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 work was supported by the National Key R&D Program of China(2017YFC0602204-01) and NSFC (Grant Nos. 41530321 and 41104083).
Corresponding Authors: Liu Guo-Feng (E-mail: liugf@cugb.edu.cn)
E-mail: liugf@cugb.edu.cn
About author: 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 China University 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.
Cite this article:
. An efficient scheme for multi-GPU TTI reverse time migration*[J]. APPLIED GEOPHYSICS, 2019, 16(1): 61-69.
2019, Vol. 16 
