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Equivalence classes and conditional hardness in massively parallel computations
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS. University of Copenhagen, Copenhagen, Denmark.ORCID iD: 0000-0003-4468-2675
University of Padova, Padua, Italy.
2022 (English)In: Distributed computing, ISSN 0178-2770, E-ISSN 1432-0452, Vol. 35, no 2, p. 165-183Article in journal (Refereed) Published
Abstract [en]

The Massively Parallel Computation (MPC) model serves as a common abstraction of many modern large-scale data processing frameworks, and has been receiving increasingly more attention over the past few years, especially in the context of classical graph problems. So far, the only way to argue lower bounds for this model is to condition on conjectures about the hardness of some specific problems, such as graph connectivity on promise graphs that are either one cycle or two cycles, usually called the one cycle versus two cycles problem. This is unlike the traditional arguments based on conjectures about complexity classes (e.g., P≠ NP), which are often more robust in the sense that refuting them would lead to groundbreaking algorithms for a whole bunch of problems. In this paper we present connections between problems and classes of problems that allow the latter type of arguments. These connections concern the class of problems solvable in a sublogarithmic amount of rounds in the MPC model, denoted by MPC(o(log N)) , and the standard space complexity classes L and NL, and suggest conjectures that are robust in the sense that refuting them would lead to many surprisingly fast new algorithms in the MPC model. We also obtain new conditional lower bounds, and prove new reductions and equivalences between problems in the MPC model. Specifically, our main results are as follows.Lower bounds conditioned on the one cycle versus two cycles conjecture can be instead argued under the L⊈ MPC(o(log N)) conjecture: these two assumptions are equivalent, and refuting either of them would lead to o(log N) -round MPC algorithms for a large number of challenging problems, including list ranking, minimum cut, and planarity testing. In fact, we show that these problems and many others require asymptotically the same number of rounds as the seemingly much easier problem of distinguishing between a graph being one cycle or two cycles.Many lower bounds previously argued under the one cycle versus two cycles conjecture can be argued under an even more robust (thus harder to refute) conjecture, namely NL⊈ MPC(o(log N)). Refuting this conjecture would lead to o(log N) -round MPC algorithms for an even larger set of problems, including all-pairs shortest paths, betweenness centrality, and all aforementioned ones. Lower bounds under this conjecture hold for problems such as perfect matching and network flow.

Place, publisher, year, edition, pages
Springer Nature , 2022. Vol. 35, no 2, p. 165-183
Keywords [en]
Conditional hardness, Fine-grained complexity, Massively Parallel Computation, Complex networks, Computational complexity, Data handling, Graph theory, Complexity class, Fine grained, Large-scale data processing, Low bound, Massively parallels, Parallel Computation, Parallel computation model, Equivalence classes
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-319607DOI: 10.1007/s00446-021-00418-2ISI: 000744824300001PubMedID: 35300185Scopus ID: 2-s2.0-85123235387OAI: oai:DiVA.org:kth-319607DiVA, id: diva2:1701556
Note

QC 20221006

Available from: 2022-10-06 Created: 2022-10-06 Last updated: 2022-10-06Bibliographically approved

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Na Nongkai, Danupon

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