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.
翻译:心脏电生理模拟在理解心律失常和指导临床决策中的应用日益广泛。然而,这类模拟通常需要配备大量CPU核心的高性能计算资源,这对许多研究团队和临床医生而言往往难以获取。为此,我们提出了TorchCor——一个基于通用GPU、采用有限元方法进行心脏电生理模拟的高性能Python库。TorchCor基于PyTorch构建,能显著加速心脏电生理模拟,尤其针对大规模三维网格。通过构造解析解和$N$-版本基准问题的验证,该求解器的准确性得到了确认。TorchCor面向学术和商业用途免费开放,且无使用限制。