Multi-component anisotropy prestack time migration based on collaborative parallel computing with CPU and GPU
LIU Shuai1, JI Xiaohui1, LU Jun2, RONG Junzhao2
1. School of Information Engineering, China University of Geosciences(Beijing), Beijing 100083, China; 2. School of Energy Resources, China University of Geosciences(Beijing), Beijing 100083, China
Abstract:The anisotropy prestack time migration (PSTM) algorithm costs a lot of time in practical application due to current seismic survey sizes.CPU-cluster computing is usually used to accelerate PSTM,but it leads to the increase of communication cost between the computing nodes.According to the CPU structure,the only way to improve a cluster performance is to enlarge the scale of cluster.To solve this problem,a multi-component anisotropy PSTM algorithm based on collaborative parallel computing with CPU and GPU is proposed.This algorithm implements CPU collaborative parallel computing with a multi-GPUs environment and OpenMP and compute unified device architecture (CUDA).It decreases I/O costs with the memory map method,and optimizes reading and storing seismic data according to the structural features of CPU and GPU.The algorithm segments image volume to decrease memory occupation,computes the number of inlines which is equal to the number of available GPUs.One GPU thread will image one seismic data trace amongst inline.The propose approach was tested on 29GB seismic data with different numbers of GPUs.Between P-P wave and P-S wave seismic data,speedups are 444 and 449 when parallel computing with CPU collaborative parallel computing to 6 GPUs.
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LIU Shuai, JI Xiaohui, LU Jun, RONG Junzhao. Multi-component anisotropy prestack time migration based on collaborative parallel computing with CPU and GPU. Oil Geophysical Prospecting, 2019, 54(1): 65-72.
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