Multi-GPU Programming Model for Subgraph Matching in Large Graphs

Subgraph matching is an important method of data mining in complex networks. In recent years, the subgraph matching algorithm based on GPU (graphics processing units) has shown obvious speed advantages.However, due to the large scale of graph data and a large number of intermediate results of subgra...

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Vydáno v:Jisuanji kexue yu tansuo Ročník 17; číslo 7; s. 1576 - 1585
Hlavní autor: LI Cenhao, CUI Pengjie, YUAN Ye, WANG Guoren
Médium: Journal Article
Jazyk:čínština
Vydáno: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 01.07.2023
Témata:
graph analysis; multi-gpu; subgraph matching in large graphs; priority scheduling; concurrent programming model
ISSN:1673-9418
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Abstract Subgraph matching is an important method of data mining in complex networks. In recent years, the subgraph matching algorithm based on GPU (graphics processing units) has shown obvious speed advantages.However, due to the large scale of graph data and a large number of intermediate results of subgraph matching, the memory capacity of a single GPU soon becomes the main bottleneck for processing subgraph matching algorithm of large graph. Therefore, this paper proposes a multi-GPU programming model for large graph subgraph matching. Firstly, the framework of subgraph matching algorithm based on multi-GPU is proposed, and the cooperative operation of subgraph matching algorithm on multi-GPU is realized, which solves the problem of graph scale of subgraph matching on GPU. Secondly, a dynamic adjustment technique based on query graph is used to deal with cross-partition subgraph sets, which solves the cross-partition subgraph matching problem caused by graph segmentation. Finally, based on the characteristics of S
AbstractList Subgraph matching is an important method of data mining in complex networks. In recent years, the subgraph matching algorithm based on GPU (graphics processing units) has shown obvious speed advantages.However, due to the large scale of graph data and a large number of intermediate results of subgraph matching, the memory capacity of a single GPU soon becomes the main bottleneck for processing subgraph matching algorithm of large graph. Therefore, this paper proposes a multi-GPU programming model for large graph subgraph matching. Firstly, the framework of subgraph matching algorithm based on multi-GPU is proposed, and the cooperative operation of subgraph matching algorithm on multi-GPU is realized, which solves the problem of graph scale of subgraph matching on GPU. Secondly, a dynamic adjustment technique based on query graph is used to deal with cross-partition subgraph sets, which solves the cross-partition subgraph matching problem caused by graph segmentation. Finally, based on the characteristics of S
Author LI Cenhao, CUI Pengjie, YUAN Ye, WANG Guoren
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  organization: 1. School of Computer Science and Engineering, Northeastern University, Shenyang 110000, China 2. School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
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Snippet Subgraph matching is an important method of data mining in complex networks. In recent years, the subgraph matching algorithm based on GPU (graphics processing...
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SubjectTerms graph analysis; multi-gpu; subgraph matching in large graphs; priority scheduling; concurrent programming model
Title Multi-GPU Programming Model for Subgraph Matching in Large Graphs
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