Li Qin, Zhu Xin, Chen Wenxi
Graduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, Fukushima, Japan.
Department of AI Technology Development, M&D Data Science Center, Tokyo Medical and Dental University, Chiyoda 101-0062, Tokyo, Japan.
Biomedicines. 2024 Sep 19;12(9):2126. doi: 10.3390/biomedicines12092126.
The simulation of electrophysiological cardiac models plays an important role in facilitating the investigation of cardiac behavior under various conditions. However, these simulations often require a lot of computational resources.
To address this challenge, this study introduced a method for speeding up three-dimensional cardiac simulations using GPU parallelization. A series of optimizations was introduced, encompassing various aspects such as data storage, algorithmic enhancements, and data transfer.
The experimental results reveal that the optimized GPU parallel simulations achieve an approximate 50-fold acceleration compared with their CPU serial program.
This investigation substantiates the considerable potential of GPUs in advancing the field of cardiac electrophysiology simulations.
心脏电生理模型的模拟在促进对各种条件下心脏行为的研究中起着重要作用。然而，这些模拟通常需要大量的计算资源。
为应对这一挑战，本研究引入了一种使用GPU并行化来加速三维心脏模拟的方法。引入了一系列优化措施，涵盖数据存储、算法改进和数据传输等各个方面。
实验结果表明，优化后的GPU并行模拟与CPU串行程序相比，实现了约50倍的加速。
本研究证实了GPU在推动心脏电生理模拟领域发展方面具有巨大潜力。
