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Multi-core for k-means clustering on FPGA

dc.contributor.authorCanilho, José
dc.contributor.authorVéstias, Mário
dc.contributor.authorNeto, Horácio
dc.date.accessioned2016-12-06T15:01:21Z
dc.date.available2016-12-06T15:01:21Z
dc.date.issued2016
dc.description.abstractIn this paper, a configurable many-core hardware/ software architecture is proposed to efficiently execute the widely known and commonly used K-means clustering algorithm. A prototype was designed and implemented on a Xilinx Zynq- 7000 All Programmable SoC. A single core configured with the slowest configuration achieves a 10X speed-up compared to the software only solution. The system is fully scalable and capable of achieving much higher speed-ups by increasing its parallelism.pt_PT
dc.identifier.citationCANILHO, José; VÉSTIAS, Mário Pereira; NETO, Horácio - Multi-core for k-means clustering on FPGA. In 26th International Conference on Field-Programmable Logic and Applications (FPL). Lausanne, Switzerland: IEEE, 2016. ISSN 1946-1488. Pp. 1-4pt_PT
dc.identifier.doihttp://ieeexplore.ieee.org/document/7577313/pt_PT
dc.identifier.issn1946-1488
dc.identifier.urihttp://hdl.handle.net/10400.21/6601
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.publisherversionhttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7577313pt_PT
dc.subjectClusteringpt_PT
dc.subjectK-meanspt_PT
dc.subjectHardware/Software Co-designpt_PT
dc.subjectHardware accelerationpt_PT
dc.subjectSystems on Chippt_PT
dc.titleMulti-core for k-means clustering on FPGApt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage4
oaire.citation.startPage1
person.familyNameVéstias
person.givenNameMário
person.identifier.ciencia-id4717-C2C7-3F2C
person.identifier.orcid0000-0001-8556-4507
person.identifier.ridH-9953-2012
person.identifier.scopus-author-id14525867300
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationa7d22b29-c961-45ac-bc09-cd5e1002f1e8
relation.isAuthorOfPublication.latestForDiscoverya7d22b29-c961-45ac-bc09-cd5e1002f1e8

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