2016
Reduction of computing time for leastsquares migration based on the Helmholtz equation by graphics processing units
Publication
Publication
Computational Geosciences , Volume 20  Issue 2 p. 297 315
In geophysical applications, the interest in leastsquares
migration (LSM) as an imaging algorithm is
increasing due to the demand for more accurate solutions
and the development of highperformance computing. The
computational engine of LSM in this work is the numerical
solution of the 3D Helmholtz equation in the frequency
domain. The Helmholtz solver is BiCGSTAB preconditioned
with the shifted Laplace matrixdependent multigrid
method. In this paper, an efficient LSM algorithm is presented
using several enhancements. First of all, a frequency
decimation approach is introduced that makes use of redundant
information present in the data. It leads to a speedup of
LSM, whereas the impact on accuracy is kept minimal. Secondly,
a new matrix storage format Very Compressed Row
Storage (VCRS) is presented. It not only reduces the size of
the stored matrix by a certain factor but also increases the
efficiency of the matrixvector computations. The effects of
lossless and lossy compression with a proper choice of the
compression parameters are positive. Thirdly, we accelerate
the LSM engine by graphics cards (GPUs). A GPU is used
as an accelerator, where the data is partially transferred to
a GPU to execute a set of operations or as a replacement,
where the complete data is stored in the GPU memory. We
demonstrate that using the GPU as a replacement leads to
higher speedups and allows us to solve larger problem sizes.
Summarizing the effects of each improvement, the resulting
speedup can be at least an order of magnitude compared to
the original LSM method.
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doi.org/10.1007/s105960159546z  
Computational Geosciences  
Organisation  Scientific Computing 
Knibbe, H, Vuik, C, & Oosterlee, C.W. (2016). Reduction of computing time for leastsquares migration based on the Helmholtz equation by graphics processing units. Computational Geosciences, 20(2), 297–315. doi:10.1007/s105960159546z
