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Related Experiment Video

Updated: Jun 6, 2026

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology

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

Ronan M Amorim¹, Bernardo M Rocha, Fernando O Campos

¹Department of Computer Science, Federal University of Juiz de Fora, Brazil. ronanrmo@gmail.com

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 25, 2010

Summary

This study introduces a tool for simulating cardiac electrical activity, enabling faster computational modeling. GPU-accelerated solvers achieved significant speedups, aiding cardiac research and drug development.

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Area of Science:

Computational biology
Biophysics
Medical imaging

Background:

Cardiac electrical activity modeling is crucial for understanding heart function, disease diagnosis, and drug testing.
Simulating cardiac bioelectric activity presents computational challenges due to its multi-scale nature and complex implementation.

Purpose of the Study:

To present a tool for prototyping ordinary differential equations (ODEs) in cardiac modeling.
To enable automatic generation of high-performance solvers optimized for Graphics Processing Units (GPUs).

Main Methods:

Developed a prototyping tool for ODEs in cardiac modeling.
Implemented automatic generation of high-performance solvers for GPU hardware.
Evaluated solver performance using four distinct cardiac myocyte models.

Main Results:

The GPU-accelerated solvers demonstrated significant performance improvements.
Speedups ranged from 75 to 290 times faster compared to Central Processing Unit (CPU) versions.
The tool facilitates efficient simulation of cardiac electrical activity.

Conclusions:

The developed tool and GPU solvers offer a powerful solution for accelerating cardiac modeling simulations.
This advancement can enhance the understanding of cardiac biophysics and support the development of new diagnostic techniques and drug testing platforms.