Abstract
Immersed boundary-lattice Boltzmann method (IB-LBM) has become a popular method for studying fluid-structure interaction (FSI) problems. However, the performance issues of the IB-LBM have to be considered when simulating the practical problems. The Graphics Processing Units (GPUs) from NVIDIA offer a possible solution for the parallel computing, while the CPU is a multicore processor that can also improve the parallel performance. This paper proposes a parallel algorithm for IB-LBM on a CPU-GPU heterogeneous platform, in which the CPU not only controls the launch of the kernel function but also performs calculations. According to the relatively local calculation characteristics of IB-LBM and the features of the heterogeneous platform, the flow field is divided into two parts: GPU computing domain and CPU computing domain. CUDA and OpenMP are used for parallel computing on the two computing domains, respectively. Since the calculation time is less than the data transmission time, a buffer is set at the junction of two computational domains. The size of the buffer determines the number of the evolution of the flow field before the data exchange. Therefore, the number of communications can be reduced by increasing buffer size. The performance of the method was investigated and analyzed using the traditional metric MFLUPS. The new algorithm is applied to the computational simulation of red blood cells (RBCs) in Poiseuille flow and through a microchannel.
Highlights
In the immersed boundary-lattice Boltzmann method (IBLBM), the flow field is solved by the lattice Boltzmann method (LBM), and the interaction between the fluid and the immersed object is solved by the immersed boundary method (IB) [1]
Since Feng and Michaelides [2] first successfully applied the IB-LBM to simulate the motion of rigid particles, IB-LBM has become a popular method for studying the fluid-structure interaction (FSI) problems
Cheng et al [4] developed an IB-LBM for simulating a multiphase flow with solid particles and liquid drops. e IB-LBM is widely used to studying red blood cells (RBCs) flow in the blood, such as the interaction between plasma flow and RBCs movement [5] and the aggregation and deformation of red blood cells in an ultrasound field [6]
Summary
In the immersed boundary-lattice Boltzmann method (IBLBM), the flow field is solved by the lattice Boltzmann method (LBM), and the interaction between the fluid and the immersed object is solved by the immersed boundary method (IB) [1]. A new parallel algorithm for IB-LBM is proposed on CPU-GPU heterogeneous platform. The flow field is divided into CPU domains and GPU domains, which are calculated by the Compute Unified Device Architecture (CUDA) and OpenMP, respectively. Setting a buffer of proper size can reduce data communication and improve computing performance. As expected, this strategy greatly improved calculation efficiency without affecting the calculation accuracy of the IB-LBM.
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