Show simple item record

dc.contributor.authorCardona, Jordi
dc.contributor.authorHernandez, Carles
dc.contributor.authorMezzetti, Enrico
dc.contributor.authorAbella, Jaume
dc.contributor.authorCazorla, Francisco J.
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2019-07-08T13:38:00Z
dc.date.available2019-07-08T13:38:00Z
dc.date.issued2019-01-07
dc.identifier.citationCardona, J. [et al.]. NoCo: ILP-Based Worst-Case Contention Estimation for Mesh Real-Time Manycores. A: "2018 IEEE Real-Time Systems Symposium (RTSS)". IEEE, 2019, p. 265-276.
dc.identifier.isbn978-1-5386-7908-1
dc.identifier.issn2576-3172
dc.identifier.urihttp://hdl.handle.net/2117/165804
dc.description.abstractManycores are capable of providing the computational demands required by functionally-advanced critical applications in domains such as automotive and avionics. In manycores a network-on-chip (NoC) provides access to shared caches and memories and hence concentrates most of the contention that tasks suffer, with effects on the worst-case contention delay (WCD) of packets and tasks' WCET. While several proposals minimize the impact of individual NoC parameters on WCD, e.g. mapping and routing, there are strong dependences among these NoC parameters. Hence, finding the optimal NoC configurations requires optimizing all parameters simultaneously, which represents a multidimensional optimization problem. In this paper we propose NoCo, a novel approach that combines ILP and stochastic optimization to find NoC configurations in terms of packet routing, application mapping, and arbitration weight allocation. Our results show that NoCo improves other techniques that optimize a subset of NoC parameters.
dc.description.sponsorshipThis work has been partially supported by the Spanish Ministry of Economy and Competitiveness under grant TIN2015- 65316-P and the HiPEAC Network of Excellence. It also received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (agreement No. 772773). Carles Hernández is jointly supported by the MINECO and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been partially supported by the Spanish Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Enrico Mezzetti has been partially supported by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva-Incorporaci´on postdoctoral fellowship number IJCI-2016-27396.
dc.format.extent12 p.
dc.language.isoeng
dc.publisherIEEE
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshHigh performance computing
dc.subject.otherNoC
dc.subject.otherMesh
dc.subject.otherWCET
dc.subject.otherILP
dc.subject.otherContention
dc.titleNoCo: ILP-Based Worst-Case Contention Estimation for Mesh Real-Time Manycores
dc.typeConference lecture
dc.subject.lemacSupercomputadors
dc.identifier.doi10.1109/RTSS.2018.00043
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8603219
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/772773/EU/Sustainable Performance for High-Performance Embedded Computing Systems/SuPerCom
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/TIN2014-60404-JIN
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/IJCI-2016-27396
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/RYC-2013-14717
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/TIN2015-65316-P
upcommons.citation.publishedtrue
upcommons.citation.publicationName2018 IEEE Real-Time Systems Symposium (RTSS)
upcommons.citation.startingPage265
upcommons.citation.endingPage276


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder