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Dedong Xie

dblp:328/0339 · DBLP profile ↗
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3ranked-venue papers
2as first author
3since 2021 · last 2026
0009-0005-7324-6110ORCID · corroborated

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

Systems, architecture and hardware · 2 · 2 first-author · 2 since 2021Software engineering, systems software and programming languages · 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 · 40% Energy-efficient computing · 37% Storage systems · 23%

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

TopicWeightPapersLastEvidence papers
Energy-efficient computing
power management
1.012026
PASS: A Power Adaptive Storage Server · EuroSys 2026
Storage systems › networked storage
storage server
1.012026
PASS: A Power Adaptive Storage Server · EuroSys 2026
Cloud and datacenter computing
inference serving
0.912025
NanoFlow: Towards Optimal Large Language Model Serving Throughput · OSDI 2025
Cloud and datacenter computing › inference serving
LLM serving
0.912025
NanoFlow: Towards Optimal Large Language Model Serving Throughput · OSDI 2025
Energy-efficient computing
datacenter power management
0.312026
PASS: A Power Adaptive Storage Server · EuroSys 2026
Energy-efficient computing › power management
power capping
0.312026
PASS: A Power Adaptive Storage Server · EuroSys 2026

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

workload-proportional scaling · 1.0power-adaptive resource management · 1.0
YearPublicationVenuePosition
2026 PASS: A Power Adaptive Storage Server
abstract
Power management has become important in data centers. Since data center workloads are often dynamic, it is common practice to conserve energy by scaling resources up or down to match the workload. And since data centers often oversubscribe the power delivery infrastructure, operators can add power capping on top of these workload-proportional systems to adjust to available power. We find that this combination leaves performance on the table and provides only a limited power control range. Instead, we argue for power-adaptive systems that attempt to make the best use of the available power budget. To illustrate this approach, we built PASS, a power-adaptive storage system. PASS considers the interactions between different system components, including software and hardware, when making its power management decisions. For example, when under the same power constraint, PASS achieves 3–25× better throughput on filebench workloads than Intel's SPDK storage stack with Google Thunderbolt, a state of the art power capping system.
Dedong Xie, Theano Stavrinos, Jonggyu Park, Simon Peter 0001, Baris Kasikci, Thomas E. Anderson
EuroSys1
2025 NanoFlow: Towards Optimal Large Language Model Serving Throughput
Kan Zhu, Yilong Zhao 0002, Liangyu Zhao, Gefei Zuo, Yile Gu, Dedong Xie, Zihao Ye 0001, Keisuke Kamahori, Chien-Yu Lin, Ziren Wang, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci
OSDI7
2024 Can Storage Devices be Power Adaptive?
abstract
Power is becoming a scarce resource for data centers, raising the need for power adaptive system design---the ability to dynamically change power consumption---to match available power. Storage makes up an increasing fraction of total data center power consumption. As such, it holds great potential to contribute to data center power adaptivity.
Dedong Xie, Theano Stavrinos, Kan Zhu, Simon Peter 0001, Baris Kasikci, Thomas E. Anderson
HotStorage1