SEG Technical Program Expanded Abstracts 2012 2012
DOI: 10.1190/segam2012-0727.1
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Comparison of iterative and direct solvers for 3D CSEM modeling

Abstract: Electromagnetic (EM) modeling in frequency domain requires solving large linear systems of equations. This can be accomplished using direct or iterative techniques. We compare the performance of the direct MUMPS and an iterative QMR solver for controlled-source EM modeling on distributed computing platforms. We first establish a conductivity value for air that lets the iterative solver converge while maintaining accuracy of subsurface EM fields, and then demonstrate the accuracy of the direct and iterative sol… Show more

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Cited by 7 publications
(7 citation statements)
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“…In all maps the relative error in the air is orders of magnitude larger than in the water or formation. Similar observations have been earlier reported by Grayver & Streich (2012). Fortunately, large errors in the air do not create a problem in most practical CSEM applications.…”
Section: Choice Of Blr Thresholdsupporting
confidence: 89%
“…In all maps the relative error in the air is orders of magnitude larger than in the water or formation. Similar observations have been earlier reported by Grayver & Streich (2012). Fortunately, large errors in the air do not create a problem in most practical CSEM applications.…”
Section: Choice Of Blr Thresholdsupporting
confidence: 89%
“…Computation time with an increasing number of right‐hand side vectors (i.e. sources) for a preconditioned BiCG iterative solver with a simultaneous solving strategy (Grayver and Streich ) and a direct solver (PARDISO) to solve the EM fields due to multiple sources for the inclined sheet model (Figure ). Numbers on each line represent the number of cores used.…”
Section: Resultsmentioning
confidence: 99%
“…After matrix factorisation, the number of right‐hand side vectors barely affects the total solution time in a direct solver, as shown in Figure , whereas an iterative solver typically calculates multiple right‐hand side vectors repeatedly. Figure also shows a simultaneous solving strategy (Grayver and Streich ), which was introduced to optimise the performance of preconditioned BiCG by utilising a set of cores to concurrently solve each divided sub‐problem. As mentioned in the above‐cited paper, the iterative solver combined with this strategy scales less favourably because the increasing number of concurrent processes decreases the amount of shared resources accessible to each core.…”
Section: Resultsmentioning
confidence: 99%
“…Direct solvers are generally more expensive than iterative solvers in terms of computation time and memory (Grayver and Streich, 2012). However, they also have advantages.…”
Section: Theorymentioning
confidence: 97%