Yanpeng Yu

Yanpeng Yu

PhD student @ Yale University

Department of Computer Science

Yale University

Biography

Download my resumé.

I am a fifth-year Ph.D. student at the Department of Computer Science, Yale University, advised by Professor Anurag Khandelwal and Professor Lin Zhong. My research focuses on designing efficient cache-coherence and synchronization protocols for large-scale shared memory systems such as disaggregated memory or CPU-GPU shared memory.

My research received a Distinguished Artifact Award at ISCA 2025, and was selected for IEEE Micro’s Top Picks in Computer Architecture in 2025.

I’ve had the exciting opportunity to spend two summers as a research intern in the Architecture Research Group at NVIDIA Corporation, where I worked on systems and architectures for Large Language Models (LLM).

Prior to my Ph.D. study, I was an undergraduate student at Peking University.

Interests
  • Memory Disaggregation
  • Cache Coherence Protocols
  • Synchronization Protocols
  • Architecture/System for ML
Education
  • Ph.D. in Computer Science, 2021-Present

    Yale University

  • M.Sc. in Computer Science, 2021-2024

    Yale University

  • B.Sc. in Computer Science and Technology, 2017-2021

    Peking University

Recent Publications

(2026). Efficient and Scalable Synchronization via Generalized Cache Coherence. OSDI'26.

(2025). Efficient MoE Serving in the Memory-Bound Regime: Balance Activated Experts, Not Tokens. In Submission.

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(2025). CORD: Low-Latency, Bandwidth-Efficient and Scalable Release Consistency via Directory Ordering. ISCA'25 Distinguished Artifact Award. Selected for IEEE Micro’s Top Picks in Computer Architecture in 2025.

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(2023). An Efficient Data Structure for Dynamic Graph on GPUs. TKDE'23.

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(2021). MIND: In-Network Memory Management for Disaggregated Data Centers. SOSP'21.

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