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Accelerating multi-channel filtering of audio signal on ARM processors

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Abstract

Tablets and smart phones are nowadays equipped with low-power processor architectures such as the ARMv7 and the ARMv8 series. These processors integrate powerful SIMD units to exploit the intrinsic data-parallelism of most media and signal processing applications. In audio signal processing, there exist multiple problems that require filtering operations such as equalizations or signal synthesizers, among others. Most of these applications can be efficiently executed today on mobile devices by leveraging the processor SIMD unit. In this paper, we target the implementation of multi-channel filtering of audio signals on ARM architectures. To this end, we consider two common audio filter structures: FIR and IIR. The latter is analyzed in two different forms: direct form I and parallel form. Our results show that the SIMD-accelerated implementation increases the processing speed by a factor of 4\(\times \) with respect to the original code, and our hand-tuned SIMD implementation outperforms the auto-vectorized code by a factor of 2\(\times \). These results allow us to deal in real time with multi-channel systems composed of 260 FIR filters with 256 coefficients, or 125 IIR filters with 256 coefficients, of INT16 data type.

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References

  1. 1.

    ARM NEON. http://www.arm.com/. Accessed 23 Feb 2015

  2. 2.

    Rämo J, Välimäki V, Bank B (2014) High-precision parallel graphic equalizer. IEEE Trans Audio Speech Lang Process 22:1894–1904

  3. 3.

    Mathews MV, Miller JE, Moore FR, Pierce JR, Risset JC (1969) The technology of computer music. MIT Press, Cambridge, Mass

  4. 4.

    Risset JC (1985) Computer music experiments 185. Comput Music J 22:11–18

  5. 5.

    Puckette M (2007) The theory and technique of electronic music, World Scientific Publishing ISBN-13: 978–9812700773

  6. 6.

    Savioja L, Välimäki V, Smith JO (2011) Audio signal processing using graphics processing units. J Audio Eng Soc 59:3–19

  7. 7.

    Belloch JA, Bank B, Savioja L, Gonzalez A, Välimäki V (2014) Multi-channel IIR filtering of audio signals using a GPU. In: Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP-14), pp 6692–6696

  8. 8.

    Belloch JA, Gonzalez A, Martnez-Zaldívar FJ, Vidal AM (2013) Multichannel massive audio processing for a generalized crosstalk cancellation and equalization application using GPUs. Integr Comput Aided Eng 20:169–182

  9. 9.

    Algazi V, Duda R (2011) Headphone-based spatial sound. IEEE Signal Process Mag 28:33–42

  10. 10.

    Belloch JA, Ferrer M, Gonzalez A, Martinez-Zaldívar FJ, Vidal AM (2013) Headphone-based virtual spatialization of sound with a GPU accelerator. J Audio Eng Soc 61:546–556

  11. 11.

    Huang Y, Chen J, Benesty J (2011) Immerse audio schemes. IEEE Signal Process Mag 28:20–32

  12. 12.

    Oppenheim AV, Willsky AS, Hamid S (1997) Signals and systems, processing series, 2nd edn. Prentice Hall, Upper Saddle River

  13. 13.

    Bank B (2008) Perceptually motivated audio equalization using fixed-pole parallel second-order filters. IEEE Signal Process Lett 15:477–480

  14. 14.

    Mitra G, Johnston B, Rendell AP, McCreath E, Zhou J (2013) Use of SIMD vector operations to accelerate application code performance on low-powered ARM and Intel Platforms. In: IEEE 27th International Parallel and Distributed Processing Symposium Workshops PhD Forum (IPDPSW), pp 1107–1116

  15. 15.

    Welch E, Patru D, Saber E, Bengtson K (2012) A study of the use of SIMD instructions for two image processing algorithms. Western New York Image Processing Workshop (WNYIPW), pp 21–24

  16. 16.

    Wang R, Wan J, Wang W, Wang Z, Dong S, Gao W (2013) High definition IEEE AVS decoder on ARM NEON platform. In: 20th IEEE International Conference on Image Processing (ICIP), pp 1524–1527

  17. 17.

    Holgersson SB (2012) Optimising IIR filters using ARM NEON, Master Thesis of University of Denmark

  18. 18.

    Rabiner LR, Gold B (1975) Theory and application of digital signal processing. Prentice-Hall, Englewood Cliffs

  19. 19.

    ARM NEON intrinsics. http://gcc.gnu.org/onlinedocs/gcc-4.4.1/gcc/ARM-NEON-Intrinsics.html. Accessed 12 July 2015

  20. 20.

    ARM NEON auto-vectorization. http://gcc.gnu.org/onlinedocs/gcc/ARM-Options.html. Accessed 22 July 2015

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Acknowledgments

The researchers from Universitat Jaume I are supported by the CICYT projects TIN2014-53495-R and TIN2011-23283 of the Ministerio de Economía y Competitividad and FEDER. The authors from the Universitat Politècnica de València are supported by projects TEC2015-67387-C4-1-R and PROMETEOII/2014/003. This work was also supported from the European Union FEDER (CAPAP-H5 network TIN2014-53522-REDT).

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Correspondence to Jose A. Belloch.

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Belloch, J.A., Alventosa, F.J., Alonso, P. et al. Accelerating multi-channel filtering of audio signal on ARM processors. J Supercomput 73, 203–214 (2017). https://doi.org/10.1007/s11227-016-1689-8

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Keywords

  • Low-power processors
  • ARMv7 and ARM®Cortex-A15
  • NEON®Intrinsics
  • Audio processing