Geodesic
Implementation and performance of wave tomography algorithms on simd cpu and gpu computing platforms
Numerical methods and programming, Tome 22 (2021) no. 4, pp. 322-332.

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This paper is concerned with implementation of wave tomography algorithms on modern SIMD CPU and GPU computing platforms. The field of wave tomography, which is currently under development, requires powerful computing resources. Main applications of wave tomography are medical imaging, nondestructive testing, seismic studies. Practical applications depend on computing hardware. Tomographic image reconstruction via wave tomography technique involves solving coefficient inverse problems for the wave equation. Such problems can be solved using iterative gradient-based methods, which rely on repeated numerical simulation of wave propagation process. In this study, finite-difference time-domain (FDTD) method is employed for wave simulation. This paper discusses software implementation of the algorithms and compares the performance of various computing devices: multi-core Intel and ARM-based CPUs, NVidia graphics processors.
Keywords: wave tomography, inverse problem, SIMD, GPU, benchmark.
Mots-clés : ARM 
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     title = {Implementation and performance of wave tomography algorithms on simd cpu and gpu computing platforms},
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A. V. Goncharsky; S. Y. Romanov; S. Yu. Seryozhnikov. Implementation and performance of wave tomography algorithms on simd cpu and gpu computing platforms. Numerical methods and programming, Tome 22 (2021) no. 4, pp. 322-332. http://geodesic.mathdoc.fr/item/VMP_2021_22_4_a6/