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Erschienen in: Distributed Computing 2/2020

04.09.2019

A complexity-based classification for multiprocessor synchronization

verfasst von: Faith Ellen, Rati Gelashvili, Nir Shavit, Leqi Zhu

Erschienen in: Distributed Computing | Ausgabe 2/2020

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Abstract

For many years, Herlihy’s elegant computability-based Consensus Hierarchy has been our best explanation of the relative power of various objects. Since real multiprocessors allow the different instructions they support to be applied to any memory location, it makes sense to consider combining the instructions supported by different objects, rather than considering collections of different objects. Surprisingly, this causes Herlihy’s computability-based hierarchy to collapse. In this paper, we suggest an alternative: a complexity-based classification of the relative power of sets of multiprocessor synchronization instructions, captured by the minimum number of memory locations of unbounded size that are needed to solve obstruction-free consensus when using different sets of instructions.

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Metadaten
Titel
A complexity-based classification for multiprocessor synchronization
verfasst von
Faith Ellen
Rati Gelashvili
Nir Shavit
Leqi Zhu
Publikationsdatum
04.09.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Distributed Computing / Ausgabe 2/2020
Print ISSN: 0178-2770
Elektronische ISSN: 1432-0452
DOI
https://doi.org/10.1007/s00446-019-00361-3

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