On the Complexity of List Ranking in the Parallel External Memory Model

  • Riko Jacob
  • Tobias Lieber
  • Nodari Sitchinava
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8635)


We study the problem of list ranking in the parallel external memory (PEM) model. We observe an interesting dual nature for the hardness of the problem due to limited information exchange among the processors about the structure of the list, on the one hand, and its close relationship to the problem of permuting data, which is known to be hard for the external memory models, on the other hand.

By carefully defining the power of the computational model, we prove a permuting lower bound in the PEM model. Furthermore, we present a stronger Ω(log2 N) lower bound for a special variant of the problem and for a specific range of the model parameters, which takes us a step closer toward proving a non-trivial lower bound for the list ranking problem in the bulk-synchronous parallel (BSP) and MapReduce models. Finally, we also present an algorithm that is tight for a larger range of parameters of the model than in prior work.


Shared Memory List Ranking Communication Round MapReduce Model Chance Encounter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Riko Jacob
    • 1
  • Tobias Lieber
    • 1
  • Nodari Sitchinava
    • 2
  1. 1.Institute for Theoretical Computer ScienceETH ZürichSwitzerland
  2. 2.Department of Information and Computer SciencesUniversity of HawaiiUSA

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