Simulation of clinical electrophysiology in 3D human atria: a high‐performance computing and high‐performance visualization application

Atrial fibrillation (AF) is a common cardiac disease of genuine clinical concern with high rates of morbidity, leading to major personal and National Health Service costs. Computer modelling of AF using biophysically detailed cellular models with realistic 3D anatomical geometry allows investigation of the underlying ionic mechanisms in far more detail than with experimental physiology. We have developed a 3D virtual human atrium that combines detailed cellular electrophysiology including ion channel kinetics and homeostasis of ionic concentrations with anatomical details. The segmented anatomical structure and the multivariable nature of the system make the 3D simulations of AF computationally large and intensive. Computational demands are such that a full problem‐solving environment requires access to resources of high‐performance computing (HPC), high‐performance visualization (HPV), remote data repositories and backend infrastructure. This is a classic example of e Science and Grid‐enabled computing. This study was carried out using multiple processor shared memory systems and massively parallel distributed memory systems. With the envisaged increase in anatomical and molecular detail in our cardiac models the requirement for HPC resources is predicted to increase many fold (∼ 1–10 teraflops). Distributed computing is essential, both through massively parallel systems (a single supercomputer) and multiple parallel systems made accessible through the Grid. Analysis and interpretation of results are enhanced by HPV, which in itself is a large data computing aspect of cardiac modelling.