Comparison of Parallel Computing Approaches of a Finite-Difference Implementation of the Acoustic Diffusion Equation Model

Navarro JM, Imbernón B, López JJ, Cecilia JM. Comparison of Parallel Computing Approaches of a Finite-Difference Implementation of the Acoustic Diffusion Equation Model. In: AES Convention 139. Audio Engineering Society; 2015. Paper 9359. Available from: https://aes.org/publications/elibrary-page/?id=17917

@inproceedings{Navarro2015_17917,
  author = {Navarro, Juan M. and Imbernón, Baldomero and López, José J. and Cecilia, José M.},
  title = {{Comparison of Parallel Computing Approaches of a Finite-Difference Implementation of the Acoustic Diffusion Equation Model}},
  booktitle = {AES Convention 139},
  note = {Paper 9359},
  year = {2015},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=17917}
}

TY  - CPAPER
TI  - Comparison of Parallel Computing Approaches of a Finite-Difference Implementation of the Acoustic Diffusion Equation Model
AU  - Navarro, Juan M.
AU  - Imbernón, Baldomero
AU  - López, José J.
AU  - Cecilia, José M.
T2  - AES Convention 139
M1  - Paper 9359
PY  - 2015
DA  - 2015/10/06
UR  - https://aes.org/publications/elibrary-page/?id=17917
PB  - Audio Engineering Society
LA  - en
AB  - The diffusion equation model has been intensively researched as a room-acoustics simulation algorithm during last years. A 3-D finite-difference implementation of this model was proposed to evaluate the propagation over time of sound field within rooms. Despite the computational saving of this model to calculate the room energy impulse response, elapsed times are still long when high spatial resolutions and/or simulations in several frequency bands are needed. In this work several data-parallel approaches of this finite-difference solution on Graphics Processing Units are proposed using a compute unified device architecture programming model. A comparison of their performance running on different models of Nvidia GPUs is carried out. In general, 2D vertical block approach running in a Tesla K20C shows the best speed-up of more than 15 times versus CPU version.
ER  -