Multicore implementation of a multichannel parallel graphic equalizer

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 proc...

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Bibliographic Details
Published inThe Journal of supercomputing Vol. 78; no. 14; pp. 15715 - 15729
Main Authors Belloch, Jose A., Badía, José M, León, German, Bank, Balázs, Välimäki, Vesa
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2022
Springer Nature B.V
Subjects
Algorithms
CMMSE- Computational and Mathematical methods
Compilers
Computer Science
Electronic devices
Embedded systems
Energy efficiency
Equalizers
Interpreters
Microprocessors
Mobile computing
Power consumption
Power management
Processor Architectures
Programming Languages
Real time
Signal processing
Sound reproduction
System-on-chip (SoC)
Embedded systems
Audio systems
Real time
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Summary: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.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-022-04495-3