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dc.contributor.authorAlistarh, Dan
dc.contributor.authorKuznetsov, Petr
dc.contributor.authorRavi, Srivatsan
dc.contributor.authorKopinsky, Justin
dc.contributor.authorShavit, Nir N.
dc.date.accessioned2018-07-06T17:35:33Z
dc.date.available2018-07-06T17:35:33Z
dc.date.issued2017-06
dc.identifier.issn0178-2770
dc.identifier.issn1432-0452
dc.identifier.urihttp://hdl.handle.net/1721.1/116831
dc.description.abstractSeveral hybrid transactional memory (HyTM) schemes have recently been proposed to complement the fast, but best-effort nature of hardware transactional memory with a slow, reliable software backup. However, the costs of providing concurrency between hardware and software transactions in HyTM are still not well understood. In this paper, we propose a general model for HyTM implementations, which captures the ability of hardware transactions to buffer memory accesses. The model allows us to formally quantify and analyze the amount of overhead (instrumentation) caused by the potential presence of software transactions. We prove that (1) it is impossible to build a strictly serializable HyTM implementation that has both uninstrumented reads and writes, even for very weak progress guarantees, and (2) the instrumentation cost incurred by a hardware transaction in any progressive opaque HyTM is linear in the size of the transaction’s data set. We further describe two implementations which exhibit optimal instrumentation costs for two different progress conditions. In sum, this paper proposes the first formal HyTM model and captures for the first time the trade-off between the degree of hardware-software TM concurrency and the amount of instrumentation overhead. Keywords: hardware transactional memory, Instrumentation, Lower boundsen_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.isversionofhttps://doi.org/10.1007/s00446-017-0305-3en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceSpringer Berlin Heidelbergen_US
dc.titleInherent limitations of hybrid transactional memoryen_US
dc.typeArticleen_US
dc.identifier.citationAlistarh, Dan, et al. “Inherent Limitations of Hybrid Transactional Memory.” Distributed Computing, vol. 31, no. 3, June 2018, pp. 167–85.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorKopinsky, Justin
dc.contributor.mitauthorShavit, Nir N.
dc.relation.journalDistributed Computingen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-04-21T03:56:22Z
dc.language.rfc3066en
dc.rights.holderSpringer-Verlag GmbH Germany
dspace.orderedauthorsAlistarh, Dan; Kopinsky, Justin; Kuznetsov, Petr; Ravi, Srivatsan; Shavit, Niren_US
dspace.embargo.termsNen
dc.identifier.orcidhttps://orcid.org/0000-0003-2062-0998
dc.identifier.orcidhttps://orcid.org/0000-0002-4552-2414
mit.licenseOPEN_ACCESS_POLICYen_US


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