HPCC: high precision congestion control
Name
hpcc.pdf
Description
Accepted version
Size
1.49 MB
Format
Adobe PDF
Checksum (MD5)
467d04c8fec1786cabc30e94188691f4
Author(s)
Li, Yuliang
Miao, Rui
Liu, Hongqiang Harry
Zhuang, Yan
Feng, Fei
Tang, Lingbo
Cao, Zheng
Zhang, Ming
Kelly, Frank
Alizadeh, Mohammad
Date Issued
August 2019
Journal
SIGCOMM 2019 - Proceedings of the 2019 Conference of the ACM Special Interest Group on Data Communication
Publisher
Association for Computing Machinery (ACM)
Citation
Li, Yuliang, Miao, Rui, Liu, Hongqiang Harry, Zhuang, Yan, Feng, Fei et al. 2019. "HPCC: high precision congestion control." SIGCOMM 2019 - Proceedings of the 2019 Conference of the ACM Special Interest Group on Data Communication.
Version
Author's final manuscript
Abstract
© 2019 Association for Computing Machinery. Congestion control (CC) is the key to achieving ultra-low latency, high bandwidth and network stability in high-speed networks. From years of experience operating large-scale and high-speed RDMA networks, we find the existing high-speed CC schemes have inherent limitations for reaching these goals. In this paper, we present HPCC (High Precision Congestion Control), a new high-speed CC mechanism which achieves the three goals simultaneously. HPCC leverages in-network telemetry (INT) to obtain precise link load information and controls traffic precisely. By addressing challenges such as delayed INT information during congestion and overreaction to INT information, HPCC can quickly converge to utilize free bandwidth while avoiding congestion, and can maintain near-zero in-network queues for ultra-low latency. HPCC is also fair and easy to deploy in hardware. We implement HPCC with commodity programmable NICs and switches. In our evaluation, compared to DCQCN and TIMELY, HPCC shortens flow completion times by up to 95%, causing little congestion even under large-scale incasts.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3341302.3342085
