Abstract
Despite the increasing performance of modern processors it is well known that the majority of models that account for 3D underwater acoustic predictions still require a high computational cost. In this context, this work presents strategies to enhance the computational performance of a ray-based 3D model. First, it is presented an optimized method for acoustic field calculations, that accounts for a large number of sensors. Second, the inherent parallelism of ray tracing and the high workload of 3D propagation are carefully considered, leading to the development of parallel algorithms for field predictions using a GPU architecture. The strategies were validated through performance analyses and comparisons with experimental data from a tank scale experiment, and the results show that model predictions are computationally efficient and accurate. The combination of numerical enhancements and parallel computing allowed to speedup model calculations for a large number of receivers.
Supported by Institute of Sea Studies Admiral Paulo Moreira, Brazilian Navy. Thanks are due to the SiPLAB research team, LARSyS, FCT, University of Algarve.
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References
Johnson, O.G.: Three-dimensional wave equation computations on vector computers. Proc. IEEE 72, 90–95 (1984)
Tolstoy, A.: 3-D propagation issues and models. J. Comput. Acoust. 4(03), 243–271 (1996)
Jensen, F.B., Kuperman, W.A., Porter, M.B., Schmidt, H.: Computational Ocean Acoustics, 2nd edn. Springer, New York (2011). https://doi.org/10.1007/978-1-4419-8678-8
Jenserud, T., Ivansson, S.: Measurements and modeling of effects of out-of-plane reverberation on the power delay profile for underwater acoustic channels. IEEE J. Oceanic Eng. 40(4), 807–821 (2015)
Sturm, F., Korakas, A.: Comparisons of laboratory scale measurements of three-dimensional acoustic propagation with solutions by a parabolic equation model. J. Acoust. Soc. Am. 133(1), 108–118 (2013)
Etter, P.C.: Underwater Acoustic Modeling and Simulation, 4th edn. CRC Press, Boca Raton (2013)
Reilly, S.M., Potty, G.R., Goodrich, M.: Computing acoustic transmission loss using 3D Gaussian ray bundles in geodetic coordinates. J. Comput. Acoust. 24(01), 16500071–165000724 (2016)
Soares, C., Zabel, F., Jesus, S.M.: A shipping noise prediction tool. In: OCEANS 2015-Genova, pp. 1–7. IEEE (2015)
Calazan, R.M., Rodríguez, O.C.: TRACEO3D ray tracing model for underwater noise predictions. In: Camarinha-Matos, L.M., Parreira-Rocha, M., Ramezani, J. (eds.) DoCEIS 2017. IAICT, vol. 499, pp. 183–190. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56077-9_17
Kirk, D.B., Wen-Mei, W.H.: Programming Massively Parallel Processors: A Hands-on Approach. Morgan kaufmann, Burlington (2013)
Hursky, P., Porter, M.B.: Accelerating underwater acoustic propagation modeling using general purpose graphic processing units. In: OCEANS 2011, pp. 1–6. IEEE (2011)
Sun, X., Da, L., Li, Y.: Study of BDRM asynchronous parallel computing model based on multiple cuda streams. In: 2014 Seventh International Symposium on Computational Intelligence and Design (ISCID), vol. 1, pp. 181–184. IEEE (2014)
Ey, E.: Adaptation of an acoustic propagation model to the parallel architecture of a graphics processor. Master’s thesis, University of Algarve (2013)
Calazan, R.M., Rodríguez, O.C., Nedjah, N.: Parallel ray tracing for underwater acoustic predictions. In: Gervasi, O., et al. (eds.) ICCSA 2017. LNCS, vol. 10404, pp. 43–55. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62392-4_4
Open source high performance computing. https://www.open-mpi.org/. Accessed 13 June 2018
Ocean acoustics library. http://oalib.hlsresearch.com/. Accessed 03 July 2018
Rodriguez, O.C., Sturm, F., Petrov, P., Porter, M.: Three-dimensional model benchmarking for cross-slope wedge propagation. In: Proceedings of Meetings on Acoustics, Boston, MA, 25–29 June 2017, vol. 30, p. 070004. ASA (2017)
Calazan, R., Rodríguez, O.C.: Simplex based three-dimensional eigenray search for underwater predictions. J. Acoust. Soc. Am. 143(4), 2059–2065 (2018)
Rodriguez, O.C., Collis, J.M., Simpson, H.J., Ey, E., Schneiderwind, J., Felisberto, P.: Seismo-acoustic ray model benchmarking against experimental tank data. J. Acoust. Soc. Am. 132(2), 709–717 (2012)
Červenỳ, V., Pšenčík, I.: Ray amplitudes of seismic body waves in laterally inhomogeneous media. Geophys. J. Int. 57(1), 91–106 (1979)
Popov, M.M.: Ray theory and Gaussian beam method for geophysicists. EDUFBA, Salvador, Bahia (2002)
Porter, M.B.: BELLHOP3D user guide. Techical report, Heat, Light, and Sound Research Inc. (2016)
CUDA C programming guide. Technical Report, Nvidia Corporation (2018). https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html. Accessed 16 May 2018
The GNU FORTRAN compiler. https://gcc.gnu.org/onlinedocs/gfortran/Interoperability-with-C.html. Accessed 05 June 2018
Korakas, A., Sturm, F., Sessarego, J.-P., Ferrand, D.: Scaled model experiment of long-range across-slope pulse propagation in a penetrable wedge. J. Acoust. Soc. Am. 126(1), EL22–EL27 (2009)
Floating point and IEEE 754 compliance for NVIDIA GPUs. Technical Report, Nvidia Corporation (2018). https://docs.nvidia.com/cuda/floating-point/index.html. Accessed 31 May 2018
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Calazan, R.M., Rodríguez, O.C., Jesus, S.M. (2020). Numerical Enhancements and Parallel GPU Implementation of a 3D Gaussian Beam Model. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12249. Springer, Cham. https://doi.org/10.1007/978-3-030-58799-4_36
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