Parallel algorithm of seismic signal frequency compensation based on CUDA
ZHANG Quan1,2,3, ZHANG Jieming1, LEI Qin1, PENG Bo1,2, LIU Shuyan1,2
1. School of Computer Science, Southwest Petroleum University, Chengdu, Sichuan 610500, China; 2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University), Chengdu, Sichuan 610500, China; 3. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
Abstract:The frequency compensation algorithm of seismic signals based on compressed sensing can effectively broaden the spectrum of seismic signals and improve the resolution of seismic data. Although the algorithm has a good frequency-broadening effect, it has low time efficiency in the face of high-dimensional and large-scale seismic data. Analysis shows that the bottleneck of the algorithm lies in massive algebraic operations for the reflection coefficient and convolution operations in signal reconstruction. Therefore, a parallel scheme based on CUDA is proposed for parallel optimization of the algorithm. Firstly, the organization form of seismic data is changed to make it more efficient and more suitable for parallel processing. Then, the serial code for computing the reflection coefficient is reconstructed, and a large number of lightweight threads of GPU are called by CUDA to parallelize the algebraic operations. Finally, the convolution calculation method of time-domain signals is changed by the convolution theorem, and the convolution operation of two time-domain signals is converted to the frequency domain by the cufft library function. The results reveal that the parallel algorithm achieves four times the overall speedup of the serial algorithm on the PC side on the pre-mise of ensuring computational accuracy.
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