Accord: Accelerating Big Data Applications on Heterogeneous Processors
Many applications require fast access, processing, and analytics of their
big data, for example, millions of image files, tables containing hundreds of millions of rows,
and billion-edge graphs.
With the rapid advances of hardware technologies, these applications run on
powerful servers with heterogeneous processors, computer clusters, and cloud
computing platforms. However, the data handling and processing is often
not in accordance with the underlying hardware resources. Therefore, we
proposed to develop software techniques that
accelerate these applications by utilizing their hardware
resources effectively. In particular, we work on data-parallel primitives as well as
parallel algorithms on graph analytics and relational queries.
The processors we consider include
multicore CPUs, Intel Knights Landing (KNL) processors, and GPUs.
Publications
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Guanghua Li, Hao Zhang, and Qiong Luo. Vora: A Vector-Based Engine for Scalable GPU-Accelerated Subgraph Query Processing.In IEEE International Conference on Data Engineering (ICDE), 2027.
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Guanghua Li, Xibo Sun, Qiong Luo, and Lijun Chang. Efficient GPU-Based Continuous Subgraph Matching on Batch Updates. APWeb 2026.
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Yicheng Hu, Xibo Sun, Qiong Luo: Finding Maximum Common Subgraphs Efficiently Through Dynamic Bidirectional Vertex Selection. APWeb-WAIM (3) 2025: 34-50
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Guanghua Li, Hao Zhang, Xibo Sun, Qiong Luo, and Yuanyuan Zhu. TenGraph: A Tensor-Based Graph Query Engine.Proceedings of the VLDB Endowment, 2024
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Xibo Sun, Qiong Luo:Efficient GPU-Accelerated Subgraph Matching. Proc. ACM Manag. Data 1(2): 181:1-181:26 (2023)
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Xibo Sun, Shixuan Sun, Qiong Luo, Bingsheng He: An In-Depth Study of Continuous Subgraph Matching. Proc. VLDB Endow. 15(7): 1403-1416 (2022)
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Shixuan Sun, Qiong Luo:Subgraph Matching With Effective Matching Order and Indexing. IEEE Trans. Knowl. Data Eng. 34(1): 491-505 (2022)
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Lipeng Wang, Qiong Luo, Shengen Yan:DIESEL+: Accelerating Distributed Deep Learning Tasks on Image Datasets. IEEE Trans. Parallel Distributed Syst. 33(5): 1173-1184 (2022)
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Zhuohang Lai, Xibo Sun, Qiong Luo, Xiaolong Xie:Accelerating multi-way joins on the GPU. VLDB J. 31(3): 529-553 (2022)
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Zonghao Feng, Qipeng Xie, Qiong Luo, Yujie Chen, Haoxuan Li, Huizhong Li, Qiang Yan:
Accelerating Elliptic Curve Digital Signature Algorithms on GPUs. SC 2022: 27:1-27:13
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Yulin Che, Zhuohang Lai, Shixuan Sun, Yue Wang, Qiong Luo:
Accelerating Truss Decomposition on Heterogeneous Processors. Proc. VLDB Endow. 13(10): 1751-1764 (2020)
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Lipeng Wang, Songgao Ye, Baichen Yang, Youyou Lu, Hequan Zhang, Shengen Yan, Qiong Luo:
DIESEL: A Dataset-Based Distributed Storage and Caching System for Large-Scale Deep Learning Training. ICPP 2020: 20:1-20:11
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Shixuan Sun, Qiong Luo:
In-Memory Subgraph Matching: An In-depth Study. SIGMOD Conference 2020: 1083-1098
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Shixuan Sun, Yulin Che, Lipeng Wang, Qiong Luo:
Efficient Parallel Subgraph Enumeration on a Single Machine. ICDE 2019: 232-243
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Shixuan Sun, Qiong Luo:
Scaling Up Subgraph Query Processing with Efficient Subgraph Matching. ICDE 2019: 220-231
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Yulin Che, Zhuohang Lai, Shixuan Sun, Qiong Luo, Yue Wang:
Accelerating All-Edge Common Neighbor Counting on Three Processors. ICPP 2019: 42:1-42:10
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Zhuohang Lai, Qiong Luo, Xiaolong Xie:
Efficient Data-Parallel Primitives on Heterogeneous Systems. ICPP 2019: 74:1-74:10
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Shixuan Sun, Qiong Luo:
Parallelizing Recursive Backtracking Based Subgraph Matching on a Single Machine. ICPADS 2018: 42-50
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Zhuohang Lai, Qiong Luo, Xiaoying Jia:
Revisiting Multi-pass Scatter and Gather on GPUs. ICPP 2018: 25:1-25:11
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Yulin Che, Shixuan Sun, Qiong Luo:
Parallelizing Pruning-based Graph Structural Clustering. ICPP 2018: 77:1-77:10
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Lipeng Wang, Xiaoying Jia, Qiong Luo:
Betweenness Centrality Revisited on Four Processors. ICPADS 2017: 614-623
Source Code Repository
Rapids at HKUST on GitHub
Acknowledgement
We thank our industrial sponsors Alibaba, Huawei and SenseTime for their generous support. Part of the work was supported by Grant 16209821 (RapidCM: Fast In-Memory Continuous Subgraph Matching, Jan 2022 - Jun 2025) from the Hong Kong Research Grants Council.