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The persistent challenge of data locality in the post-exascale era

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dc.contributor.coauthorUnat, D.
dc.contributor.coauthorDubey, A.
dc.contributor.coauthorJeannot, E.
dc.contributor.coauthorShalf, J.
dc.date.accessioned2026-08-14T11:27:34Z
dc.date.issued2025
dc.description.abstractThe era of exascale computing, exemplified by systems like Frontier, achieving exaflop-level performance marks a milestone. However, the quest for sheer compute power leads to strong imbalance in system design. Hence, scaling advancements in memory, network bandwidth, and storage are also necessary and poses challenges, with a crucial need to address data locality issues. This paper underscores the fundamental importance of data locality as a key abstraction for optimizing application performance. Despite notable software solutions, the growing complexity of parallelism and memory hierarchy demands performance portable data locality solutions across diverse computing platforms. The manuscript revisits data locality aspects, covering hardware considerations, application perspectives, software stack abstractions and tool support. It concludes with insights into data locality challenges and opportunities, emphasizing the ongoing significance of collaborative research for progress in this critical issue.
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuEU
dc.description.sponsorshipThe authors thank the 6th Programming and Abstractions for Data Locality Workshop participants for engaging in lively discussions at the workshop, which greatly contributed to the compilation of this article. Dr. Unat received funding from the European Research Council under the European Union's Horizon 2020 Research and Innovation Programme (Grant 949587). This work was supported by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research, under Contract DE-AC02-06CH11357.
dc.description.versionPublished Version
dc.identifier.ScopusPercentile69
dc.identifier.ScopusQuartileQ2
dc.identifier.WoSPercentile42,4
dc.identifier.WoSQuartileQ3
dc.identifier.doi10.1109/mcse.2025.3567586
dc.identifier.eissn1558-366X
dc.identifier.embargoN/A
dc.identifier.endpage27
dc.identifier.grantno949587
dc.identifier.grantnoDE-AC02-06CH11357
dc.identifier.issn1521-9615
dc.identifier.issue4
dc.identifier.scopus2-s2.0-105004703464
dc.identifier.startpage19
dc.identifier.urihttp://doi.org/10.1109/mcse.2025.3567586
dc.identifier.urihttps://hdl.handle.net/20.500.14288/34663
dc.identifier.volume27
dc.identifier.wos001653534900001
dc.keywordsMarket research
dc.keywordsComputational modeling
dc.keywordsBandwidth
dc.keywordsWires
dc.keywordsTransistors
dc.keywordsResource management
dc.keywordsMemory management
dc.keywordsMathematical models
dc.keywordsHardware
dc.keywordsVoltage control
dc.keywordsExascale computing
dc.languageeng
dc.publisherIEEE
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofComputing in Science and Engineering
dc.relation.openaccessN/A
dc.rightsN/A
dc.rights.uriN/A
dc.subjectDecision sciences
dc.subjectInformation systems and management
dc.subjectComputer science
dc.titleThe persistent challenge of data locality in the post-exascale era
dc.typeJournal Article
dspace.entity.typePublication

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