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Cache-aware Schedulability Analysis of PREM Compliant Tasks

dc.contributor.authorRashid, Syed Aftab
dc.contributor.authorAwan, Muhammad Ali
dc.contributor.authorSouto, Pedro
dc.contributor.authorBletsas, Konstantinos
dc.contributor.authorTovar, Eduardo
dc.date.accessioned2022-10-03T10:39:17Z
dc.date.available2022-10-03T10:39:17Z
dc.date.issued2022-01-11
dc.description.abstractThe Predictable Execution Model (PREM) is useful for mitigating inter-core interference due to shared resources such as the main memory. However, it is cache-agnostic, which makes schedulabulity analysis pessimistic, via overestimation of prefetches and write-backs. In response, we present cache-aware schedulability analysis for PREM tasks on fixed-task-priority partitioned multicores, that bounds the number of cache prefetches and write-backs. Our approach identifies memory blocks loaded in the execution of a previous scheduling interval of each task, that remain in the cache until its next scheduling interval. Doing so, greatly reduces the estimated prefetches and write backs. In experimental evaluations, our analysis improves the schedulability of PREM tasks by up to 55 percentage points.pt_PT
dc.description.sponsorshipThis work was partially supported by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology), within the CISTER Research Unit (UIDP/UIDB/04234/2020); also by the Operational Competitiveness Programme and Internationalization (COMPETE 2020) under the PT2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by national funds through the FCT, within project PREFECT (POCI-01-0145-FEDER-029119); also by the European Union’s Horizon 2020 - The EU Framework Programme for Research and Innovation 2014-2020, under grant agreement No. 732505. Project ”TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145- FEDER000020” financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreementpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.23919/DATE54114.2022.9774670
dc.identifier.urihttp://hdl.handle.net/10400.22/20900
dc.language.isoengpt_PT
dc.publisherIEEE
dc.relationUIDP/UIDB/04234/2020pt_PT
dc.relationPOCI-01-0145-FEDER-029119pt_PT
dc.relationLightweight Computation for Networks at the Edge
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.titleCache-aware Schedulability Analysis of PREM Compliant Taskspt_PT
dc.title.alternative220101pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleLightweight Computation for Networks at the Edge
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/732505/EU
oaire.fundingStreamH2020
person.familyNameSouto
person.familyNameBletsas
person.familyNameTovar
person.givenNamePedro
person.givenNameKonstantinos
person.givenNameEduardo
person.identifier.ciencia-id3114-46AE-02BB
person.identifier.ciencia-idC614-0255-0E07
person.identifier.ciencia-id6017-8881-11E8
person.identifier.orcid0000-0002-0822-3423
person.identifier.orcid0000-0002-3640-0239
person.identifier.orcid0000-0001-8979-3876
person.identifier.scopus-author-id23398810800
person.identifier.scopus-author-id6507950422
person.identifier.scopus-author-id7006312557
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication497682b6-33c1-47fb-a02d-b18bc941093b
relation.isAuthorOfPublicatione1e06d77-a9b1-4e27-8a98-bba7b3b7626c
relation.isAuthorOfPublication80b63d8a-2e6d-484e-af3c-55849d0cb65e
relation.isAuthorOfPublication.latestForDiscoverye1e06d77-a9b1-4e27-8a98-bba7b3b7626c
relation.isProjectOfPublication53ade512-30d8-4f8c-a0a4-9e38aee21e55
relation.isProjectOfPublication.latestForDiscovery53ade512-30d8-4f8c-a0a4-9e38aee21e55

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