Abstract
In order to improve the efficiency of magnetotelluric Occam inversion algorithm, a parallel Gaussian elimination algorithm based on two-dimensional constant bandwidth storage is developed, which is implemented on graphic processing units (GPUs) by using CUDA Fortran. Detailed descriptions of the programming are presented. The parallel algorithm can simultaneously and rapidly calculate multiple large matrices. To make full use of the GPU computational power and memory bandwidth, the data access patterns have been analyzed and optimized in depth for parallel access. The experimental results show that with the increase of the number of matrices, higher speedup can be obtained. The high efficiency of the parallel strategy makes it easier for other algorithms based on two-dimensional constant bandwidth storage.
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Acknowledgments
This work has been supported by the National Natural Science Foundation of China under research project 41264005 and also supported by the Guangxi department of education under the research project 201102ZD018.
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Xiao, Y., Liu, Y. (2015). GPU Acceleration for the Gaussian Elimination in Magnetotelluric Occam Inversion Algorithm. In: Wong, W. (eds) Proceedings of the 4th International Conference on Computer Engineering and Networks. Lecture Notes in Electrical Engineering, vol 355. Springer, Cham. https://doi.org/10.1007/978-3-319-11104-9_15
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DOI: https://doi.org/10.1007/978-3-319-11104-9_15
Publisher Name: Springer, Cham
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