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Acoustic reverse-time migration using GPU card and POSIX thread based on the adaptive optimal finite-difference scheme and the hybrid absorbing boundary condition

机译:基于自适应最优有限差分方案和混合吸收边界条件的GPU卡和POSIX线程的声学逆时偏移

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摘要

Reverse-time migration (RTM) is a powerful tool for imaging geologically complex structures such as steep-dip and subsalt. However, its implementation is quite computationally expensive. Recently, as a low-cost solution, the graphic processing unit (GPU) was introduced to improve the efficiency of RTM. In the paper, we develop three ameliorative strategies to implement RTM on GPU card. First, given the high accuracy and efficiency of the adaptive optimal finite-difference (FD) method based on least squares (LS) on central processing unit (CPU), we study the optimal LS-based FD method on GPU. Second, we develop the CPU-based hybrid absorbing boundary condition (ABC) to the GPU-based one by addressing two issues of the former when introduced to GPU card: time-consuming and chaotic threads. Third, for large-scale data, the combinatorial strategy for optimal checkpointing and efficient boundary storage is introduced for the trade-off between memory and recomputation. To save the time of communication between host and disk, the portable operating system interface (POSIX) thread is utilized to create the other CPU core at the checkpoints. Applications of the three strategies on GPU with the compute unified device architecture (CUDA) programming language in RTM demonstrate their efficiency and validity.
机译:逆时偏移(RTM)是用于对地质复杂结构(如陡倾和盐下)成像的强大工具。但是,其实现在计算上非常昂贵。最近,作为一种低成本解决方案,引入了图形处理单元(GPU)以提高RTM的效率。在本文中,我们开发了三种改进策略来在GPU卡上实现RTM。首先,鉴于中央处理器(CPU)上基于最小二乘(LS)的自适应最优有限差分(FD)方法的高精度和高效率,我们研究了GPU上基于LS的最优FD方法。其次,通过解决前者引入GPU卡时的两个问题:耗时和混乱的线程,我们将基于CPU的混合吸收边界条件(ABC)开发为基于GPU的混合边界条件。第三,对于大规模数据,引入了最佳检查点和有效边界存储的组合策略,以在存储和重新计算之间进行权衡。为了节省主机和磁盘之间的通信时间,可移植操作系统接口(POSIX)线程用于在检查点创建另一个CPU内核。这三种策略在RTM中通过计算统一设备体系结构(CUDA)编程语言在GPU上的应用证明了其效率和有效性。

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  • 来源
    《Computers & geosciences》 |2018年第6期|42-55|共14页
  • 作者单位

    China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing 102249, Peoples R China;

    China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing 102249, Peoples R China;

    China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing 102249, Peoples R China;

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