Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells
The EMI model represents excitable cells in a more accurate manner than traditional homogenized models at the price of increased computational complexity. The increased complexity of solving the EMI model stems from a significant increase in the number of computational nodes and from the form of the...
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doaj-19377b282d984e0d97de2bbefe3899ae2021-01-13T05:42:41ZengFrontiers Media S.A.Frontiers in Physics2296-424X2021-01-01810.3389/fphy.2020.579461579461Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac CellsKaroline Horgmo Jæger0Kristian Gregorius Hustad1Xing Cai2Xing Cai3Aslak Tveito4Aslak Tveito5Simula Research Laboratory, Lysaker, NorwaySimula Research Laboratory, Lysaker, NorwaySimula Research Laboratory, Lysaker, NorwayDepartment of Informatics, University of Oslo, Oslo, NorwaySimula Research Laboratory, Lysaker, NorwayDepartment of Informatics, University of Oslo, Oslo, NorwayThe EMI model represents excitable cells in a more accurate manner than traditional homogenized models at the price of increased computational complexity. The increased complexity of solving the EMI model stems from a significant increase in the number of computational nodes and from the form of the linear systems that need to be solved. Here, we will show that the latter problem can be solved by careful use of operator splitting of the spatially coupled equations. By using this method, the linear systems can be broken into sub-problems that are of the classical type of linear, elliptic boundary value problems. Therefore, the vast collection of methods for solving linear, elliptic partial differential equations can be used. We demonstrate that this enables us to solve the systems using shared-memory parallel computers. The computing time scales perfectly with the number of physical cells. For a collection of 512 × 256 cells, we solved linear systems with about 2.5×108 unknows. Since the computational effort scales linearly with the number of physical cells, we believe that larger computers can be used to simulate millions of excitable cells and thus allow careful analysis of physiological systems of great importance.https://www.frontiersin.org/articles/10.3389/fphy.2020.579461/fullelectrophysiological modelcardiac conductioncell modelingfinite difference methodoperator splitting algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Karoline Horgmo Jæger Kristian Gregorius Hustad Xing Cai Xing Cai Aslak Tveito Aslak Tveito |
spellingShingle |
Karoline Horgmo Jæger Kristian Gregorius Hustad Xing Cai Xing Cai Aslak Tveito Aslak Tveito Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells Frontiers in Physics electrophysiological model cardiac conduction cell modeling finite difference method operator splitting algorithm |
author_facet |
Karoline Horgmo Jæger Kristian Gregorius Hustad Xing Cai Xing Cai Aslak Tveito Aslak Tveito |
author_sort |
Karoline Horgmo Jæger |
title |
Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells |
title_short |
Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells |
title_full |
Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells |
title_fullStr |
Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells |
title_full_unstemmed |
Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells |
title_sort |
efficient numerical solution of the emi model representing the extracellular space (e), cell membrane (m) and intracellular space (i) of a collection of cardiac cells |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Physics |
issn |
2296-424X |
publishDate |
2021-01-01 |
description |
The EMI model represents excitable cells in a more accurate manner than traditional homogenized models at the price of increased computational complexity. The increased complexity of solving the EMI model stems from a significant increase in the number of computational nodes and from the form of the linear systems that need to be solved. Here, we will show that the latter problem can be solved by careful use of operator splitting of the spatially coupled equations. By using this method, the linear systems can be broken into sub-problems that are of the classical type of linear, elliptic boundary value problems. Therefore, the vast collection of methods for solving linear, elliptic partial differential equations can be used. We demonstrate that this enables us to solve the systems using shared-memory parallel computers. The computing time scales perfectly with the number of physical cells. For a collection of 512 × 256 cells, we solved linear systems with about 2.5×108 unknows. Since the computational effort scales linearly with the number of physical cells, we believe that larger computers can be used to simulate millions of excitable cells and thus allow careful analysis of physiological systems of great importance. |
topic |
electrophysiological model cardiac conduction cell modeling finite difference method operator splitting algorithm |
url |
https://www.frontiersin.org/articles/10.3389/fphy.2020.579461/full |
work_keys_str_mv |
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