Gravity inversion using wavelet-based compression on parallel hybrid CPU/GPU systems : application to southwest Ghana

2013

Article référencé dans le Web of Science WOS:000326964400014

Martin R., Monteiller V., Komatitsch D., Perrouty S., Jessell Mark, Bonvalot Sylvain, Lindsay M.

Geophysical Journal International, 2013, 195 (3), p. 1594-1619 ISSN 0956-540X

We solve the 3-D gravity inverse problem using a massively parallel voxel (or finite element) implementation on a hybrid multi-CPU/multi-GPU (graphics processing units/GPUs) cluster. This allows us to obtain information on density distributions in heterogeneous media with an efficient computational time. In a new software package called TOMOFAST3D, the inversion is solved with an iterative least-square or a gradient technique, which minimizes a hybrid L-1-/L-2-norm-based misfit function. It is drastically accelerated using either Haar or fourth-order Daubechies wavelet compression operators, which are applied to the sensitivity matrix kernels involved in the misfit minimization. The compression process behaves like a pre-conditioning of the huge linear system to be solved and a reduction of two or three orders of magnitude of the computational time can be obtained for a given number of CPU processor cores. The memory storage required is also significantly reduced by a similar factor. Finally, we show how this CPU parallel inversion code can be accelerated further by a factor between 3.5 and 10 using GPU computing. Performance levels are given for an application to Ghana, and physical information obtained after 3-D inversion using a sensitivity matrix with around 5.37 trillion elements is discussed. Using compression the whole inversion process can last from a few minutes to less than an hour for a given number of processor cores instead of tens of hours for a similar number of processor cores when compression is not used.

Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Géophysique interne [066]

GHANA

Fonds IRD

PAR00011166