耦合Nvidia/AMD两类GPU的格子玻尔兹曼模拟

利用图形处理单元(graphic processing unit, GPU)进行通用计算近年来得到关注, Nvidia和AMD公司已推出了各自的开发环境CUDA和ASC. 很多计算在GPU上的速度远高于目前的CPU. 格子玻尔兹曼方法(lattice Boltzmann method, LBM)作为一种网格上的粒子方法, 对流动模拟具有良好的内在并行性, 非常适合利用GPU进行大规模并行计算. 本文提出了一种耦合Nvidia和AMD的两类GPU完成LBM凹槽流模拟的算法, 对于两类GPU, 在LBM的D2Q9模型下分别设计了相应的算法和程序, 之后利用消息传递接口(message passing interface, MPI)协议通过多程序多数据流(multi-program multi-data, MPMD)模式使其能够联合计算, 以充分发挥混合GPU集群系统的性能. 通过GPU和CPU程序结果的比较, 证实了GPU计算的正确性和所能带来的显著的加速比, 为建设通用大规模GPU并行计算平台提供了重要参考.

Lattice Boltzmann simulation on Nvidia and AMD GPUs

General purpose computing on graphic processing units (GPUs) has received great attention re-cently. Both Nvidia and AMD have announced their own SDK, CUDA and ASC, respectively. Com-pared with CPUs, many applications can achieve high speed-up on GPUs. As a mesh-based particle method for flow simulation, lattice Boltzmann method (LBM) has perfect intrinsic parallelism that is very suitable for large-scale parallel computing. In this article, we put forward an algorithm for LB simulation of flow in grooved channel using the D2Q9 model, running on both Nvidia and AMD GPUs in the multi-program multi-data (MPMD) mode through message passing interface (MPI). The capability of hybrid GPU clusters can thus be fully utilized. The correctness and performance of the computation is analyzed through comparison with corresponding CPU implementation and significant speed-up of the GPU implementation has been demonstrated. The results provide valuable references to the establishment of GPU-based high performance computing (HPC) systems.