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Equivalence classes and conditional hardness in massively parallel computations

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...

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Autores principales: Nanongkai, Danupon, Scquizzato, Michele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907129/
https://www.ncbi.nlm.nih.gov/pubmed/35300185
http://dx.doi.org/10.1007/s00446-021-00418-2
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author Nanongkai, Danupon
Scquizzato, Michele
author_facet Nanongkai, Danupon
Scquizzato, Michele
author_sort Nanongkai, Danupon
collection PubMed
description 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., [Formula: see text] ), 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 [Formula: see text] , and the standard space complexity classes [Formula: see text] and [Formula: see text] , 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 [Formula: see text] conjecture: these two assumptions are equivalent, and refuting either of them would lead to [Formula: see text] -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 [Formula: see text] . Refuting this conjecture would lead to [Formula: see text] -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.
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spelling pubmed-89071292022-03-15 Equivalence classes and conditional hardness in massively parallel computations Nanongkai, Danupon Scquizzato, Michele Distrib Comput Article 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., [Formula: see text] ), 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 [Formula: see text] , and the standard space complexity classes [Formula: see text] and [Formula: see text] , 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 [Formula: see text] conjecture: these two assumptions are equivalent, and refuting either of them would lead to [Formula: see text] -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 [Formula: see text] . Refuting this conjecture would lead to [Formula: see text] -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. Springer Berlin Heidelberg 2022-01-20 2022 /pmc/articles/PMC8907129/ /pubmed/35300185 http://dx.doi.org/10.1007/s00446-021-00418-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Nanongkai, Danupon
Scquizzato, Michele
Equivalence classes and conditional hardness in massively parallel computations
title Equivalence classes and conditional hardness in massively parallel computations
title_full Equivalence classes and conditional hardness in massively parallel computations
title_fullStr Equivalence classes and conditional hardness in massively parallel computations
title_full_unstemmed Equivalence classes and conditional hardness in massively parallel computations
title_short Equivalence classes and conditional hardness in massively parallel computations
title_sort equivalence classes and conditional hardness in massively parallel computations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907129/
https://www.ncbi.nlm.nih.gov/pubmed/35300185
http://dx.doi.org/10.1007/s00446-021-00418-2
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