FRACTAL ANALYSIS OF HIGH-PERFORMANCE PARALLEL ARCHITECTURES FOR NONLINEAR CARDIAC MODELS

Abstract

In this study, we develop parallel techniques for solving nonlinear equations arising in cardiac modeling, which are often computationally challenging due to their complexity and sensitivity. The proposed parallel scheme achieves a convergence order of 3 phi + 3, where phi is an element of (0, 1] is a fractional parameter. Several cardiac models are employed to evaluate the efficiency, accuracy, and stability of the method. A detailed fractal analysis of the developed schemes is also presented, providing deeper insights into their dynamical behavior. Numerical results demonstrate that the proposed approach outperforms classical methods in terms of convergence rate, residual error, and stability. This work highlights the potential of fractional parallel solvers to more effectively capture complex cardiac dynamics and contribute to advanced biomedical computations.