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Shengdong Dai

dblp:390/0548 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2026
0009-0008-1939-1087ORCID · reported

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

Software engineering, systems software and programming languages · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 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 architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 52% Memory systems · 48%
Computer networks
1 paper
Internet architecture and protocols · 50% Routing and switching · 50%
Software engineering, system software, and programming languages
1 paper
Operating systems · 100%

Topics — the 10 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems › memory hierarchy › cache hierarchy management
last-level cache management
1.012026
Cacheman: A Comprehensive Last-Level Cache Management System for Multi-tenant Clouds · PPoPP 2026
Cloud and datacenter computing › multi-tenancy
multi-tenant cloud
1.012026
Cacheman: A Comprehensive Last-Level Cache Management System for Multi-tenant Clouds · PPoPP 2026
Routing and switching › qos routing
priority routing
0.912025
To PRI or Not To PRI, That's the question · OSDI 2025
Operating systems › resource management › memory management › virtual memory
demand paging
0.812024
VPRI: Efficient I/O Page Fault Handling via Software-Hardware Co-Design for IaaS Clouds · SOSP 2024
Operating systems › resource management
memory management
0.812024
VPRI: Efficient I/O Page Fault Handling via Software-Hardware Co-Design for IaaS Clouds · SOSP 2024
Cloud and datacenter computing › virtualization
device pass-through
0.812024
VPRI: Efficient I/O Page Fault Handling via Software-Hardware Co-Design for IaaS Clouds · SOSP 2024
Cloud and datacenter computing › cloud service models
infrastructure as a service
0.812024
VPRI: Efficient I/O Page Fault Handling via Software-Hardware Co-Design for IaaS Clouds · SOSP 2024
Memory systems › memory management
virtual memory
0.812024
VPRI: Efficient I/O Page Fault Handling via Software-Hardware Co-Design for IaaS Clouds · SOSP 2024
Memory systems › cache management
cache allocation
0.312026
Cacheman: A Comprehensive Last-Level Cache Management System for Multi-tenant Clouds · PPoPP 2026
Memory systems › memory management › memory management unit
IOMMU
0.212024
VPRI: Efficient I/O Page Fault Handling via Software-Hardware Co-Design for IaaS Clouds · SOSP 2024

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

software-hardware co-design · 1.5real-time allocation algorithm · 1.0gradient-based sharing · 1.0
YearPublicationVenuePosition
2026 Cacheman: A Comprehensive Last-Level Cache Management System for Multi-tenant Clouds
abstract
Competition for the last-level cache (LLC) is a long-standing issue in multi-tenant cloud environments, often leading to severe performance interference among co-located virtual machines. LLC management in the cloud faces unique challenges, including unpredictable tenant workloads, misaligned performance metrics, and the need to ensure fairness under service level agreements (SLAs). Existing LLC allocation methods fall short in addressing these challenges. We present Cacheman, a comprehensive LLC management system designed from real-world cloud deployment experience. Cacheman introduces a novel gradient-based sharing mechanism for LLC ways, enabling smooth LLC allocation adjustments that simultaneously improve fairness and utilization efficiency. Its real-time allocation algorithm promptly detects and mitigates unfair LLC allocation, adapting to dynamic workloads with second-scale responsiveness. Additionally, Cacheman supports performance consistency for tenants running distributed applications by enforcing negotiated upper bounds on cache usage. Extensive experiments demonstrate that Cacheman effectively achieves its multi-dimensional goals, and long-term production deployment further shows that it significantly reduces SLA violations caused by LLC contention.
Xiaokang Hu, Yuchao Cao, Naixuan Guan, Yifan Wu 0037, Xishi Qiu, Shengdong Dai, Ben Luo, Sanchuan Cheng, Fudong Qiu, Yibin Shen, Jiesheng Wu
PPoPP6
2025 To PRI or Not To PRI, That's the question
Yun Wang 0039, Xianting Tian, Ben Luo, Zhixiang Wei, Zhibai Huang, Kailiang Xu, Kaihuan Peng, Kaijie Guo, Guangjian Wang, Shengdong Dai, Yibin Shen, Jiesheng Wu, Zhengwei Qi
OSDI13
2024 VPRI: Efficient I/O Page Fault Handling via Software-Hardware Co-Design for IaaS Clouds
abstract
Device pass-through has been widely adopted by cloud service providers to achieve near bare-metal I/O performance in virtual machines (VMs). However, this approach requires static pinning of VM memory, making on-demand paging unavailable. The hardware device I/O page fault (IOPF) capability offers an optimal solution to this limitation. Current IOPF approaches, using either standard IOMMU capabilities (ATS+PRI) or devices with independent IOMMU implementations, have not gained widespread adoption in public Infrastructure-as-a-Service clouds. This is due to high costs, platform dependency, and significant impacts on performance and service level objectives (SLOs). We present the Virtualized Page Request Interface (VPRI), a novel IOPF system developed through software-hardware collaboration. VPRI is not only platform-independent, free from address translation complexities, but also cost-effective, and designed to minimize SLO impact. Our work enables large-scale deployment of IOPF capability in Alibaba Cloud with negligible impact on SLOs. When integrated with memory management software, it significantly enhances memory utilization in public IaaS clouds, effectively overcoming the static memory pinning restriction associated with pass-through devices.
Kaijie Guo, Dingji Li, Ben Luo, Yibin Shen, Kaihuan Peng, Ning Luo 0003, Shengdong Dai, Jianming Song, Zeyu Mi
SOSP7