A Fast Parallelized Computational Approach Based on Sparse LU Factorization for Predictions of Spatial and Time-Dependent Currents and Voltages in Full-Body Biomodels

Realistic and accurate numerical simulations of electrostimulation of tissues and full-body biomodels have been developed and implemented. Typically, whole-body systems are very complex and consist of a multitude of tissues, organs, and subcomponents with diverse properties. From an electrical stand...

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Bibliographic Details
Published in:IEEE transactions on plasma science 2006-08, Vol.34 (4), p.1431-1440
Main Authors: Mishra, A., Joshi, R.P., Schoenbach, K.H., Clark, C.D.
Format: Article
Language:English
Subjects:
Algorithms
Animal structures
Clustering algorithms
Computation
Computer simulation
Concurrent computing
Conductivity
Demand
Distributed computing
Distributed currents
Electric potential
Electricity
Format
Grid computing
LU decomposition
Mathematical models
Numerical analysis
Numerical simulation
parallel computing
Permittivity
Resistivity
Spatial resolution
tissue modeling
Tissues
Voltage
whole body
Zoology
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Summary:Realistic and accurate numerical simulations of electrostimulation of tissues and full-body biomodels have been developed and implemented. Typically, whole-body systems are very complex and consist of a multitude of tissues, organs, and subcomponents with diverse properties. From an electrical standpoint, these can be characterized in terms of separate conductivities and permittivities. Accuracy demands good spatial resolution; thus, the overall tissue/animal models need to be discretized into a fine-grained mesh. This can lead to a large number of grid points (especially for a three-dimensional entity) and can place prohibitive requirements of memory storage and execution times on computing machines. Here, the authors include a simple yet fast and efficient numerical implementation. It is based on LU decomposition for execution on a cluster of computers running in parallel with distributed storage of the data in a sparse format. In this paper, the details of electrical tissue representation, the fast algorithm, the relevant biomodels, and specific applications to whole-animal studies of electrostimulation are discussed
ISSN:0093-3813
1939-9375
DOI:10.1109/TPS.2006.876485