BeatBox - HPC Environment for Biophysically and Anatomically Realistic Cardiac Simulations

尽管经过了一个多世纪的研究，但人们对心律失常的触发机制知之甚少。即使是现代的实验方法也不能提供足够的时间和空间分辨率来追踪心脏组织样本中纤颤的发展，更不用说活体心脏了。人类遗传学的进步提供了关于某些基因对细胞活动的影响的信息，但没有解释导致纤颤发生的机制。因此，对于某些遗传性心脏病，首先出现的症状是死亡。对心脏组织中电活动的计算机模拟已经导致了我们对心脏颤动和心脏性猝死的理解，随着我们接近全心脏建模的最终目标，它们的影响预计将显著增加。由于每个细胞需要大量的方程和所需的巨大的空间和时间尺度，对动作电位在心脏组织中的传播进行建模在计算上是昂贵的。这个问题的复杂性包括对单个细胞通过组织的不均质性到整个心脏复杂几何形状的潜在离子电流的描述。心脏组织计算模型的及时运行越来越依赖于高性能计算(HPC)的有效使用。目前最先进的心脏模拟工具要么受到现代详细模型的可用性的限制，要么受到其易用性的限制。当前模型实现的多样性导致许多研究人员开发自己的特别软件，使他们无法有效地利用HPC的力量，也无法流畅地协作。因此，它阻碍了科学进步。这个项目的目标是开发一个用于生物物理学和解剖学上真实模拟心脏活动的高性能计算环境，一个可适应和可扩展的框架，研究人员可以利用它来利用高性能计算。

Despite over a century's study, the trigger mechanisms of cardiac arrhythmias are poorly understood. Even modern experimental methods do not provide sufficient temporal and spacial resolution to trace the development of fibrillation in samples of cardiac tissue, not to mention the heart in vivo. Advances in human genetics provide information on the impact of certain genes on cellular activity, but do not explain the resultant mechanisms by which fibrillation arises. Thus, for some genetic cardiac diseases, the first presenting symptom is death.Computer simulations of electrical activity in cardiac tissue have already led to developments in our understanding of heart fibrillation and sudden cardiac death and their impact is expected to increase significantly as we approach the ultimate goal of whole-heart modelling. Modelling the propagation of Action Potential through cardiac tissue is computationally expensive due to the huge number of equations per cell and the vast spacial and temporal scales required. The complexity of the problem encompasses the description of ionic currents underlying excitation of a single cell through the inhomogeneity of the tissue to the complex geometry of the whole heart. The timely running of computational models of cardiac tissue is increasingly dependent on the effective use of High Performance Computing (HPC). Current state of the art cardiac simulation tools are limited either by the availability of modern, detailed models, or by their ease of use. The miscellany of current model implementations leads many researchers to develop their own ad-hoc software, preventing them from both utilising the power of HPC effectively, and from collaborating fluidly. It is, therefore, impeding scientific progress.The aim of this project is to develop an HPC environment for biophysically and anatomically realistic simualtion of cardiac activity, an adaptable and extensible framework with which High Performance Computing may be harnessed by researchers.