networking\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10507175/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Optical Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10507175/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Reliable and efficient RAR-based distributed model training in computing power network
The computing power network (CPN) is a novel network technology that integrates computing power from the cloud, edge, and terminals using IP/optical cross-layer networks for distributed computing. CPNs can provide an effective solution for distributed model training (DMT). As a bandwidth optimization architecture based on data parallelism, ring all-reduce (RAR) is widely used in DMT. However, any node or link failure on the ring can interrupt or block the requests deployed on the ring. Meanwhile, due to the resource competition of batch RAR-based DMT requests, inappropriate scheduling strategies will also lead to low training efficiency or congestion. As far as we know, there is currently no research that considers the survivability of rings in scheduling strategies for RAR-based DMT. To fill this gap, we propose a scheduling scheme for RAR-based DMT requests in CPNs to optimize the allocation of computing and wavelength resources considering the time dimension while ensuring reliability. In practical scenarios, service providers may focus on different performance metrics. We formulate an integer linear programming (ILP) model and a RAR-based DMT deployment algorithm (RDDA) to solve this problem considering four optimization objectives under the premise of the minimum blocking rate: minimum computing resource consumption, minimum wavelength resource consumption, minimum training time, and maximum reliability. Simulation results demonstrate that our model satisfies the reliability requirements while achieving corresponding optimal performance for DMT requests under four optimization objectives.
期刊介绍:
The scope of the Journal includes advances in the state-of-the-art of optical networking science, technology, and engineering. Both theoretical contributions (including new techniques, concepts, analyses, and economic studies) and practical contributions (including optical networking experiments, prototypes, and new applications) are encouraged. Subareas of interest include the architecture and design of optical networks, optical network survivability and security, software-defined optical networking, elastic optical networks, data and control plane advances, network management related innovation, and optical access networks. Enabling technologies and their applications are suitable topics only if the results are shown to directly impact optical networking beyond simple point-to-point networks.