Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/9719
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dc.contributor.authorDerrick, J-
dc.contributor.authorSmith, G-
dc.contributor.authorDongol, B-
dc.date.accessioned2015-01-13T13:24:14Z-
dc.date.available2014-
dc.date.available2015-01-13T13:24:14Z-
dc.date.issued2014-
dc.identifier.citationLecture Notes in Computer Science, 8739, pp. 341 - 356, 2014en_US
dc.identifier.issn0302-9743-
dc.identifier.urihttp://link.springer.com/chapter/10.1007%2F978-3-319-10181-1_21-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/9719-
dc.description.abstractLinearizability is the standard correctness criterion for fine-grained, non-atomic concurrent algorithms, and a variety of methods for verifying linearizability have been developed. However, most approaches assume a sequentially consistent memory model, which is not always realised in practice. In this paper we define linearizability on a weak memory model: the TSO (Total Store Order) memory model, which is implemented in the x86 multicore architecture. We also show how a simulation-based proof method can be adapted to verify linearizability for algorithms running on TSO architectures. We demonstrate our approach on a typical concurrent algorithm, spinlock, and prove it linearizable using our simulation-based approach. Previous approaches to proving linearizabilty on TSO architectures have required a modification to the algorithm's natural abstract specification. Our proof method is the first, to our knowledge, for proving correctness without the need for such modification.en_US
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.subjectLinearizabilityen_US
dc.subjectConsistent memory modelen_US
dc.subjectTSO (Total Store Order)en_US
dc.subjectx86 multicore architectureen_US
dc.titleVerifying linearizability on TSO architecturesen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-319-10181-1_21-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
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pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Computer Science-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Computer Science/Computer Science-
Appears in Collections:Dept of Computer Science Research Papers

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