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曾立
Li Zeng, senior algorithm researcher and programmer in computer science and technology.
Email: bookug AT qq DOT com
GitHub,
Google Scholar
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Biography
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I obtained my B.S. degree from PKU in 2016, and studied as a master for two years.
Development and optimization of graph database system gStore is my main work in this period.
Later, I finished Ph.D. in 3 years by researching the optimization of graph algorithms on heterogeneous CPU-GPU platforms.
My current research interests include graph algorithms, database optimization, high-performance computing and LLM acceleration.
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Publications
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Li Zeng, et al. KBQA: Accelerate Fuzzy Path Query on Knowledge Graph.
DEXA, 2023.
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Yu Gao, Meng Qin, Yibin Ding, Li Zeng, et al. RaftGP: Random Fast Graph Partitioning.
IEEE High Performance Extreme Computing, 2023.
(GraphChallenge Innovation Award)
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Li Zeng, Lei Zou, M. Tamer Özsu. SGSI: A scalable GPU-friendly Subgraph Isomorphism Algorithm.
IEEE Transactions on Knowledge and Data Engineering, 2022.
(CCF A journal)
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Li Zeng, et al. HTC: Hybrid vertex-parallel and edge-parallel Triangle Counting.
IEEE High Performance Extreme Computing, 2022.
(GraphChallenge Innovation Award)
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Li Zeng, et al. SQLG+: Efficient k-hop Query Processing on RDBMS.
International Conference on Database Systems for Advanced Applications, 2022.
(CCF B conference)
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Li Zeng, Yan Jiang, Weixin Lu, Lei Zou. Deep Analysis on Subgraph Isomorphism.
arXiv, 2021. [pdf]
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Li Zeng, Lei Zou, M. Tamer Özsu, et al. GSI: GPU-friendly Subgraph Isomorphism.
IEEE International Conference on Data Engineering, 2020. [pdf]
(CCF A conference)
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Fan Zhang, Lei Zou, Li Zeng, Xiangyang Gou. Dolha - an efficient and exact data structure for streaming graphs. The journal of World Wide Web, 2020.
(CCF B journal)
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Li Zeng, Lei Zou. Redesign of the gStore system.
Frontier of Computer Science, 2018. [pdf] (CCF C journal)
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Yu Zhang, Li Zeng, Lei Zou. Regular Path Queries on Large Graph Data.
Natural Language Processing and Chinese Computing, 2018. (CCF C conference)
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张雨，曾立，邹磊。大规模图数据的正则路径查询。北京大学学报自然科学版，2018。
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Projects
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Improvement of Graph Machine Learning System
- Distributed data loading of hybrid features: Redesign the architecture of data loading module to support hybrid features on node/edge, optimize the parsing of feature string and yield >2× speedup.
- Distributed real-time sampling in data loading: Create memory clip module. During data loading, if memory is not enough, a clipping will be performed on graph store. The sampling function used in clipping is defined by users.
Contribution: reduce the memory consumption greatly (31%) with little decrease in model effect (1%).
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Acceleration of Large Scale Graph Algorithms
- Survey and optimization of subgraph isomorphism on CPU: survey the best solutions of subgraph isomorphism on CPU and propose four general techniques for improvement
- Acceleration of subgraph isomorphism on GPU: novel data structure and join algorithm, >10× speedup
- Acceleration of other graph algorithms on GPU: optimize solutions of shortest path and triangle counting, both achieve >2× speedup
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Development of Graph Database System
As the primary developer of graph database gStore, cumulatively update 5,000,000 lines of code, greatly improve the performance (100×) and scale (40×).
Meanwhile, accumulate experience of leading a team (>10 people), make them qualified for every module respectively.
- Optimization of query plans: accelerate SPARQL queries, support predicate variable and property path
- Improvement of indices: continually optimize the disk-based key-value indices (specially designed for gStore)
- Others: improve user interface, create web server, standardize the development, add documents of design and usage
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Recommended GitHub Repositories
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- PaperNotes: collect papers, write notes and search quickly based on multiple tags
- LinuxProgramming: basic knowledge and some advanced topics about Linux Programming
- GraphBenchmark: a benchmark for generating all kinds of graphs and queries
- SIEP: the state-of-the-art subgraph matching algorithms on CPU
- GSI: subgraph isomorphism on GPU, also see my implementation of GunrockSM, GpSM, gutil
- gStore: graph database system
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Last modified: Apr 29, 2022
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