Automatic code generation for solvers of cardiac cellular membrane dynamics in GPUs

The modeling of the electrical activity of the heart is of great medical and scientific interest, as it provides a way to get a better understanding of the related biophysical phenomena, allows the development of new techniques for diagnoses and serves as a platform for drug tests. However, due to the multi-scale nature of the underlying processes, the simulations of the cardiac bioelectric activity are still a computational challenge. In addition to that, the implementation of these computer models is a time consuming and error prone process. In this work we present a tool for prototyping ordinary differential equations (ODEs) in the area of cardiac modeling that aim to provide the automatic generation of high performance solvers tailored to the new hardware architecture of the graphic processing units (GPUs). The performance of these automatic solvers was evaluated using four different cardiac myocyte models. The GPU version of the solvers were between 75 and 290 times faster than the CPU versions.