An inner-outer subcycling algorithm for parallel cardiac electrophysiology simulations

Area of Science:

• Computational biology
• Biophysics
• Numerical analysis

Background:

• Cardiac electrophysiological simulations are crucial for understanding heart function.
• Current simulation methods face efficiency challenges, particularly with complex ionic models.
• Parallel computing is essential for large-scale cardiac simulations.

Purpose of the Study:

• To introduce a novel subcycling time integration algorithm for cardiac monodomain simulations.
• To improve the computational efficiency of simulating cardiac electrical activity.
• To reduce simulation turnaround time for both idealized and patient-specific cardiac geometries.

Main Methods:

• Developed and implemented a subcycling time integration algorithm tailored for ionic models within the monodomain equations.
• Utilized parallel computing architectures to assess the scalability of the proposed algorithm.
• Conducted numerical experiments on idealized and patient-specific cardiac geometries.

Main Results:

• The proposed subcycling algorithm accurately simulates cardiac electrophysiology.
• The method demonstrates close to linear parallel scalability on systems with over 1000 processor cores.
• Significant reduction in simulation time for cardiac electrical function was achieved.

Conclusions:

• The novel subcycling algorithm offers an efficient approach for cardiac electrophysiological simulations.
• This advancement can accelerate the use of computational modeling in clinical settings for personalized medicine.
• Reduced simulation times facilitate model tuning for matching clinical measurements.