大规模并行人体循环系统模型

A. Randles, E. Draeger, T. Oppelstrup, L. Krauss, John A. Gunnels
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引用次数: 56

摘要

血流模拟对血管疾病患者的诊断和治疗的潜在影响是巨大的。全动脉树的增强模型可以提供对动脉高血压等疾病的深入了解,并使研究局部因素对整体血流动力学的影响成为可能。我们提出了一种新的、高度可扩展的晶格玻尔兹曼方法实现,该方法解决了多尺度耦合、有限内存容量和带宽以及复杂几何结构中鲁棒负载平衡等关键挑战。我们展示了在1,572,864个Blue Gene/Q核的全身动脉树中三维、高分辨率血流动力学模拟的强缩放。更快的计算流量在全动脉网络使前所未有的风险分层在逐次病人的基础上。为了实现这一目标,我们引入了计算上的进步,大大缩短了生物流体模拟的求解时间。
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Massively parallel models of the human circulatory system
The potential impact of blood flow simulations on the diagnosis and treatment of patients suffering from vascular disease is tremendous. Empowering models of the full arterial tree can provide insight into diseases such as arterial hypertension and enables the study of the influence of local factors on global hemodynamics. We present a new, highly scalable implementation of the lattice Boltzmann method which addresses key challenges such as multiscale coupling, limited memory capacity and bandwidth, and robust load balancing in complex geometries. We demonstrate the strong scaling of a three-dimensional, high-resolution simulation of hemodynamics in the systemic arterial tree on 1,572,864 cores of Blue Gene/Q. Faster calculation of flow in full arterial networks enables unprecedented risk stratification on a perpatient basis. In pursuit of this goal, we have introduced computational advances that significantly reduce time-to-solution for biofluidic simulations.
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