Scalable matrix computations on large scale-free graphs using 2D graph partitioning

@article{Boman2013ScalableMC,
  title={Scalable matrix computations on large scale-free graphs using 2D graph partitioning},
  author={Erik G. Boman and Karen D. Devine and Sivasankaran Rajamanickam},
  journal={2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC)},
  year={2013},
  pages={1-12}
}
Scalable parallel computing is essential for processing large scale-free (power-law) graphs. The distribution of data across processes becomes important on distributed-memory computers with thousands of cores. It has been shown that two-dimensional layouts (edge partitioning) can have significant advantages over traditional one-dimensional layouts. However, simple 2D block distribution does not use the structure of the graph, and more advanced 2D partitioning methods are too expensive for large… CONTINUE READING
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