Amorim Ronan M, Rocha Bernardo M, Campos Fernando O, Dos Santos Rodrigo W
Department of Computer Science, Federal University of Juiz de Fora, Brazil.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:2666-9. doi: 10.1109/IEMBS.2010.5626620.
The modeling of the electrical activity of the heart is of great medical and scientific interest, as it provides a way to get a better understanding of the related biophysical phenomena, allows the development of new techniques for diagnoses and serves as a platform for drug tests. However, due to the multi-scale nature of the underlying processes, the simulations of the cardiac bioelectric activity are still a computational challenge. In addition to that, the implementation of these computer models is a time consuming and error prone process. In this work we present a tool for prototyping ordinary differential equations (ODEs) in the area of cardiac modeling that aim to provide the automatic generation of high performance solvers tailored to the new hardware architecture of the graphic processing units (GPUs). The performance of these automatic solvers was evaluated using four different cardiac myocyte models. The GPU version of the solvers were between 75 and 290 times faster than the CPU versions.
心脏电活动的建模具有重大的医学和科学意义,因为它提供了一种更好地理解相关生物物理现象的方法,有助于开发新的诊断技术,并作为药物测试的平台。然而,由于潜在过程的多尺度性质,心脏生物电活动的模拟仍然是一个计算挑战。除此之外,这些计算机模型的实现是一个耗时且容易出错的过程。在这项工作中,我们展示了一种用于心脏建模领域常微分方程(ODE)原型设计的工具,旨在自动生成针对图形处理单元(GPU)新硬件架构量身定制的高性能求解器。使用四种不同的心肌细胞模型对这些自动求解器的性能进行了评估。求解器的GPU版本比CPU版本快75到290倍。