Lattice Boltzmann simulations on GPUs with ESPResSo
Lattice Boltzmann simulations on GPUs with ESPResSo
复制标题
使用 ESPResSo 在 GPU 上进行格子玻尔兹曼模拟
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
A. Arnold
中科院分区：
文献类型：
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作者：
D. Roehm;A. Arnold
对于溶液中大分子的动力学，由溶剂分子介导的流体动力学相互作用通常起着重要的作用，尽管人们对溶剂本身的动力学不感兴趣。因此，在计算机模拟中，用晶格流体代替溶剂可以节省大量的计算机时间。大分子通过分子动力学（MD）传播，而流体则由波动的晶格-玻尔兹曼（LB）方程控制。我们提出了一个波动LB实现一个单一的图形卡（GPU）耦合到MD模拟运行在传统的处理器（CPU）。特别强调的是组合代码的优化。在我们的实现中，LB更新与CPU上的力计算并行执行，这通常完全隐藏了LB的额外计算成本。与我们在传统四核CPU上的并行LB实现相比，GPU LB的速度快了50倍，并且我们表明，具有Infiniband互连的整个商品集群在强大的扩展性方面无法优于单个GPU。所提供的代码是开源仿真包ESPResSo（http：//www.example.com）的一部分。www.espressomd.org
For the dynamics of macromolecules in solution, hydrodynamic interactions mediated by the solvent molecules often play an important role, although one is not interested in the dynamics of the solvent itself. In computer simulations one can therefore save a large amount of computer time by replacing the solvent with a lattice fluid. The macromolecules are propagated by Molecular Dynamics (MD), while the fluid is governed by the fluctuating Lattice-Boltzmann (LB) equation. We present a fluctuating LB implementation for a single graphics card (GPU) coupled to a MD simulation running on conventional processors (CPUs). Particular emphasis lies on the optimization of the combined code. In our implementation, the LB update is performed in parallel with the force calculation on the CPU, which often completely hides the additional computational cost of the LB. Compared to our parallel LB implementation on a conventional quad-core CPU, the GPU LB is 50 times faster, and we show that a whole commodity cluster with Infiniband interconnnect cannot outperform a single GPU in strong scaling. The presented code is part of the open source simulation package ESPResSo (http://www.espressomd.org).