Analyzing the memory ordering models of the Apple M1

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dc.identifier.uri http://dx.doi.org/10.15488/17196
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/17324
dc.contributor.author Wrenger, Lars
dc.contributor.author Töllner, Dominik
dc.contributor.author Lohmann, Daniel
dc.date.accessioned 2024-04-25T06:46:55Z
dc.date.available 2024-04-25T06:46:55Z
dc.date.issued 2024
dc.identifier.citation Wrenger, L.; Töllner, D.; Lohmann, D.: Analyzing the memory ordering models of the Apple M1. In: Journal of Systems Architecture 149 (2024), 103102. DOI: https://doi.org/10.1016/j.sysarc.2024.103102
dc.description.abstract The Apple M1 ARM processor family incorporates two memory consistency models: the conventional ARM weak memory ordering and the Total store ordering (TSO) model from the x86 architecture utilized by Apple's x86 emulator, Rosetta 2. The presence of both memory ordering models on the same hardware enables us to thoroughly benchmark and compare their performance characteristics and worst-case workloads. In this paper, we assess the performance implications of TSO on the Apple M1 processor architecture. Based on the multi-threading workloads of the SPEC2017 CPU FP benchmark suite, our findings indicate that TSO is, on average, 8.94 percent slower than ARM's weaker memory ordering. Through synthetic benchmarks, we further explore the workloads that experience the most significant performance degradation due to TSO. We also take a deeper look into the specific atomic instructions provided by the ARMv8.3 specification and their synchronization overheads. eng
dc.language.iso eng
dc.publisher Amsterdam : Elsevier
dc.relation.ispartofseries Journal of Systems Architecture 149 (2024)
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0
dc.subject Apple M1 eng
dc.subject ARM eng
dc.subject Memory ordering eng
dc.subject TSO eng
dc.subject.ddc 004 | Informatik
dc.title Analyzing the memory ordering models of the Apple M1 eng
dc.type Article
dc.type Text
dc.relation.essn 1873-6165
dc.relation.issn 1383-7621
dc.relation.doi https://doi.org/10.1016/j.sysarc.2024.103102
dc.bibliographicCitation.volume 149
dc.bibliographicCitation.firstPage 103102
dc.description.version publishedVersion eng
tib.accessRights frei zug�nglich
dc.bibliographicCitation.articleNumber 103102


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