SJTU-IPADS / Wukong
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Wukong for Linked Data
Wukong is a fast and distributed graph-structured store that leverages efficient graph exploration to proivde highly concurrent and low-latency query processing over big linked data.
Feature Highlights
- High-performance and scalable in-memory graph store
- Fast and concurrent SPARQL query processing by graph exloration
- Fast communication by leveraging RDMA feature of InfiniBand network
- A GPU extension of query engine for heterogenous (CPU/GPU) cluster
- A type-centric SPARQL query plan optimizer
For more details see Wukong Project, including new features, roadmap, instructions, etc.
Getting Started
License
Wukong is released under the Apache 2.0 license.
If you use Wukong in your research, please cite our paper:
@inproceedings{osdi2016wukong,
author = {Shi, Jiaxin and Yao, Youyang and Chen, Rong and Chen, Haibo and Li, Feifei},
title = {Fast and Concurrent RDF Queries with RDMA-based Distributed Graph Exploration},
booktitle = {12th USENIX Symposium on Operating Systems Design and Implementation},
series = {OSDI '16},
year = {2016},
month = Nov,
isbn = {978-1-931971-33-1},
address = {GA},
pages = {317--332},
url = {https://www.usenix.org/conference/osdi16/technical-sessions/presentation/shi},
publisher = {USENIX Association},
}
Academic and Reference Papers
[OSDI] Fast and Concurrent RDF Queries with RDMA-based Distributed Graph Exploration. Jiaxin Shi, Youyang Yao, Rong Chen, Haibo Chen, and Feifei Li. Proceedings of 12th USENIX Symposium on Operating Systems Design and Implementation, Savannah, GA, US, Nov, 2016.
[SOSP] Sub-millisecond Stateful Stream Querying over Fast-evolving Linked Data. Yunhao Zhang, Rong Chen, and Haibo Chen. Proceedings of the 26th ACM Symposium on Operating Systems Principles, Shanghai, China, October, 2017.
[USENIX ATC] Fast and Concurrent RDF Queries using RDMA-assisted GPU Graph Exploration. Siyuan Wang, Chang Lou, Rong Chen, and Haibo Chen. Proceedings of 2018 USENIX Annual Technical Conference, Boston, MA, US, July 2018.
[USENIX ATC] Pragh: Locality-preserving Graph Traversal with Split Live Migration. Xiating Xie, Xingda Wei, Rong Chen, and Haibo Chen. Proceedings of 2019 USENIX Annual Technical Conference, Renton, WA, US, July 2019.