TSH: Easy-to-be distributed partitioning for large-scale graphs-Reference-Cited by-同舟云学术

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TSH: Easy-to-be distributed partitioning for large-scale graphs

Published:2019-12 Issue: Volume:101 Page:804-818
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Wang Ning,Wang Zhigang,Gu Yu,Bao Yubin,Yu Ge

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference49 articles.

1. Pegasus: a peta-scale graph mining system implementation and observations;Kang,2009

2. Pregel: a system for large-scale graph processing;Malewicz,2010

3. Hama: an efficient matrix computation with the mapreduce framework;Seo,2010

4. Apache Giraph. http://giraph.apache.org/.

5. Gps: a graph processing system;Salihoglu,2013

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. HashGrid: An optimized architecture for accelerating graph computing on FPGAs;Future Generation Computer Systems;2025-01

2. Lightweight Streaming Graph Partitioning by Fully Utilizing Knowledge from Local View;2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS);2023-07

3. Towards PageRank Update in a Streaming Graph by Incremental Random Walk;IEEE Access;2022

4. DMGA: A Distributed Shortest Path Algorithm for Multistage Graph;Scientific Programming;2021-05-31

5. SDP: Scalable Real-time Dynamic Graph Partitioner;IEEE Transactions on Services Computing;2021

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