Peng Cheng
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Peng Cheng |
I'm currently a senior principal research manager at Microsoft Research Asia (MSRA). I received my Ph.D. in Computer Science and Technology from Tsinghua University in 2015 and B.S. degrees in Software Engineering from Beihang University in 2010. I was as a visiting student in UCLA from September 2013 to September 2014. In 2015, I joined MSRA.
Please feel free to send me an email if you are interested in a full-time research position, internship, or visiting researcher role in MSRA Vancouver lab.
My research interests are in the broad areas of systems and networking, cloud and AI infrastructure, and AI. My recent work is mainly focusing on:
Artificial Specialized Intelligence
AI for Systems and Networking
AI for Cloud and AI Infrastructure
News
2024/07. NeoMem got accepted at MICRO 2024.
2024/07. SuperBench received the Best Paper Award at ATC 2024!
2024/07. Live Migration for Storage-Optimized VMs got accepted at APSys 2024.
2024/05. SuperBench got accepted at ATC 2024.
2023/10. FP8-LM has been released on Arxiv.
2023/07. SPFresh got accepted at SOSP 2023.
2023/04. Query Processing on Gaming Consoles got accepted at DAMON 2023.
2023/02. Tutel got accepted at MLSys 2023.
2022/12. ARK got accepted at NSDI 2023.
2022/11. ElasticFlow got accepted at ASPLOS 2023.
2022/10. PipeDevice got accepted at CoNEXT 2022.
2022/09. SeCBAD got accepted at NeurIPS 2022.
2022/07. OpenNetLab received the Best Paper Award at APNet 2022!
2022/06. Towards GPU-driven Code Execution for Distributed Deep Learning received the Best Paper Award at MLArchSys 2022!
2022/05. RuleCache got accepted at ICWS 2022.
2022/04. PilotFish got accepted at ATC 2022.
2022/04. OpenNetLab and ALT got accepted at APNet 2022.
2022/04. Moneo got accepted at ICC 2022 and OSR 2022.
Selected Papers (Full List)
MICRO’24 NeoMem: Hardware/Software Co-Design for CXL-Native Memory Tiering
ATC’24 SuperBench: Improving Cloud AI Infrastructure Reliability with Proactive Validation
SOSP’23 SPFresh: Incremental In-Place Update for Billion-Scale Vector Search
MLSys’23 Tutel: Adaptive Mixture-of-Experts at Scale
NSDI’23 ARK: GPU-driven Code Execution for Distributed Deep Learning
ASPLOS’23 ElasticFlow: An Elastic Serverless Training Platform for Distributed Deep Learning
CoNEXT’22 PipeDevice: A Hardware-Software Co-Design Approach to Intra-Host Container Communication
NeurIPS’22 An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context
ICWS’22 RuleCache: Accelerating Web Application Firewalls by On-line Learning Traffic Patterns
ATC’22 PilotFish: Harvesting Free Cycles of Cloud Gaming with Deep Learning Training
INFOCOM’21 NFD: Using Behavior Models to Develop Cross-Platform Network Functions
ATC’20 NetKernel: Making Network Stack Part of the Virtualized Infrastructure
NSDI’19 Direct Universal Access: Making Data Center Resources Available to FPGA
ICNP’18 Micro-Burst in Data Centers: Observations, Analysis, and Mitigations
NSDI’18 Multi-Path Transport for RDMA in Datacenters
CoNEXT’17 Tagger: Practical PFC Deadlock Prevention in Data Center Networks
SIGCOMM’16 ClickNP: Highly flexible and High-performance Network Processing with Reconfigurable Hardware
ATC’16 Fast and Cautious: Leveraging Multi-path Diversity for Transport Loss Recovery in Data Centers
EuroSys’16 TFC: Token Flow Control in Data Center Networks
NSDI’14 Catch the Whole Lot in an Action: Rapid Precise Packet Loss Notification in Data Center
Services
Program Committee: NSDI 2025, CoNEXT 2023