Macro-parallelisation for controlled source electromagnetic applications
dc.contributor.author | Pethick, Andrew | |
dc.contributor.author | Harris, Brett | |
dc.date.accessioned | 2017-01-30T11:36:23Z | |
dc.date.available | 2017-01-30T11:36:23Z | |
dc.date.created | 2015-12-27T20:00:13Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Pethick, A. and Harris, B. 2016. Macro-parallelisation for controlled source electromagnetic applications. Journal of Applied Geophysics. 124: pp. 91-105. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/13335 | |
dc.identifier.doi | 10.1016/j.jappgeo.2015.11.013 | |
dc.description.abstract |
© 2015 Elsevier B.V. Many geophysical computational problems can be referred to as "embarrassingly parallel". Parallel computing utilises linked CPU cores to solve computational problems. We create a "macro" parallelisation method that rapidly recovers solutions to large scale electromagnetic forward and inverse modelling problems. The method involves software operating above a generic electromagnetic data structure. Two examples are provided. The first example quantifies the reduction in computational time where macro-parallelisation is applied to forward modelling of data generated during synthetic marine controlled source electromagnetic surveys. In the second numerical experiment we apply macro-parallelisation to recover the subsurface conductivity distribution from a large airborne transient electromagnetic survey spanning more than 2000km2. The computation time for inverting 98 thousand soundings with a serial batch approach on an i7 with a single thread was 65h. Computational time from inverting 98 thousand soundings on a single thread of a standard i7 processor was 65h. A 1700 times improvement in computation time was achieved through macro-parallelisation across just 350 cores of a Cray XC30 Supercomputer. Inversion of data for the full AEM survey took just 135s. Parallel computing is rapidly becoming an essential for geophysicists. We provide description, sequence diagrams, pseudo-code and examples to illustrate its implementation. In summary we present applied parallelisation for the masses. | |
dc.title | Macro-parallelisation for controlled source electromagnetic applications | |
dc.type | Journal Article | |
dcterms.source.volume | 124 | |
dcterms.source.startPage | 91 | |
dcterms.source.endPage | 105 | |
dcterms.source.issn | 0926-9851 | |
dcterms.source.title | Journal of Applied Geophysics | |
curtin.department | Department of Exploration Geophysics | |
curtin.accessStatus | Fulltext not available |
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