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http://dx.doi.org/10.5392/JKCA.2022.22.06.056

GPU Based Incremental Connected Component Processing in Dynamic Graphs  

Kim, Nam-Young (충북대학교 빅데이터협동과정)
Choi, Do-Jin (창원대학교 컴퓨터공학과)
Bok, Kyoung-Soo (원광대학교 인공지능융합학과)
Yoo, Jae-Soo (충북대학교 정보통신공학부)
Publication Information
The Journal of the Korea Contents Association / v.22, no.6, 2022 , pp. 56-68 More about this Journal
Abstract
Recently, as the demand for real-time processing increases, studies on a dynamic graph that changes over time has been actively done. There is a connected components processing algorithm as one of the algorithms for analyzing dynamic graphs. GPUs are suitable for large-scale graph calculations due to their high memory bandwidth and computational performance. However, when computing the connected components of a dynamic graph using the GPU, frequent data exchange occurs between the CPU and the GPU during real graph processing due to the limited memory of the GPU. The proposed scheme utilizes the Weighted-Quick-Union algorithm to process large-scale graphs on the GPU. It supports fast connected components computation by applying the size to the connected component label. It computes the connected component by determining the parts to be recalculated and minimizing the data to be transmitted to the GPU. In addition, we propose a processing structure in which the GPU and the CPU execute asynchronously to reduce the data transfer time between GPU and CPU. We show the excellence of the proposed scheme through performance evaluation using real dataset.
Keywords
Dynamic Graph; GPU; Connected Component; Graph Analysis; Limited Memory;
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