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Simulations of Cardiac Electrophysiology Combining GPU and Adaptive Mesh Refinement Algorithms

机译:结合GPU和自适应网格细化算法的心脏电生理模拟

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Computer models have become valuable tools for the study and comprehension of the complex phenomena of cardiac electrophysiology. However, the high complexity of the biophysical processes translates into complex mathematical and computational models. In this paper we evaluate a hybrid multicore and graphics processing unit numerical algorithm based on mesh adaptivity and on the finite volume method to cope with the complexity and to accelerate these simulations. This is a very attractive approach since the electrical wavefront corresponds to only a small fraction of the cardiac tissue. Usually, the numerical solution of the partial differential equations that model the phenomenon requires very fine spatial discretization to follow the wavefront, which is approximately 0.2 mm. The use of uniform meshes leads to high computational cost as it requires a large number of mesh points. In this sense, the tests reported in this work show that simulations of three-dimensional models of cardiac tissue have been accelerated by more than 626 times using the adaptive mesh algorithm together with its parallelization, with no significant loss in accuracy.
机译:计算机模型已成为研究和理解心脏电生理学复杂现象的宝贵工具。然而,生物物理过程的高度复杂性转化为复杂的数学和计算模型。在本文中,我们评估了一种基于网格自适应性和有限体积方法的混合多核和图形处理单元数值算法,以应对复杂性并加速这些仿真。这是一种非常有吸引力的方法,因为电波前仅对应于心脏组织的一小部分。通常,模拟该现象的偏微分方程的数值解需要非常精细的空间离散化才能跟随波前,波前近似为0.2 mm。均匀网格的使用导致较高的计算成本,因为它需要大量的网格点。从这个意义上讲,这项工作中报告的测试表明,使用自适应网格算法及其并行化功能,可使心脏组织三维模型的仿真速度提高了626倍以上,而准确性没有明显下降。

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