Liang Geng
Liang Geng

Ph.D. Student

The Ohio State University

About Me

Hi, I’m Liang Geng (耿亮), a third-year Ph.D. student in the Computer Science Department, OSU. I’m interested in computer systems, especially GPU and RDMA programming. My current research is repurposing NVIDIA RT Cores to accelerate non-graphics workloads, such as geospatial data processing. My advisors are Prof. Xiaodong Zhang and Dr. Rubao Lee. Before joining the OSU, I was a senior engineer at Alibaba DAMO Academy supervised by Dr. Wenyuan Yu, where I developed GPU support for libgrape-lite and was the initial contributor to GrapeScope and Vineyard. I was fortunately advised by Prof. Yanfeng Zhang and Dr. Hao Wang while pursuing my Master’s Degree. They helped me to start my research journey.

Interests
  • Geospatial Data Processing
  • Parallel Computing
  • Distributed Systems
Education

  • Ph.D., Computer Science, 2022 - Current

    The Ohio State University, USA

  • M.Eng., Computer Science, 2016 - 2019

    Northeastern University, China

  • B.Eng., Software Engineering, 2012 - 2016

    Liaoning Technical University, China

Recent Publications
Liang Geng, Rubao Lee, Xiaodong Zhang (2024). RayJoin: Fast and Accurate Spatial Join with Ray Tracing. In ICS.
PDF Code Slides
Liang Geng, Hao Wang, Jingsong Meng, Dayi Fan, Sami Ben-Romdhane, Hari Kadayam Pichumani, Vinay Phegade, Xiaodong Zhang (2024). RR-Compound: RDMA-fused gRPC for Low Latency and High Throughput with an Easy Interface. In TPDS.
Code
Shufeng Gong, Chao Tian, Qiang Yin, Zhengdong Wang, Song Yu, Yanfeng Zhang, Wenyuan Yu, Liang Geng, Chong Fu, Ge Yu, Jingren Zhou (2024). Ingress: an automated incremental graph processing system. In VLDB Journal.
Ke Meng, Liang Geng, Xue Li, Qian Tao, Wenyuan Yu, Jingren Zhou (2023). Efficient Multi-GPU Graph Processing with Remote Work Stealing. In ICDE.
Code
Wenfei Fan, Liang Geng, Ruochun Jin, Ping Lu, Resul Tugay, Wenyuan Yu (2022). Linking Entities across Relations and Graphs. In ICDE.
Code
Mengbai Xiao, Hao Wang, Liang Geng, Rubao Lee, Xiaodong Zhang (2022). An RDMA-enabled In-memory Computing Platform for R-tree on Clusters. In TSAS.
PDF
Shufeng Gong, Chao Tian, Qiang Yin, Wenyuan Yu, Yanfeng Zhang, Liang Geng, Song Yu, Ge Yu, Jingren Zhou (2021). Automating Incremental Graph Processing with Flexible Memoization. In VLDB.
PDF
Qiange Wang, Yanfeng Zhang, Hao Wang, Liang Geng, Rubao Lee, Xiaodong Zhang, Ge Yu (2020). Automating Incremental and Asynchronous Evaluation for Recursive Aggregate Data Processing. In SIGMOD.
PDF
Mengbai Xiao, Hao Wang, Liang Geng, Rubao Lee, Xiaodong Zhang (2019). Catfish: Adaptive RDMA-enabled R-Tree for Low Latency and High Throughput. In ICDCS.
PDF
Simon Zhang, Mengbai Xiao, Chengxin Guo, Liang Geng, Hao Wang, Xiaodong Zhang (2019). HYPHA: a framework based on separation of parallelisms to accelerate persistent homology matrix reduction. In ICS.
PDF
Hao Wang, Liang Geng, Rubao Lee, Kaixi Hou, Yanfeng Zhang, Xiaodong Zhang (2019). SEP-graph: finding shortest execution paths for graph processing under a hybrid framework on GPU. In PPoPP.
PDF Code Slides