论文标题
两相流的晶格玻尔兹曼方法的性能可移植性随相变
Performance portability of lattice Boltzmann methods for two-phase flows with phase change
论文作者
论文摘要
使用晶格Boltzmann方法（LBM）进行模拟一或两相流的数值代码被广泛编译并在图形过程单元上运行。但是，这些计算单元需要使用适合这些体系结构的低级语言（例如，用于GPU NVIDIA或OPENCL）来重写程序。在本文中，我们将精力集中在LBM的性能便携性上，即用高级抽象编写LB算法的可能性，同时在多种体系结构（例如Multicores X86，GPU Nvidia，arm，ARM等）上保持有效的效率。为了这样的目的，通过开发用C ++语言编写的lbm_saclay来实现LBM的实现，并与Kokkos库一起在高性能计算的背景下进行性能便携性。在本文中，LBM用于模拟与相变的两相流量问题的相位模型。数学模型由不可压缩的Navier-Stokes方程与保守的Allen-CAHN模型组成。该模型最初在文献中开发用于不良二元流体，以模拟在液体和气体之间的界面上发生的相变。为此，添加了一个涉及相场的时间导数的源项添加热方程。在相位方程中，添加源项以近似界面处的质量产量。进行了几项验证，以逐步检查完整模型的实现。最后，在CPU和GPU平台上比较了膜沸腾的物理问题的计算时间。
Numerical codes using the Lattice Boltzmann Methods (LBM) for simulating one- or two-phase flows are widely compiled and run on graphical process units. However, those computational units necessitate to re-write the program by using a low-level language which is suited to those architectures (e.g. CUDA for GPU NVIDIA or OpenCL). In this paper we focus our effort on the performance portability of LBM i.e. the possibility of writing LB algorithms with a high-level of abstraction while remaining efficient on a wide range of architectures such as multicores x86, GPU NVIDIA, ARM, and so on. For such a purpose, implementation of LBM is carried out by developing a unique code, LBM_saclay written in the C++ language, coupled with the Kokkos library for performance portability in the context of High Performance Computing. In this paper, the LBM is used to simulate a phase-field model for two-phase flow problems with phase change. The mathematical model is composed of the incompressible Navier-Stokes equations coupled with the conservative Allen-Cahn model. Initially developed in the literature for immiscible binary fluids, the model is extended here to simulate phase change occurring at the interface between liquid and gas. For that purpose, a heat equation is added with a source term involving the time derivative of the phase field. In the phase-field equation a source term is added to approximate the mass production rate at the interface. Several validations are carried out to check step-by-step the implementation of the full model. Finally, computational times are compared on CPU and GPU platforms for the physical problem of film boiling.
