Multitenancy for Fast and Programmable Networks in the Cloud


Tao Wang, New York University; Hang Zhu, Johns Hopkins University; Fabian Ruffy, New York University; Xin Jin, Johns Hopkins University; Anirudh Sivaraman, New York University; Dan R. K. Ports, Microsoft Research; Aurojit Panda, New York University


Fast and programmable network devices are now readily available, both in the form of programmable switches and smart network-interface cards. Going forward, we envision that these devices will be widely deployed in the networks of cloud providers (e.g., AWS, Azure, and GCP) and exposed as a programmable surface for cloud customers—similar to how cloud customers can today rent CPUs, GPUs, FPGAs, and ML accelerators. Making this vision a reality requires us to develop a mechanism to share the resources of a programmable network device across multiple cloud tenants. In other words, we need to provide multitenancy on these devices. In this position paper, we design compile and run-time approaches to multitenancy. We present preliminary results showing that our design provides both efficient resource utilization and isolation of tenant programs from each other.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

@inproceedings {254134,
author = {Tao Wang and Hang Zhu and Fabian Ruffy and Xin Jin and Anirudh Sivaraman and Dan R. K. Ports and Aurojit Panda},
title = {Multitenancy for Fast and Programmable Networks in the Cloud},
booktitle = {12th {USENIX} Workshop on Hot Topics in Cloud Computing (HotCloud 20)},
year = {2020},
url = {},
publisher = {{USENIX} Association},
month = jul,

Presentation Video