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dc.contributor.authorIssa, Shady
dc.contributor.authorFelber, Pascal
dc.contributor.authorMatveev, Alexander
dc.contributor.authorRomano, Paolo
dc.date.accessioned2021-09-17T18:01:50Z
dc.date.available2021-09-17T18:01:50Z
dc.date.issued2019-11-11
dc.identifier.urihttps://hdl.handle.net/1721.1/131299
dc.description.abstractAbstract Transactional memory (TM) aims at simplifying concurrent programming via the familiar abstraction of atomic transactions. Recently, Intel and IBM have integrated hardware based TM (HTM) implementations in commodity processors, paving the way for the mainstream adoption of the TM paradigm. Yet, existing HTM implementations suffer from a crucial limitation, which hampers the adoption of HTM as a general technique for regulating concurrent access to shared memory: the inability to execute transactions whose working sets exceed the capacity of CPU caches. In this article we propose P8TM, a novel approach that mitigates this limitation on IBM’s POWER8 architecture by leveraging a key combination of hardware and software techniques to support different execution paths. P8TM also relies on self-tuning mechanisms aimed at dynamically switching between different execution modes to best adapt to the workload characteristics. In-depth evaluation with several benchmarks indicates that P8TM can achieve striking performance gains in workloads that stress the capacity limitations of HTM, while achieving performance on par with HTM even in unfavourable workloads.en_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.isversionofhttps://doi.org/10.1007/s00446-019-00363-1en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSpringer Berlin Heidelbergen_US
dc.titleExtending hardware transactional memory capacity via rollback-only transactions and suspend/resumeen_US
dc.typeArticleen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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.updated2020-09-24T20:58:32Z
dc.language.rfc3066en
dc.rights.holderSpringer-Verlag GmbH Germany, part of Springer Nature
dspace.embargo.termsY
dspace.date.submission2020-09-24T20:58:32Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Needed


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