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首页> 外文期刊>Procedia Computer Science >Accelerating Solid-fluid Interaction using Lattice-boltzmann and Immersed Boundary Coupled Simulations on Heterogeneous Platforms
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Accelerating Solid-fluid Interaction using Lattice-boltzmann and Immersed Boundary Coupled Simulations on Heterogeneous Platforms

机译：在异质平台上使用Lattice-boltzmann和沉浸边界耦合模拟来加速固液相互作用

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We propose a numerical approach based on the Lattice-Boltzmann (LBM) and Immersed Boundary (IB) methods to tackle the problem of the interaction of solids with an incompressible fluid flow. The proposed method uses a Cartesian uniform grid that incorporates both the fluid and the solid domain. This is a very optimum and novel method to solve this problem and is a growing research topic in Computational Fluid Dynamics. We explain in detail the parallelization of the whole method on both GPUs and an heterogeneous GPU-Multicore platform and describe different optimizations, focusing on memory management and CPU-GPU communication. Our performance evaluation consists of a series of numerical experiments that simulate situations of industrial and research interest. Based on these tests, we have shown that the baseline LBM implementation achieves satisfactory results on GPUs. Unfortunately, when coupling LBM and IB methods on GPUs, the overheads of IB degrade the overall performance. As an alternative we have explored an heterogeneous implementation that is able to hide such overheads and allows us to exploit both Multicore and GPU resources in a cooperative way.
机译：我们提出了一种基于Lattice-Boltzmann（LBM）和浸入边界（IB）方法的数值方法，以解决固体与不可压缩流体相互作用的问题。所提出的方法使用笛卡尔均匀网格，该网格合并了流体域和固体域。这是解决此问题的一种非常理想且新颖的方法，并且是计算流体力学中一个正在发展的研究主题。我们将详细解释整个方法在GPU和异构GPU-Multicore平台上的并行化，并描述不同的优化方法，重点是内存管理和CPU-GPU通信。我们的性能评估包含一系列数值实验，这些数值模拟了工业和研究兴趣的情况。基于这些测试，我们已经表明，基线LBM实现在GPU上可获得令人满意的结果。不幸的是，当在GPU上结合LBM和IB方法时，IB的开销降低了整体性能。作为替代方案，我们探索了一种异构实现，该实现能够隐藏此类开销并允许我们以协作方式利用多核和GPU资源。

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