MMap: Fast billion-scale graph computation on a PC via memory mapping

@article{Lin2014MMapFB,
  title={MMap: Fast billion-scale graph computation on a PC via memory mapping},
  author={Zhiyuan Lin and Minsuk Kahng and Kaeser Md. Sabrin and Duen Horng Chau and Ho Lee and U. Kang},
  journal={2014 IEEE International Conference on Big Data (Big Data)},
  year={2014},
  pages={159-164}
}
Graph computation approaches such as GraphChi and TurboGraph recently demonstrated that a single PC can perform efficient computation on billion-node graphs. To achieve high speed and scalability, they often need sophisticated data structures and memory management strategies. We propose a minimalist approach that forgoes such requirements, by leveraging the fundamental memory mapping (MMap) capability found on operating systems. We contribute: (1) a new insight that MMap is a viable technique… CONTINUE READING
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A fast parallel graph engine handling billion - scale graphs in a single pc

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