McCullough J W S, Richardson R A, Patronis A, Halver R, Marshall R, Ruefenacht M, Wylie B J N, Odaker T, Wiedemann M, Lloyd B, Neufeld E, Sutmann G, Skjellum A, Kranzlmüller D, Coveney P V
Centre for Computational Science, Department of Chemistry, University College London, London, UK.
Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.
Interface Focus. 2021 Feb 6;11(1):20190119. doi: 10.1098/rsfs.2019.0119. Epub 2020 Dec 11.
Many scientific and medical researchers are working towards the creation of a virtual human-a personalized digital copy of an individual-that will assist in a patient's diagnosis, treatment and recovery. The complex nature of living systems means that the development of this remains a major challenge. We describe progress in enabling the HemeLB lattice Boltzmann code to simulate 3D macroscopic blood flow on a full human scale. Significant developments in memory management and load balancing allow near linear scaling performance of the code on hundreds of thousands of computer cores. Integral to the construction of a virtual human, we also outline the implementation of a self-coupling strategy for HemeLB. This allows simultaneous simulation of arterial and venous vascular trees based on human-specific geometries.
许多科学和医学研究人员正在努力创建虚拟人——个体的个性化数字副本，以辅助患者的诊断、治疗和康复。生命系统的复杂性意味着其开发仍然是一项重大挑战。我们描述了使HemeLB格子玻尔兹曼代码能够在完整人体尺度上模拟三维宏观血流方面取得的进展。内存管理和负载平衡方面的重大进展使该代码在数十万计算机核心上具有近乎线性的扩展性能。作为构建虚拟人的一个组成部分，我们还概述了HemeLB自耦合策略的实现。这允许基于特定于人的几何形状同时模拟动脉和静脉血管树。
