SpeedCore: Space-efficient and Dependency-aware GPU Parallel Framework for Core Decomposition-Reference-Cited by-同舟云学术

SpeedCore: Space-efficient and Dependency-aware GPU Parallel Framework for Core Decomposition

Published:2024-08-12 Issue: Volume:7 Page:555-564
ISSN:
Container-title:Proceedings of the 53rd International Conference on Parallel Processing
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Author:

Zhao Chen¹^ORCID,Yu Ting²^ORCID,Zheng Zhigao¹^ORCID,Zhu Yuanyuan³^ORCID,Jin Song³^ORCID,Du Bo³^ORCID,Tao Dacheng⁴^ORCID

Affiliation:

1. School of Computer Science, Wuhan University, China

2. Zhejianglab, China

3. Wuhan University, China

4. The University of Sydney, Australia

Funder

Knowledge Innovation Program of Wuhan - Basic Research

Natural Science Foundation of Zhejiang Province

Fundamental Research Funds for the Central Universities

CCF-Huawei Populus euphratica Fund

National Key Research and Development Program of China

National Natural Science Foundation of China

Key Research and Development Program of Hubei Province

Project funded by China Postdoctoral Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3673038.3673111

Reference37 articles.

1. Akhlaque Ahmad Lyuheng Yuan Da Yan Guimu Guo Jieyang Chen and Chengcui Zhang. 2023. Accelerating k-Core Decomposition by a GPU. In ICDE. 1818–1831.

2. Neighborhood-Based Hypergraph Core Decomposition

3. Vladimir Batagelj and Matjaz Zaversnik. 2003. An O(m) Algorithm for Cores Decomposition of Networks. arXivcs/0310049 (2003).

4. James Cheng Yiping Ke Shumo Chu and M. Tamer Özsu. 2011. Efficient core decomposition in massive networks. In ICDE. 51–62.

5. Deming Chu, Fan Zhang, Wenjie Zhang, Xuemin Lin, Ying Zhang, Yinglong Xia, and Chenyi Zhang. 2024. Discovering and Maintaining the Best k in Core Decomposition. TKDE (2024), 1–18.