Multi-cluster, mixed-mode computational modeling of human head conductivity

Authors:
Adnan Salman;Sergei Turovets;Allen D. Malony;Vasily Volkov
Affiliations:
NeuroInformatics Center, University of Oregon, Eugene, OR;NeuroInformatics Center, University of Oregon, Eugene, OR;NeuroInformatics Center, University of Oregon, Eugene, OR;Institute of Mathematics, Academy of Sciences, Minsk, Belarus
Venue:
IWOMP'05/IWOMP'06 Proceedings of the 2005 and 2006 international conference on OpenMP shared memory parallel programming
Year:
2005

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Abstract

A multi-cluster computational environment with mixed-mode (MPI + OpenMP) parallelism for estimation of unknown regional electrical conductivities of the human head, based on realistic geometry from segmented MRI up to 2563 voxels resolution, is described. A finite difference multi-component alternating direction implicit (ADI) algorithm, parallelized using OpenMP, is used to solve the forward problem calculation describing the electrical field distribution throughout the head given known electrical sources. A simplex search in the multi-dimensional parameter space of tissue conductivities is conducted in parallel across a distributed system of heterogeneous computational resources. The theoretical and computational formulation of the problem is presented. Results from test studies based on the synthetic data are provided, comparing retrieved conductivities to known solutions from simulation. Performance statistics are also given showing both the scaling of the forward problem and the performance dynamics of the distributed search.