论文标题
基于GPU的基于各向异性，异质酸扩散的Gatenby-Gawlinski模型的平行模拟
GPU-based parallel simulations of the Gatenby-Gawlinski model with anisotropic, heterogeneous acid diffusion
论文作者
论文摘要
我们介绍了用于酸介导的肿瘤侵袭的Gatenby-Gawlinski模型的变体，该模型是乳酸在周围健康组织中的各向异性和异质扩散。通过在交错的笛卡尔网格上采用有限的体积方案，对二维数据进行数值模拟，并考虑了通过现代CUDA GPU技术的平行实现。这种方法的有效性是通过重现生物学相关的结果来证明的，例如形成传播方面以及正常细胞和癌细胞之间的间质差距的出现，这是由降低pH的策略驱动的，并显着取决于扩散速率。通过对串行和并行执行协议的性能分析，我们推断出利用高度平行的基于GPU的计算设备可以在定期形状的网格上恢复有限的体积方案，并与显式的时间离散化，以使复杂的应用程序以使其对入侵过程的接口扩散问题进行复杂的应用程序。
We introduce a variant of the Gatenby-Gawlinski model for acid-mediated tumor invasion, accounting for anisotropic and heterogeneous diffusion of the lactic acid across the surrounding healthy tissues. Numerical simulations are performed for two-dimensional data by employing finite volume schemes on staggered Cartesian grids, and parallel implementation through the modern CUDA GPUs technology is considered. The effectiveness of such approach is proven by reproducing biologically relevant results like the formation of propagating fronts and the emergence of an interstitial gap between normal and cancerous cells, which is driven by the pH lowering strategy and depends significantly on the diffusion rates. By means of a performance analysis of the serial and parallel execution protocols, we infer that exploiting highly parallel GPU-based computing devices allows to rehabilitate finite volume schemes on regularly-shaped meshes, together with explicit time discretization, for complex applications to interface diffusion problems of invasive processes.
