A complexity-based classification for multiprocessor synchronization

Faith Ellen, Rati Gelashvili, Nir Shavit, Leqi Zhu

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)125-144
Number of pages20
JournalDistributed Computing
Volume33
Issue number2
DOIs
StatePublished - 1 Apr 2020

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