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dc.contributor.authorLockerman, Elliot
dc.contributor.authorFeldmann, Axel
dc.contributor.authorBakhshalipour, Mohammad
dc.contributor.authorStanescu, Alexandru
dc.contributor.authorGupta, Shashwat
dc.contributor.authorSanchez, Daniel
dc.contributor.authorBeckmann, Nathan
dc.date.accessioned2022-11-22T15:10:12Z
dc.date.available2022-07-19T15:50:21Z
dc.date.available2022-11-22T15:10:12Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/143865.2
dc.description.abstract© 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM. In order to scale, future systems will need to dramatically reduce data movement. Data movement is expensive in current designs because (i) traditional memory hierarchies force computation to happen unnecessarily far away from data and (ii) processing-in-memory approaches fail to exploit locality. We propose Memory Services, a flexible programming model that enables data-centric computing throughout the memory hierarchy. In Memory Services, applications express functionality as graphs of simple tasks, each task indicating the data it operates on. We design and evaluate Livia, a new system architecture for Memory Services that dynamically schedules tasks and data at the location in the memory hierarchy that minimizes overall data movement. Livia adds less than 3% area overhead to a tiled multicore and accelerates challenging irregular workloads by 1.3× to 2.4× while reducing dynamic energy by 1.2× to 4.7×.en_US
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionof10.1145/3373376.3378497en_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.sourceACMen_US
dc.titleLivia: Data-Centric Computing Throughout the Memory Hierarchyen_US
dc.typeArticleen_US
dc.identifier.citationLockerman, Elliot, Feldmann, Axel, Bakhshalipour, Mohammad, Stanescu, Alexandru, Gupta, Shashwat et al. 2020. "Livia: Data-Centric Computing Throughout the Memory Hierarchy." International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journalInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOSen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-07-19T15:47:00Z
dspace.orderedauthorsLockerman, E; Feldmann, A; Bakhshalipour, M; Stanescu, A; Gupta, S; Sanchez, D; Beckmann, Nen_US
dspace.date.submission2022-07-19T15:47:04Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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