An adaptive step size GPU ODE solver for simulating the electric cardiac activity

Simulation of electric cardiac activity requires the solution of a very large system of ordinary differential equations, which requires long computing times. Modern Graphic Processing Units (GPU) are powerful computing devices, which have been used to simulate electric cardiac activity. However, the numerical techniques applied were based on fixed time step. In this paper we describe an adaptive step size solver written for GPUs, and its application to simulate the behavior of a model of 300 atrial cells. Results presented in this study show that a robust adaptive step ODE solver can be implemented in a GPU. As expected, GPU implementations achieved much better performance than CPU solutions. In addition, the presented adaptive methodology achieved a computation time reduction up to a 25% versus a fix step implementation.