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Kaijie Guo

dblp:170/2419 · DBLP profile ↗
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4ranked-venue papers
1as first author
4since 2021 · last 2025
—ORCID · conflict

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

Software engineering, systems software and programming languages · 3 · 1 first-author · 3 since 2021Artificial intelligence and machine learning · 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 · 77% Memory systems · 18% Hardware accelerators and domain-specific architectures · 5%
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 11 heaviest of 12, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Routing and switching › qos routing
priority routing
0.912025
To PRI or Not To PRI, That's the question · OSDI 2025
Cloud and datacenter computing
cluster resource management and scheduling
0.912025
Tai Chi: A General High-Efficiency Scheduling Framework for SmartNICs in Hyperscale Clouds · SOSP 2025
Cloud and datacenter computing › quality of service
SLO-aware scheduling
0.912025
Tai Chi: A General High-Efficiency Scheduling Framework for SmartNICs in Hyperscale Clouds · SOSP 2025
Cloud and datacenter computing › computation offloading › network function offloading
SmartNIC offload
0.912025
Tai Chi: A General High-Efficiency Scheduling Framework for SmartNICs in Hyperscale Clouds · SOSP 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
Hardware accelerators and domain-specific architectures › network accelerator
SmartNIC
0.312025
Tai Chi: A General High-Efficiency Scheduling Framework for SmartNICs in Hyperscale Clouds · SOSP 2025
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 · 1.5
YearPublicationVenuePosition
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
OSDI10
2025 Tai Chi: A General High-Efficiency Scheduling Framework for SmartNICs in Hyperscale Clouds
abstract
Cloud service providers increasingly adopt SmartNICs to offload data-plane services (e.g., DPDK and SPDK) and control-plane tasks (such as disk and NIC initialization). Our analysis of production environments reveals that data-plane services statically provision CPUs for peak load, resulting in 67.5% idle CPU cycles during 99% of their runtime in IaaS clouds, leading to wasted CPU resources. On the other hand, control-plane tasks fail to meet critical Service Level Objectives (SLOs), such as virtual machine startup time. Unfortunately, achieving control-plane SLO improvements through co-scheduling with idle data-plane services remains highly challenging, due to the combined effects of intrinsic scheduling latency and the substantial architectural complexity inherent to control-plane ecosystems.
Bang Di, Kaijie Guo, Yibin Shen, Sanchuan Cheng, Fudong Qiu, Xiaokang Hu, Naixuan Guan, Dongdong Huang, Jinhu Li, Yi Wang 0004, Yifang Yang, Yilong Lv, Zhenwei Lu, Jiesheng Wu
SOSP3
2025 Remaining useful-life prediction of lithium battery based on neural-network ensemble via conditional variational autoencoder
Hengshan Zhang, Kaijie Guo, Yanping Chen 0006, Jiaze Sun
Appl. Intell.2
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
SOSP1