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GPU-accelerated Red Blood Cells Simulations with Transport Dissipative Particle Dynamics

机译:具有运输耗散粒子动力学的GPU加速的红细胞模拟

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摘要

Mesoscopic numerical simulations provide a unique approach for the quantification of the chemical influences on red blood cell functionalities. The transport Dissipative Particles Dynamics (tDPD) method can lead to such effective multiscale simulations due to its ability to simultaneously capture mesoscopic advection, diffusion, and reaction. In this paper, we present a GPU-accelerated red blood cell simulation package based on a tDPD adaptation of our red blood cell model, which can correctly recover the cell membrane viscosity, elasticity, bending stiffness, and cross-membrane chemical transport. The package essentially processes all computational workloads in parallel by GPU, and it incorporates multi-stream scheduling and non-blocking MPI communications to improve inter-node scalability. Our code is validated for accuracy and compared against the CPU counterpart for speed. Strong scaling and weak scaling are also presented to characterizes scalability. We observe a speedup of 10.1 on one GPU over all 16 cores within a single node, and a weak scaling efficiency of 91% across 256 nodes. The program enables quick-turnaround and high-throughput numerical simulations for investigating chemical-driven red blood cell phenomena and disorders.
机译:介观数值模拟为量化对红细胞功能的化学影响提供了一种独特的方法。传输耗散粒子动力学(tDPD)方法可以同时捕获介观对流,扩散和反应,因此可以导致这种有效的多尺度模拟。在本文中,我们基于tDPD对我们的红细胞模型的适应性,提出了GPU加速的红细胞模拟软件包,该软件包可以正确地恢复细胞膜的粘度,弹性,弯曲刚度和跨膜化学传输。该软件包实质上是由GPU并行处理所有计算工作负载的,并且合并了多流调度和无阻塞MPI通信,以提高节点间的可伸缩性。我们的代码经过了准确性验证,并与CPU副本进行了速度比较。还介绍了强缩放和弱缩放以表征可伸缩性。我们观察到单个节点上所有16个内核在一个GPU上的速度提高了10.1,在256个节点上的扩展效率仅为91%。该程序可进行快速周转和高通量的数值模拟,以研究化学驱动的红细胞现象和疾病。

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