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Round Compression for Parallel Matching Algorithms
[article]
2018
arXiv
pre-print
For over a decade now we have been witnessing the success of massive parallel computation (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or Spark. One of the reasons for their success is the fact that these frameworks are able to accurately capture the nature of large-scale computation. In particular, compared to the classic distributed algorithms or PRAM models, these frameworks allow for much more local computation. The fundamental question that arises in this context is though: can we
arXiv:1707.03478v2
fatcat:tsoixglzmjbdxdh47vu7okqsnm