Wave‐based inversion at scale on graphical processing units with randomized trace estimation
Wave‐based inversion at scale on graphical processing units with randomized trace estimation
复制标题
通过随机轨迹估计，在图形处理单元上进行基于 Wave 的大规模反演
DOI：
10.1111/1365-2478.13405
复制
发表时间：
2023
影响因子：
2.6
通讯作者：
Herrmann, Felix J.
中科院分区：
文献类型：
--
作者：
Louboutin, Mathias;Herrmann, Felix J.
由于软件和硬件性能的不断提高，基于波动方程的成像技术，如全波形反演和逆时偏移，正变得更加常见。然而，这些先进成像方式的广泛适应尚未实现，因为当前的实现不能充分利用加速器，特别是由内存稀缺的图形处理单元提供的加速器。通过使用随机化轨迹估计，克服了这类硬件的存储瓶颈。以有限的计算开销和可控的非相干误差为代价，伴随状态方法的存储空间被大大减少。多亏了这种通过近似成像条件实现内存减少的相对简单的方法，我们能够在不卸载内存的情况下受益于图形处理单元。我们在声波二维和三维全波形反演实例以及横向倾斜各向同性介质中成像道集的形成上演示了所提出的算法的性能。
Thanks to continued performance improvements in software and hardware, wave‐equation‐based imaging technologies, such as full‐waveform inversion and reverse‐time migration, are becoming more commonplace. However, widespread adaptation of these advanced imaging modalities has not yet materialized because current implementations are not able to reap the full benefits from accelerators, in particular those offered by memory‐scarce graphics processing units. Through the use of randomized trace estimation, we overcome the memory bottleneck of this type of hardware. At the cost of limited computational overhead and controllable incoherent errors in the gradient, the memory footprint of adjoint‐state methods is reduced drastically. Thanks to this relatively simple to implement memory reduction via an approximate imaging condition, we are able to benefit from graphics processing units without memory offloading. We demonstrate the performance of the proposed algorithm on acoustic two‐ and three‐dimensional full‐waveform inversion examples and on the formation of image gathers in transverse tilted isotropic media.