Skip to main content
Log in

An efficient scheme for multi-GPU TTI reverse time migration

  • Seismic migration/inversion
  • Published:
Applied Geophysics Aims and scope Submit manuscript

Abstract

Reverse time migration (RTM) is an indispensable but computationally intensive seismic exploration technique. Graphics processing units (GPUs) by NVIDIA® offer the option for parallel computations and speed improvements in such high-density processes. With increasing seismic imaging space, the problems associated with multi-GPU techniques need to be addressed. We propose an efficient scheme for multi-GPU programming based on the features of the compute-unified device Architecture (CUDA) using GPU hardware, including concurrent kernel execution, CUDA streams, and peer-to-peer (P2P) communication between the different GPUs. In addition, by adjusting the computing time for imaging during RTM, the data communication times between GPUs become negligible. This means that the overall computation efficiency improves linearly, as the number of GPUs increases. We introduce the multi-GPU scheme by using the acoustic wave propagation and then describe the implementation of RTM in tilted transversely isotropic (TTI) media. Next, we compare the multi-GPU and the unified memory schemes. The results suggest that the proposed multi-GPU scheme is superior and, with increasing number of GPUs, the computational efficiency improves linearly.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Cheng, J., Grossman, M., and McKercher, T., 2014, Professional CUDA C Programming, Wiley & Sons Inc., Indianapolis, Indiana, P71, 73, 74, 268, 391

    Google Scholar 

  • Foltinek, D., Eaton, D., Mahovsky, J., Moghaddam, P., and McGarry, R., 2009, Industrial-scale reverse time migration on GPU hardware: 79th Annual International Meeting, SEG, Expanded Abstracts, 2789–2793.

  • Fletcher R.P., X. Du, P.J. Fowler, 2009, Reverse time migration in tilted transversely isotropic media: Geophysics, 74, 179–187.

    Article  Google Scholar 

  • Liu, H.W., Li, B., Liu, H., Tong, X.L., Liu, Q., Wang, X. W., and Liu, W.Q., 2012. The issue of prestack reverse time migration and solutions with Graphic Processing Unit implementation, Geophysical Prospecting, 60, 906–918, doi: https://doi.org/10.1111/j.1365-2478.2011.01032.x

    Article  Google Scholar 

  • Liu, H.W., Li, B., Liu, H., Tong, X.L. and Liu, Q., 2010. The algorithm of high order finite difference pre-stack reverse time migration and GPU implementation. The Chinese Journal of Geophysics, 53(7), 1725–1733.

    Google Scholar 

  • Li, B., Liu, G.F. and Liu, H., 2009. A method of using GPU to accelerate seismic pre-stack time migration: The Chinese Journal of Geophysics, 52(1), 245–252.

    Google Scholar 

  • Liu, G.F., and Li, C., 2016, Practical implementation of prestack Kirchhoff time migration on a general purpose graphic processing unit: Acta Geophysica, 64, 1051–1063, doi: https://doi.org/10.1515/cgeo-2016-0033

    Article  Google Scholar 

  • Liu, L.R., Ding, W., Liu, H.W., and Liu, H., 2015, 3D hybrid-domain full waveform inversion on GPU: Computers and Geosciences, 83, 27–36.

    Article  Google Scholar 

  • Liu, G.F., Meng, X.H., and Liu, H., 2012, Accelerating finite difference wavefield-continuation depth migration by GPU: Applied Geophysics, 9, 41–48

    Article  Google Scholar 

  • Liu, G.F., Liu, Y.N., and Meng, X.H., 2013, 3D seismic reverse time migration on GPGPU: Computers and Geosciences, 59, 17–23

    Article  Google Scholar 

  • Micikevicius, P., 2009, 3D Finite difference computation on GPUs using CUDA: Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units, GPGPU-2, Association for Computing Machinery, 79–84.

  • Morton, S., Cullison, T., and Micikevicius, P., 2008, Experiences with seismic imaging on GPUs: 70th Annual International Conference and exhibition, EAGE, Extended Abstracts, W08.

  • Nakata, N., Tsuji, T. and Matsuoka, T., 2011, Acceleration of computation speed for elastic wave simulation using a graphics processing unit: Exploration Geophysics, 42, 98–104, doi: https://doi.org/10.1071/EG10039.

    Article  Google Scholar 

  • NVIDIA®, 2017, CUDA C Programming Guide; http://docs.nvidia.com/cuda/pdf/CUDA_C_Programming_Guide.pdf

  • Komatitsch, D., Erlebacher, G., Göddeke, D., and Michea, D., 2010, High-order finite-element seismic wave propagation modeling with MPI on a large GPU cluster: Journal of Computational Physics, 229, 7692–7714, doi: https://doi.org/10.1016/j.jcp.2010.06.024

    Article  Google Scholar 

  • Okamoto, T., Takenaka, H., Nakamura, T., and Aoki, T., 2010, Accelerating large-scale simulation of seismic wave propagation by multi-GPUs and three-dimensional domain decomposition: Earth Planets and Space, 62, 939–942

    Article  Google Scholar 

  • Shi, X.H., Li, C., and Wang, S.H., 2011, Computing prestack Kirchhoff time migration on general purpose GPU: Computers & Geosciences, 37, 1702–1710

    Article  Google Scholar 

  • Shi, Y and Wang, Y.H., 2016, Reverse time migration of 3D vertical seismic profile data: Geophysics, 81(1), S31–S38

    Article  Google Scholar 

  • Weiss, R.M., and Shragge, J., 2013, Solving 3D anisotropic elastic wave equation on parallel GPU devices: Geophysics, 78, 7–15, doi: https://doi.org/10.1190/GEO2012-0063.1

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank the reviewers, Drs. He Bingshou, Wang Boli, Li Zhenchun, and Chen Tiansheng and editors. Their comments and suggestions improved the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guo-Feng Liu.

Additional information

This work was supported by the National Key R&D Program of China(2017YFC0602204-01) and NSFC (Grant Nos. 41530321 and 41104083).

Liu Guo-Feng received a B.S. in Exploration Technology and Engineering (2004) from the China University of Geosciences (Beijing), an M.S. in Earth Exploration and Information Technology (2007) from the ChinaUniversity of Geosciences (Beijing), and a Ph.D. in Solid Geophysics (2010) from the Institute of Geology and Geophysics, CAS. Since 2010, he has been a faculty member in the School of Geophysics and Information Technology, China University of Geosciences (Beijing) and has been a postdoctoral research fellow at the Institute of Mineral Resource, Chinese Academy of Geological Sciences. His research interests include seismic wave simulations and imaging, as well as highperformance computing.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, GF., Meng, XH., Yu, ZJ. et al. An efficient scheme for multi-GPU TTI reverse time migration. Appl. Geophys. 16, 56–63 (2019). https://doi.org/10.1007/s11770-018-0743-8

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11770-018-0743-8

Keywords

Navigation