A complexity-based classification for multiprocessor synchronization

Faith Ellen, Rati Gelashvili*, Nir Shavit, Leqi Zhu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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

Funding

FundersFunder number
Intel corporations
Natural Science and Engineering Research Council of Canada
National Science FoundationCCF-1301926, CCF-1217921, IIS-1447786
U.S. Department of EnergyER26116/DE-SC0008923
Intel Corporation
Sun Microsystems
Oracle
Massachusetts Institute of Technology
Natural Sciences and Engineering Research Council of CanadaRGPIN-2015-05080
University of Toronto

    Fingerprint

    Dive into the research topics of 'A complexity-based classification for multiprocessor synchronization'. Together they form a unique fingerprint.

    Cite this