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首页> 外文期刊>Computer physics communications >New multi-GPU implementation for smoothed particle hydrodynamics on heterogeneous clusters
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New multi-GPU implementation for smoothed particle hydrodynamics on heterogeneous clusters

机译:新的多GPU实现可用于异构集群上的平滑粒子流体动力学

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A massively parallel SPH scheme using heterogeneous clusters of Central Processing Units (CPUs) and Graphics Processing Units (GPUs) has been developed. The new implementation originates from the single-GPU DualSPHysics code previously demonstrated to be powerful, stable and accurate. A combination of different parallel programming languages is combined to exploit not only one device (CPU or GPU) but also the combination of different machines. Communication among devices uses an improved Message Passing Interface (MPI) implementation which addresses some of the well-known drawbacks of MPI such as including a dynamic load balancing and overlapping data communications and computation tasks. The efficiency and scalability (strong and weak scaling) obtained with the new DualSPHysics code are analysed for different numbers of particles and different number of GPUs. Last, an application with more than 10~ particles is presented to show the capability of the code to handle simulations that otherwise require large CPU clusters or supercomputers.
机译:已经开发出使用中央处理单元(CPU)和图形处理单元(GPU)的异构集群的大规模并行SPH方案。新的实现源自先前展示的功能强大,稳定且准确的单GPU DualSPHysics代码。结合使用不同并行编程语言的组合,不仅可以利用一个设备(CPU或GPU),还可以利用不同机器的组合。设备之间的通信使用改进的消息传递接口(MPI)实现,该实现解决了MPI的一些众所周知的缺点,例如包括动态负载平衡以及重叠的数据通信和计算任务。针对不同数量的粒子和不同数量的GPU,分析了使用新的DualSPHysics代码获得的效率和可伸缩性(强缩放和弱缩放)。最后,提出了一个包含10个以上粒子的应用程序,以显示代码处理模拟的能力,这些模拟否则需要大型CPU集群或超级计算机。

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