Jinkun Geng (耿金坤)

Senior Postdoctoral Associate@SUNY

I am a Senior Postdoctoral Associate in Stony Brook University. I got my PhD degree (2019.9-2024.1) from Department of Computer Science, Stanford University. I have broad interest in networking and systems. Currently, I am focusing on building high-performance and fault-tolerant distributed systems by leveraging the advanced techniques including synchronized clocks and trustworthy execution environment (TEE). My CV is attached here .

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Education

MSc Computer Science

2016 - 2019
I worked with Professor Dan Li on high-performance networking systems.

PhD Computer Science

2019 - 2024
I worked with Professor Balaji Prabhakar, Professor Anirudh Sivaraman and Professor Mendel Rosenblum on high-performance and fault-tolerant distributed systems, with a specific focus on synchronized clocks.

Postdoc Computer Science

2025 - Present
I am working with Professor Shuai Mu and Professor Anirudh Sivaraman on fault-tolerant distributed systems and system verification.

Research Projects

Tiga: High-Peformance Geo-Distributed Transaction Processing Protocol

PhD@Stanford
& PostDoc@SUNY
2023.10 - 2025.09
  • Consolidate consensus and concurrency control using timestamps.
  • Develop proactive timestamp ordering approach based on synchronized clocks.
  • Develop timestamp agreement mechanism to rule out timestamp inversion and preserve strict serializability.
  • Tiga is open-sourced here, and we will continue to implement new optimization and functionality to Tiga.

Nezha: Deployable and High-Performance Consensus Using Synchronized Clocks

PhD@Stanford
2021.03 - 2023.09
  • Develop a common primitive based on synchronized clocks, deadline-ordered multicast (DOM)
  • Develop a protocol based on DOM, which is called Nezha. Nezha has proved to outperform the typical consensus protocols, including Multi-Paxos, Raft, NOPaxos, Fast Paxos, EPaxos, etc.
  • Nezha is open-sourced here, and we plan to integrated Nezha with some industrial systems which require high-performance consensus.

CloudEx: Fair-Access Financial Trading System in Cloud

PhD@Stanford
2019.08 - 2023.06
  • Implement fair trading mechanism in CloudEx, and provide user-friendly APIs
  • Performance optimization for CloudEx
  • Implement fault tolerance for CloudEx

Rima: An RDMA-Accelerated Model-Parallelized Solution to Large-Scale Matrix Factorization

Master@THU
2017.12 - 2018.06
  • Re-design the architecture of distributed matrix factorization. Leverage ring-based architecture instead of PS-based architecture to eliminate the centralized bottleneck and data redundancy
  • Design one-step transformation strategy to halve the communication workload for large-scale matrix factorization
  • Design three partial randomness strategies to add more robustness to the algorithm
  • Overlap the disk I/O overheads with the communication/computation overheads
  • Conduct a comparative testbed experiment between Rima and DSGD

HiPS: Hierarchical Parameter Synchronization in Large-Scale Data Center Network

Master@THU
2017.5 - 2018.03
  • Incorporate data center network (DCN) topology with distributed machine learning (DML) to boost the performance
  • Design high-efficient synchronization algorithms on top of server-centric topologies to better embrace the benefit of RDMA
  • Implement a prototype of BCube+HiPS in Tensorflow, and conduct comparative experiments with a 2-layer BCube testbed

LOS: High Performance and Strong Compatible User-level Network Stack

Master@THU
2015.10 - 2017.05
  • Design and implement a user-level stack based on DPDK, to achieve high performance and strong compatibility
  • Implement user-level Netfilter with dynamic library
  • Port Nginx on LOS without changing the source code

