Multicore implementation of a multichannel parallel graphic equalizer
View/ Open
Impact
Scholar |
Other documents of the author: BELLOCH, JOSE A.; Badía, José; León, Germán; Bank, Balázs; Välimäki, Vesa
Metadata
Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
comunitat-uji-handle4:
INVESTIGACIONMetadata
Title
Multicore implementation of a multichannel parallel graphic equalizerDate
2022-04-22Publisher
SpringerISSN
0920-8542; 1573-0484Bibliographic citation
Belloch, 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/s11227-022-04495-3Type
info:eu-repo/semantics/articleVersion
info:eu-repo/semantics/publishedVersionSubject
Abstract
Numerous 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 ... [+]
Numerous 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. [-]
Is part of
The Journal of Supercomputing (2022) 78:15715–15729Funder Name
Aalto University | Universidad Carlos III | Ministerio de Ciencia, Innovación y Universidades | National Research, Development, and Innovation Fund of Hungary | Regional Government of Madrid
Project code
NordForsk Project No. 86892 | 2021/00310/001 | PID2019-106455GB-C21 | PID2020-113656RB-C21 | TKP2021-EGA-02 | MIMACUHSPACE-CM-UC3M (2022/00024/001)
Project title or grant
Ayuda Movilidad Programa Propio de Investigación, modalidad A: jóvenes doctores
Rights
© The Author(s) 2022
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
This item appears in the folowing collection(s)
- ICC_Articles [418]