Toward real-time simulation of cardiac dynamics

We show that through careful and model-specific optimizations of their GPU implementations, simulations of realistic, detailed cardiac-cell models now can be performed in 2D and 3D in times that are close to real time using a desktop computer. Previously, large-scale simulations of detailed mathematical models of cardiac cells were possible only using supercomputers. In our study, we consider five different models of cardiac electrophysiology that span a broad range of computational complexity: the two-variable Karma model, the four-variable Bueno-Orovio-Cherry-Fenton model, the eight-variable Beeler-Reuter model, the 19-variable Ten Tusscher-Panfilov model, and the 67-variable Iyer-Mazhari-Winslow model. For each of these models, we treat both their single- and double-precision versions and demonstrate linear or even sub-linear growth in simulation times with an increase in the size of the grid used to model cardiac tissue. We also show that our GPU implementations of these models can increase simulation speeds to near real-time for simulations of complex spatial patterns indicative of cardiac arrhythmic disorders, including spiral waves and spiral wave breakup. The achievement of real-time applications without the need for supercomputers may, in the near term, facilitate the adoption of modeling-based clinical diagnostics and treatment planning, including patient-specific electrophysiological studies.