Finite difference simulations of the Navier-Stokes equations using parallel distributed computing

J. P. B. Angeli, A. Valli, N. C. Reis, A. D. Souza
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引用次数: 9

Abstract

We discuss the implementation of a numerical algorithm for simulating incompressible fluid flows based on the finite difference method and designed for parallel computing platforms with distributed-memory, particularly for clusters of workstations. The solution algorithm for the Navier-Stokes equations utilizes an explicit scheme for pressure and an implicit scheme for velocities, i. e., the velocity field at a new time step can be computed once the corresponding pressure is known. The parallel implementation is based on domain decomposition, where the original calculation domain is decomposed into several blocks, each of which given to a separate processing node. All nodes then execute computations in parallel, each node on its associated subdomain. The parallel computations include initialization, coefficient generation, linear solution on the subdomain, and inter-node communication. The exchange of information across the subdomains, or processors, is achieved using the message passing interface standard, MPI. The use of MPI ensures portability across different computing platforms ranging from massively parallel machines to clusters of workstations. The execution time and speed-up are evaluated through comparing the performance of different numbers of processors. The results indicate that the parallel code can significantly improve prediction capability and efficiency for large-scale simulations.
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应用并行分布式计算的Navier-Stokes方程的有限差分模拟
我们讨论了一种基于有限差分法的模拟不可压缩流体流动的数值算法的实现,该算法专为具有分布式内存的并行计算平台,特别是工作站集群而设计。Navier-Stokes方程的求解算法采用了压力的显式格式和速度的隐式格式,即一旦相应的压力已知,就可以计算出新的时间步长的速度场。并行实现基于域分解,将原始计算域分解为几个块,每个块分配给一个单独的处理节点。然后,所有节点并行执行计算,每个节点在其关联的子域上执行计算。并行计算包括初始化、系数生成、子域线性求解和节点间通信。跨子域或处理器的信息交换是使用消息传递接口标准MPI实现的。MPI的使用确保了从大规模并行机器到工作站集群的不同计算平台之间的可移植性。通过比较不同数量的处理器的性能来评估执行时间和加速。结果表明,并行代码可以显著提高大规模仿真的预测能力和效率。
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