Zhaoyang Huang;Yanjie Tan;Yifu Zhu;Huailiang Tan;Keqin Li
{"title":"MTDA:高效公平的多租户 DPU 卸载方法","authors":"Zhaoyang Huang;Yanjie Tan;Yifu Zhu;Huailiang Tan;Keqin Li","doi":"10.1109/TSC.2024.3433588","DOIUrl":null,"url":null,"abstract":"In modern cloud computing environment, the offloading potential of DPU must be fully exploited for multiple tenants. Existing DPU offloading techniques lack the capability to perform the fair allocation of a DPU domain's internal resources among tenants with various performance requirements. In this article, we propose a virtual multi-channel DPU offloading architecture for multiple tenants (MTDA) and implement it on a BlueField-2 DPU platform to achieve stability and fairness in resource allocation for generic datacenter tasks. MTDA provides an independent virtual channel for each tenant before their requests are submitted to avoid competition among tenants. Considering the diverse requirements of tenants, MTDA constructs a credit-based resource allocation model and a traffic-aware scheduling algorithm to fully utilize the rich computing resources of DPU and improve the fairness of DPU resource allocation. Experimental results show that MTDA increases the throughput by up to 101.2%, 143.2%, 36.1%, and 41.7%, lowers the latency by up to 50.3%, 58.9%, 26.6%, and 29.4%, improves the fairness by up to 98.8%, 99.0%, 98.3%, and 98.4%, and provides more stable performance for multi-tenants, compared with DPDK, iPipe, FairNIC, and LogNIC.","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"17 6","pages":"3971-3984"},"PeriodicalIF":5.8000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MTDA: Efficient and Fair DPU Offloading Method for Multiple Tenants\",\"authors\":\"Zhaoyang Huang;Yanjie Tan;Yifu Zhu;Huailiang Tan;Keqin Li\",\"doi\":\"10.1109/TSC.2024.3433588\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In modern cloud computing environment, the offloading potential of DPU must be fully exploited for multiple tenants. Existing DPU offloading techniques lack the capability to perform the fair allocation of a DPU domain's internal resources among tenants with various performance requirements. In this article, we propose a virtual multi-channel DPU offloading architecture for multiple tenants (MTDA) and implement it on a BlueField-2 DPU platform to achieve stability and fairness in resource allocation for generic datacenter tasks. MTDA provides an independent virtual channel for each tenant before their requests are submitted to avoid competition among tenants. Considering the diverse requirements of tenants, MTDA constructs a credit-based resource allocation model and a traffic-aware scheduling algorithm to fully utilize the rich computing resources of DPU and improve the fairness of DPU resource allocation. Experimental results show that MTDA increases the throughput by up to 101.2%, 143.2%, 36.1%, and 41.7%, lowers the latency by up to 50.3%, 58.9%, 26.6%, and 29.4%, improves the fairness by up to 98.8%, 99.0%, 98.3%, and 98.4%, and provides more stable performance for multi-tenants, compared with DPDK, iPipe, FairNIC, and LogNIC.\",\"PeriodicalId\":13255,\"journal\":{\"name\":\"IEEE Transactions on Services Computing\",\"volume\":\"17 6\",\"pages\":\"3971-3984\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Services Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10609547/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Services Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10609547/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
MTDA: Efficient and Fair DPU Offloading Method for Multiple Tenants
In modern cloud computing environment, the offloading potential of DPU must be fully exploited for multiple tenants. Existing DPU offloading techniques lack the capability to perform the fair allocation of a DPU domain's internal resources among tenants with various performance requirements. In this article, we propose a virtual multi-channel DPU offloading architecture for multiple tenants (MTDA) and implement it on a BlueField-2 DPU platform to achieve stability and fairness in resource allocation for generic datacenter tasks. MTDA provides an independent virtual channel for each tenant before their requests are submitted to avoid competition among tenants. Considering the diverse requirements of tenants, MTDA constructs a credit-based resource allocation model and a traffic-aware scheduling algorithm to fully utilize the rich computing resources of DPU and improve the fairness of DPU resource allocation. Experimental results show that MTDA increases the throughput by up to 101.2%, 143.2%, 36.1%, and 41.7%, lowers the latency by up to 50.3%, 58.9%, 26.6%, and 29.4%, improves the fairness by up to 98.8%, 99.0%, 98.3%, and 98.4%, and provides more stable performance for multi-tenants, compared with DPDK, iPipe, FairNIC, and LogNIC.
期刊介绍:
IEEE Transactions on Services Computing encompasses the computing and software aspects of the science and technology of services innovation research and development. It places emphasis on algorithmic, mathematical, statistical, and computational methods central to services computing. Topics covered include Service Oriented Architecture, Web Services, Business Process Integration, Solution Performance Management, and Services Operations and Management. The transactions address mathematical foundations, security, privacy, agreement, contract, discovery, negotiation, collaboration, and quality of service for web services. It also covers areas like composite web service creation, business and scientific applications, standards, utility models, business process modeling, integration, collaboration, and more in the realm of Services Computing.