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Zhongqing Chen

dblp:351/5759 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Transport protocols and congestion control · 57% Software-defined and programmable networks · 43%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 80% Storage systems · 20%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software-defined and programmable networks
programmable data plane
1.012026
SmartNS: Enabling Line-rate and Flexible Network Stack with SmartNIC · EuroSys 2026
Cloud and datacenter computing › computation offloading › network function offloading
SmartNIC offload
1.012026
SmartNS: Enabling Line-rate and Flexible Network Stack with SmartNIC · EuroSys 2026
Transport protocols and congestion control
TCP
0.712023
Deploying User-space TCP at Cloud Scale with LUNA · USENIX ATC 2023
Transport protocols and congestion control › TCP
user-space TCP
0.712023
Deploying User-space TCP at Cloud Scale with LUNA · USENIX ATC 2023

Methods — techniques the papers use, named apart from their topics

in-cache processing · 2.0header-only offloading · 2.0
YearPublicationVenuePosition
2026 SmartNS: Enabling Line-rate and Flexible Network Stack with SmartNIC
abstract
As the gap between network and CPU speeds rapidly increases, the CPU-centric network stack proves inadequate due to excessive CPU and memory overheads. Though hardware-offloaded network stacks alleviate these issues, they suffer from limited flexibility in both control and data planes. It seems promising to offload network stacks to Smart-NICs to provide high flexibility. However, naive offloading leads to low throughput due to the inherent architectural limitations of widespread off-path SmartNICs. Even simple operations on staged network traffic would overwhelm the limited SmartNIC memory bandwidth. To this end, we design SmartNS, a SmartNIC-centric network stack with software transport programmability and line-rate packet processing capabilities. To tackle the limitations of SmartNIC-induced challenges, we propose a header-only offloading TX path and an unlimited-working-set in-cache processing RX path to minimize memory traffic to fit the wimpy SmartNIC memory bandwidth. To fully utilize the SmartNIC computing resources, we propose a programmable offloading engine to enable cloud providers to offload customized tasks along with the network stack processing. We prototype SmartNS using the widespread Nvidia BlueField-3 SmartNIC, and implement RoCEv2 and Solar transport protocols by leveraging SmartNS's software programmability. SmartNS achieves 2.2× higher throughput than the microkernel-based baseline in block storage disaggregation and 1.3× higher throughput than the hardware-offloaded baseline in KVCache transfer.
Xuzheng Chen, Jie Zhang 0081, Baolin Zhu, Xueying Zhu, Zhongqing Chen, Lingjun Zhu, Yin Zhang 0006, Yuanchao Shu, Peng Cheng 0001, Zeke Wang
EuroSys5
2023 Deploying User-space TCP at Cloud Scale with LUNA
Lingjun Zhu, Erci Xu, Shuguang Chen, Xingyu Liao, Zhendan Yang, Zhongqing Chen, Yijun Hou, Jiaji Zhu, Jiesheng Wu
USENIX ATC12