Exploiting reuse for GPU subgraph enumeration (extended abstract)
Publication Type
Conference Proceeding Article
Publication Date
4-2023
Abstract
Subgraph enumeration is important for many applications such as network motif discovery, community detection, and frequent subgraph mining. To accelerate the execution, recent works utilize graphics processing units (GPUs) to parallelize subgraph enumeration. The performances of these parallel schemes are dominated by the set intersection operations which account for up to 95% of the total processing time. (Un)surprisingly, a significant portion (as high as 99%) of these operations is actually redundant, i.e., the same set of vertices is repeatedly encountered and evaluated. Therefore, in this paper, we seek to salvage and recycle the results of such operations to avoid repeated computation. Our solution consists of two phases. In the first phase, we generate a reusable plan that determines the opportunity for reuse. The plan is based on a novel reuse discovery mechanism that can identify available results to prevent redundant computation. In the second phase, the plan is executed to produce the subgraph enumeration results. This processing is based on a newly designed reusable parallel search strategy that can efficiently maintain and retrieve the results of set intersection operations. Our implementation on GPUs shows that our approach can achieve up to 5 times speedups compared with the state-of-the-art GPU solutions.
Keywords
Graphics processing units, Search problems, Data engineering, Recycling
Discipline
Databases and Information Systems | Graphics and Human Computer Interfaces
Research Areas
Data Science and Engineering
Publication
Proceedings of the 2023 IEEE 39th International Conference on Data Engineering (ICDE), Anaheim, California, April 3-7
ISBN
9798350322286
Identifier
10.1109/ICDE55515.2023.00309
Publisher
IEEE
City or Country
Anaheim, CA, USA
Citation
GUO, Wentiao; LI, Yuchen; and TAN, Kian-Lee.
Exploiting reuse for GPU subgraph enumeration (extended abstract). (2023). Proceedings of the 2023 IEEE 39th International Conference on Data Engineering (ICDE), Anaheim, California, April 3-7.
Available at: https://ink.library.smu.edu.sg/sis_research/8500
Copyright Owner and License
Authors
Additional URL
https://doi.org/10.1109/ICDE55515.2023.00309