Publications

  • Jinkun Geng, Shuai Mu, Anirudh Sivaraman, Balaji Prabhakar. Tiga: Accelerating Geo-Distributed Transactions with Synchronized Clocks (Preprint, Repository)
    31st Symposium on Operating Systems Principles(SOSP 2025)
  • Muhammad Haseeb, Jinkun Geng, Daniel Duclos-Cavalcanti, Xiyu Hao, Ulysses Butler, Radhika Mittal, Srinivas Narayana, Anirudh Sivaraman. Network Support For Scalable And High Performance Cloud Exchanges (PDF, Repository)
    39th ACM Special Interest Group on Data Communication Conference(SIGCOMM 2025)
  • Jinkun Geng, Anirudh Sivaraman, Balaji Prabhakar, Mendel Rosenblum. Nezha: Deployable and High-Performance Consensus Using Synchronized Clocks (Preprint, Repository)
    49th International Conference on Very Large Data Bases (VLDB 2023)
  • Ahmad Ghalayini, Jinkun Geng, Vighnesh Sachidananda, Vinay Sriram, Yilong Geng, Balaji Prabhakar, Mendel Rosenblum, Anirudh Sivaraman. CloudEx: A Fair-Access Financial Exchange in the Cloud (PDF)
    18th Workshop on Hot Topics in Operating Systems (HotOS 2021)
  • Jinkun Geng, Dan Li, Shuai Wang. Fela: Incorporating Flexible Parallelism and Elastic Tuning to Accelerate Large-Scale DML (Preprint, PPT)
    36th IEEE International Conference on Data Engineering (ICDE 2020)
  • Jinkun Geng, Dan Li, Shuai Wang. Rima: An RDMA-Accelerated Model-Parallelized Solution to Large-Scale Matrix Factorization (PDF, PPT, Poster)
    35th IEEE International Conference on Data Engineering (ICDE 2019)
  • Shuai Wang, Dan Li, Jinkun Geng. Geryon: Accelerating Distributed CNN Training by Network-Level Flow Scheduling (Preprint)
    IEEE International Conference on Computer Communications(INFOCOM 2020)
  • Jinkun Geng, Dan Li, Yang Cheng, Shuai Wang, Junfeng Li. HiPS: Hierarchical Parameter Synchronization in Large-Scale Distributed Machine Learning (PDF, PPT)
    ACM SIGCOMM 2018 Workshop on Network Meets AI & ML (NetAI 2018)
  • Yukai Huang, Jinkun Geng, Du Lin, Bin Wang, Junfeng Li, Ruilin Ling, Dan Li. LOS: A High Performance and Compatible User-level Network Operating System (PDF, PPT)
    1st Asia-Pacific Workshop on Networking (APNet 2017)
  • Talks

  • Nezha: A High-Performance Consensus Protocol Using Accurately Synchronized Clocks
    Stanford Platform Lab Winter Review, 2022
  • CloudEx: Building a Jitter-free Financial Exchange in the Cloud
    Stanford Platform Lab Seminar, 2020
  • Fela: Incorporating Flexible Parallelism and Elastic Tuning to Accelerate Large-Scale DML
    IEEE International Conference on Data Engineering (ICDE 2020)
  • Accelerating Distributed Machine Learning by Smart Parameter Server
    3rd Asia-Pacific Workshop on Networking (APNet 2019)
  • Rima: An RDMA-Accelerated Model-Parallelized Solution to Large-Scale Matrix Factorization
    35th IEEE International Conference on Data Engineering (ICDE 2019)
  • HiPS: Hierarchical Parameter Synchronization in Large-Scale Distributed Machine Learning
    ACM SIGCOMM 2018 Workshop on Network Meets AI & ML (NetAI 2018)
  • LOS: A High Performance and Compatible User-level Network Operating System
    1st Asia-Pacific Workshop on Networking (APNet 2017)
  • Work Experiences

    Clockwork

    Palo Alto
    Senior Software Researcher
    2024.01 – 2025.05
    • Develop advanced flow scheduling and load balancing algorithms.
    • Learned a lot of non-technical stuff.

    Clockwork

    Palo Alto
    Software Engineer
    2022.06 – 2022.09
    • Refactor the codebase of Nezha and prepare for open-sourcing.
    • Test and evaluate Nezha.
    • Explore the application of clock synchronization in new areas (concurrentcy control).

    Google

    Mountain View (Virtual)
    Software Engineer
    2020.06 – 2020.09
    Mentor: Hui Su
    • Optimize video encoding performance
    • Implement Warped transformation for motion vector predictio
    • Implement DBSCAN algorithm for clustering motion vectors.

    Rewards

  • Outstanding Master Graduate in Tsinghua (3 out of 141) @THU (2019.07)
  • Outstanding Master Dissertation in Tsinghua (7 out of 141) (PDF) @THU (2019.06)
  • HPDC Student Travel Grant@HPDC Committee (2019) (2019.06)
  • ICDE Student Travel Awards@ICDE Committee (2019) (2019.03)
  • Samsung Enterprise Scholarship@Samsung Group (2014.10)