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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2510.12011 |
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| _version_ | 1866911208821489664 |
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| author | Zhou, Bei Balmus, Maximilian Corrado, Cesare Cicci, Ludovica Qian, Shuang Niederer, Steven A. |
| author_facet | Zhou, Bei Balmus, Maximilian Corrado, Cesare Cicci, Ludovica Qian, Shuang Niederer, Steven A. |
| contents | Cardiac electrophysiology (CEP) simulations are increasingly used for understanding cardiac arrhythmias and guiding clinical decisions. However, these simulations typically require high-performance computing resources with numerous CPU cores, which are often inaccessible to many research groups and clinicians. To address this, we present TorchCor, a high-performance Python library for CEP simulations using the finite element method on general-purpose GPUs. Built on PyTorch, TorchCor significantly accelerates CEP simulations, particularly for large 3D meshes. The accuracy of the solver is verified against manufactured analytical solutions and the $N$-version benchmark problem. TorchCor is freely available for both academic and commercial use without restrictions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_12011 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TorchCor: High-Performance Cardiac Electrophysiology Simulations with the Finite Element Method on GPUs Zhou, Bei Balmus, Maximilian Corrado, Cesare Cicci, Ludovica Qian, Shuang Niederer, Steven A. Software Engineering Cardiac electrophysiology (CEP) simulations are increasingly used for understanding cardiac arrhythmias and guiding clinical decisions. However, these simulations typically require high-performance computing resources with numerous CPU cores, which are often inaccessible to many research groups and clinicians. To address this, we present TorchCor, a high-performance Python library for CEP simulations using the finite element method on general-purpose GPUs. Built on PyTorch, TorchCor significantly accelerates CEP simulations, particularly for large 3D meshes. The accuracy of the solver is verified against manufactured analytical solutions and the $N$-version benchmark problem. TorchCor is freely available for both academic and commercial use without restrictions. |
| title | TorchCor: High-Performance Cardiac Electrophysiology Simulations with the Finite Element Method on GPUs |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2510.12011 |