Time

10:00 AM -- 12:00 AM, Thursday, 3rd Nov.

 

Location

ZOOM online

 

Abstract

As an efficient and effective way for us to understand and manage connected data, graph is widely used in real-world applications such as social network, online payment, internet, and biology network. The volume, sparsity and irregularity of graph data has posed fundamental technical challenges for graph data management. Encouraged by the success and the rise of shared-memory architectures, I research the design, implementation and performance optimizations for high performance graph database systems on shared-memory architectures to empower large-scale graph query and analysis operations. Specifically, my current research focuses on the subgraph query problem, which is the fundamental operation to access the graph data. In this talk, I will introduce a full-stack design for subgraph query processing, from benchmark framework, algorithm and pipeline design to hardware utilization.

 

Lecturer

Dr. Shixuan Sun is currently a Senior Research Fellow at the School of Computing, National University of Singapore (NUS). His research interests are in big data systems, graph algorithms, and parallel computing. Current focus is on developing high-performance graph processing systems to empower large-scale graph query and analysis operations. He frequently publishes research papers on prestigious database venues including SIGMOD, VLDB, ICDE and TKDE.

He received his Ph.D. from the Hong Kong University of Science and Technology (HKUST) in 2020. Prior to that, he got his M.S. and B.S. from Tongji University in 2014 and 2011, respectively. He worked as a Software Development Engineer at Microsoft (Shanghai) from 2014 to 2015.