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dc.contributor.authorBELLOCH, JOSE A.
dc.contributor.authorBadía, José
dc.contributor.authorLeón, Germán
dc.contributor.authorBank, Balázs
dc.contributor.authorVälimäki, Vesa
dc.date.accessioned2022-10-03T10:57:13Z
dc.date.available2022-10-03T10:57:13Z
dc.date.issued2022-04-22
dc.identifier.citationBelloch, J.A., Badía, J., León, G. et al. Multicore implementation of a multichannel parallel graphic equalizer. J Supercomput 78, 15715–15729 (2022). https://doi.org/10.1007/s11227-022-04495-3ca_CA
dc.identifier.issn0920-8542
dc.identifier.issn1573-0484
dc.identifier.urihttp://hdl.handle.net/10234/200095
dc.description.abstractNumerous signal processing applications are emerging on mobile computing systems. These applications are subject to responsiveness constraints for user interactivity and, at the same time, must be optimized for energy efficiency. Many current embedded devices are composed of low-power multicore processors that offer a good trade-off between computational capacity and low power consumption. In this context, equalizers are widely used in multiple mobile-based applications such as “Music streaming” to adjust the levels of bass and treble in sound reproduction. In this study, we evaluate a graphic equalizer from audio, computational capacity, and energy efficiency perspectives, as well as the execution of multiple real-time equalizers running on an embedded quad-core processor of a mobile device. To this end, we experiment with the working frequencies as well as the parallelism that can be extracted from a quad-core ARM Cortex-A57. Results show that using high CPU frequencies and three or four cores, our parallel algorithm is able to equalize more than five channels per watt in real time with an audio buffer of 4096 samples, which implies a latency of 92.8 ms at the standard sample rate of 44.1 kHz.ca_CA
dc.description.sponsorShipFunding for open access charge: CRUE-Universitat Jaume I
dc.format.extent15 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherSpringerca_CA
dc.relationAyuda Movilidad Programa Propio de Investigación, modalidad A: jóvenes doctoresca_CA
dc.relation.isPartOfThe Journal of Supercomputing (2022) 78:15715–15729ca_CA
dc.rights© The Author(s) 2022ca_CA
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/ca_CA
dc.subjectaudio systemsca_CA
dc.subjectreal timeca_CA
dc.subjectembedded systemsca_CA
dc.subjectsystem-on-chip (SoC)ca_CA
dc.titleMulticore implementation of a multichannel parallel graphic equalizerca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1007/s11227-022-04495-3
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA
project.funder.nameAalto Universityca_CA
project.funder.nameUniversidad Carlos IIIca_CA
project.funder.nameMinisterio de Ciencia, Innovación y Universidadesca_CA
project.funder.nameNational Research, Development, and Innovation Fund of Hungaryca_CA
project.funder.nameRegional Government of Madridca_CA
oaire.awardNumberNordForsk Project No. 86892ca_CA
oaire.awardNumber2021/00310/001ca_CA
oaire.awardNumberPID2019-106455GB-C21ca_CA
oaire.awardNumberPID2020-113656RB-C21ca_CA
oaire.awardNumberTKP2021-EGA-02ca_CA
oaire.awardNumberMIMACUHSPACE-CM-UC3M (2022/00024/001)ca_CA


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