Parallelization of lattice Boltzmann software for execution on multi-GPU clusters with application to the simulation of blood flow through human arteries

T. Djukić, N. Filipovic
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Abstract

It is important to consider the blood flow pattern when planning vascular interventions of atherosclerotic plaques. Large scale computer modeling can be very helpful in this case. The software presented in this paper numerically models blood flow through patient-specific blood vessels. Lattice Boltzmann method was used to simulate blood flow. The principles of GPU (Graphics Processing Unit) programming are applied during implementation and the developed software was parallelized using the CUDA (Compute Unified Device Architecture) and optimized to run on a multi-GPU cluster using the MPI approach. Using the multi-GPU infrastructure, numerical simulations can utilize larger amount of memory resources for the computation, making the level of reality of the models an order of magnitude higher. Execution of the presented software enables fast and reliable case-studies and parametric analyses useful for medical decision-making. The presented software can give medical professionals fast quantitative information about fluid flow in diseased arteries and assist them in selecting the most appropriate treatment.
网格玻尔兹曼软件在多gpu集群上执行的并行化及其在人体动脉血流模拟中的应用
在规划动脉粥样硬化斑块的血管干预时,考虑血流模式是很重要的。在这种情况下,大规模的计算机建模非常有帮助。该软件在本文中提出的数值模拟血液流动通过患者特定的血管。采用点阵玻尔兹曼方法模拟血流。在实现过程中应用了GPU(图形处理单元)编程原理,开发的软件使用CUDA(计算统一设备架构)并行化,并使用MPI方法优化以在多GPU集群上运行。利用多gpu架构,数值模拟可以利用更大的内存资源进行计算,使模型的真实程度提高了一个数量级。所提出的软件的执行使快速可靠的案例研究和参数分析对医疗决策有用。所介绍的软件可以为医疗专业人员提供有关病变动脉中流体流动的快速定量信息,并帮助他们选择最合适的治疗方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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