Yibo Zhu, Haggai Eran, D. Firestone, Chuanxiong Guo, Marina Lipshteyn, Yehonatan Liron, J. Padhye, S. Raindel, M. H. Yahia, Ming Zhang
{"title":"Congestion Control for Large-Scale RDMA Deployments","authors":"Yibo Zhu, Haggai Eran, D. Firestone, Chuanxiong Guo, Marina Lipshteyn, Yehonatan Liron, J. Padhye, S. Raindel, M. H. Yahia, Ming Zhang","doi":"10.1145/2785956.2787484","DOIUrl":null,"url":null,"abstract":"Modern datacenter applications demand high throughput (40Gbps) and ultra-low latency (< 10 μs per hop) from the network, with low CPU overhead. Standard TCP/IP stacks cannot meet these requirements, but Remote Direct Memory Access (RDMA) can. On IP-routed datacenter networks, RDMA is deployed using RoCEv2 protocol, which relies on Priority-based Flow Control (PFC) to enable a drop-free network. However, PFC can lead to poor application performance due to problems like head-of-line blocking and unfairness. To alleviates these problems, we introduce DCQCN, an end-to-end congestion control scheme for RoCEv2. To optimize DCQCN performance, we build a fluid model, and provide guidelines for tuning switch buffer thresholds, and other protocol parameters. Using a 3-tier Clos network testbed, we show that DCQCN dramatically improves throughput and fairness of RoCEv2 RDMA traffic. DCQCN is implemented in Mellanox NICs, and is being deployed in Microsoft's datacenters.","PeriodicalId":268472,"journal":{"name":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"455","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2785956.2787484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 455
Abstract
Modern datacenter applications demand high throughput (40Gbps) and ultra-low latency (< 10 μs per hop) from the network, with low CPU overhead. Standard TCP/IP stacks cannot meet these requirements, but Remote Direct Memory Access (RDMA) can. On IP-routed datacenter networks, RDMA is deployed using RoCEv2 protocol, which relies on Priority-based Flow Control (PFC) to enable a drop-free network. However, PFC can lead to poor application performance due to problems like head-of-line blocking and unfairness. To alleviates these problems, we introduce DCQCN, an end-to-end congestion control scheme for RoCEv2. To optimize DCQCN performance, we build a fluid model, and provide guidelines for tuning switch buffer thresholds, and other protocol parameters. Using a 3-tier Clos network testbed, we show that DCQCN dramatically improves throughput and fairness of RoCEv2 RDMA traffic. DCQCN is implemented in Mellanox NICs, and is being deployed in Microsoft's datacenters.