Abstract
Kirchhoff pre-stack depth migration (KPSDM) algorithm, as one of the most widely used migration algorithms, plays an important part in getting the real image of the earth. However, this program takes considerable time due to its high computational cost; hence the working efficiency of the oil industry is affected. The general purpose Graphic Processing Unit (GPU) and the Compute Unified Device Architecture (CUDA) developed by NVIDIA have provided a new solution to this problem. In this study, we have proposed a parallel algorithm of the Kirchhoff pre-stack depth migration and an optimization strategy based on the CUDA technology. Our experiments indicate that for large data computations, the accelerated algorithm achieves a speedup of 8~15 times compared with NVIDIA GPU.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Deschizeaux, B., Blanc, J.Y.: Imaging Earth’s Subsurface Using CUDA, http://developer.download.nvidia.com/books/gpu_gems_3/samples/gems3_ch38.pdf
Sun, Y., Qin, F., Checkles, S., Leveille, J.P.: 3-D prestack Kirchhoff beam migration for depth imaging. Geophysics 65, 1592–1603 (2000)
Li, J.J., Dan, H., Lin, Y.: Partitioning Algorithm of 3-D Prestack Parallel Kirchhoff Depth Migration for Imaging Spaces. In: Eighth International Conference on Grid and Cooperative Computing 2009. IEEE (2009)
Xu, S., Lambar, G.: True amplitude Kirchhoff pre-stack depth migration in complex media. Chinese J. Geophys. 49(5), 1434–1444 (2006)
NVIDIA CUDA C Programming Guide, http://docs.nvidia.com/cuda/pdf/CUDA_C_Programming_Guide.pdf
Sui, H.G., Peng, F.F., Xu, C., et al.: GPU-accelerated MRF segmentation algorithm for SAR images. Computers & Geosciences 43, 159–166 (2012)
Shi, X.H., Li, C., Wang, S.H., et al.: Computing prestack Kirchhoff time migration on general purpose GPU. Computers & Geosciences 37(10), 1702–1710 (2011)
Huang, T., Li, X., Zhang, T., et al.: GPU-accelerated Direct Sampling method for multiple-point statistical simulation. Computers & Geosciences 57, 13–23 (2013)
Sanders, J., Kandrot, E.: CUDA by Example: An Introduction to General-Purpose GPU Programming (2010)
Kirk, D.B., Hwu, W.: Programming Massively Parallel Processors: A Hands-on Approach (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Wang, Y., Li, C., Tian, Y., Yan, H., Zhao, C., Zhang, J. (2014). A Parallel Algorithm of Kirchhoff Pre-stack Depth Migration Based on GPU. In: Sun, Xh., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2014. Lecture Notes in Computer Science, vol 8631. Springer, Cham. https://doi.org/10.1007/978-3-319-11194-0_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-11194-0_16
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11193-3
Online ISBN: 978-3-319-11194-0
eBook Packages: Computer ScienceComputer Science (R0)