An HPC-Based Approach to Study Living System Computational Model Parameter Dependency

Abstract

High performance computing (HPC) allows one to run in parallel large amount of independent numerical experiments for computationally intensive simulations of a complex system. Results of such experiments can be used to derive dependencies between functional characteristics of simulated system and parameters of the computational model. In this paper, we implemented this HPC approach with using a computational model of the electrical activity in the left ventricle of human heart. To illustrate possibilities of the approach, we analyzed dependencies of electrophysiological characteristics of the left ventricle on the parameters of its geometry. Particularly, we identified a dependence of the dynamics of activated myocardium part during excitation on the model parameters of the myocardial fiber orientation in the ventricular wall.