Massively parallel forward modeling of scalar and tensor gravimetry data.

Moorkamp, Max, Jegen-Kulcsar, Marion , Roberts, A. and Hobbs, R. (2010) Massively parallel forward modeling of scalar and tensor gravimetry data. Computers & Geosciences, 36 (5). pp. 680-686. DOI 10.1016/j.cageo.2009.09.018.

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Abstract

We present an approach to calculate scalar and tensor gravity utilizing the massively parallel architecture of consumer graphics cards. Our parametrization is based on rectilinear blocks with constant density within each blocks. This type of parametrization is well suited for inversion of gravity data or joint inversion with other datasets, but requires the calculation of a large number of model blocks for complex geometries. For models exceeding 10,000 cells we achieve an acceleration of a factor of 40 for scalar data and 30 for tensor data compared to a single thread on the CPU. This significant acceleration allows fast computation of large models exceeding 106 model parameters and thousands of measurement sites.

Document Type: Article
Keywords: Geophysics; Gravity modeling, Cuda, Parallel computing
Research affiliation: OceanRep > GEOMAR > Applied R&D > Energy and CO₂ Sequestration Projects
OceanRep > GEOMAR > FB4 Dynamics of the Ocean Floor > FB4-GDY Marine Geodynamics
Refereed: Yes
Open Access Journal?: No
DOI etc.: 10.1016/j.cageo.2009.09.018
ISSN: 0098-3004
Projects: Future Ocean
Date Deposited: 01 Mar 2010 11:30
Last Modified: 11 Dec 2017 13:04
URI: http://oceanrep.geomar.de/id/eprint/627

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