Work

MonoAlg3D: Enabling Cardiac Electrophysiology Digital Twins with an Efficient Open Source Scalable Solver on GPU Clusters

Year: 2025

Type: preprint

Abstract: ABSTRACT Modelling and simulation are essential in biomedicine, and specifically in computational cardiology. Reliable, efficient and accurate solvers are critical. This study presents an open source, GPU-based cardiac electrophysiology solver for scalable digital twin multiscale simulations (M ono A lg 3D), incorporating conduction system calibration and performance optimization. The solver employs the monodomain equation coupled with the Purkinje network, solved via the finite volume method, featuring a GPU-based linear solver and concurrent simulation dispatch with MPI. We demonstrate a 10.94× speedup over a CPU-based solution and scalability by running 512 simulations on 128 compute nodes, completing all coarse-mesh simulations in less than 24 minutes and fine-mesh simulations in 303 minutes. We also demonstrate integration into a cardiac digital twin pipeline for personalisation based on clinical data. The proposed open source solver enhances computational efficiency and physiological fidelity, enabling large-scale, high-speed cardiac simulations. This work marks a significant step toward fast and scalable cardiac simulations on GPU architectures, with integration in a Digital Twin personalisation pipeline including the conduction system.

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.1101/2025.04.09.647733