DockRDMA: Hybrid RDMA Virtualization for Containerized Clouds
Containers have become the de facto choice for major cloud services. Meanwhile, with demands for extremely high performance, data centers have widely adopted RDMA for their online services. RDMA virtualization is the critical technology that enables RDMA for containers. Hybrid RDMA virtualization leverages the software flexibility in the control path, and keeps the native performance in the data path. Thus, it is the best choice for RDMA virtualization. State-of-the-art hybrid RDMA virtualization cannot address containerspecific problems. This paper proposes DockRDMA, the first hybrid RDMA virtualization solution for containerized clouds. DockRDMA develops several mechanisms, including embedding physical addresses in virtual ones to provide efficient address translation, hybrid network policy enforcement at scale, a general virtual RDMA NIC initialization method to be compatible with all container platforms, and namespace checking to protect the RDMA NIC instances. Evaluation results show that DockRDMA provides bare-metal RDMA performance in the data path, and almost native communication setup time in the control path. Compared with the state-of-the-art hybrid virtualization technology, DockRDMA reduces Hadoop job completion time by 6%. It offers seamless integration with existing container platforms, protects critical information of RDMA NIC instances, and exhibits excellent scalability to meet diverse network policies required by different containers.
Authors
- Ran Shu (ORCID: https://orcid.org/0000-0002-2021-4917)
- Fengyuan Ren
- Yiran Zhang (ORCID: https://orcid.org/0000-0002-3555-0155)
- Qingkai Meng
- Bo Wang (ORCID: https://orcid.org/0000-0003-3598-5359)
- Xiaoyu Li (ORCID: https://orcid.org/0000-0002-0241-6152)
- Xiaohui Luo
- Zhongjie Chen (ORCID: https://orcid.org/0000-0001-7487-4614)
Institutions
- Microsoft Research Asia (China) (CN)
- Tsinghua University (CN)
Publication Details
- Published
- 2024-10-28
- DOI
- https://doi.org/10.1109/icnp61940.2024.10858532
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China