A feasible graph partition framework for parallel computing of big graph-Reference-Cited by-同舟云学术

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A feasible graph partition framework for parallel computing of big graph

Published:2017-10 Issue: Volume:134 Page:228-239
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Liu X.,Zhou Y.,Guan X.,Shen C.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference54 articles.

1. Graphx: a resilient distributed graph system on spark;Xin,2013

2. Powergraph: distributed graph-parallel computation on natural graphs.;Gonzalez,2012

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

4. Graph partition by swendsen-wang cuts;Barbu,2003

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

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3. The major challenges of big graph and their solutions: A review;Advances in Computers;2023

4. GON: End-to-end optimization framework for constraint graph optimization problems;Knowledge-Based Systems;2022-10

5. Graph partitioning strategies: one size does not fit all;The Journal of Supercomputing;2022-06-20

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