The LU-SGS method of Yoon and Jameson is modified for the simulation of viscous flows on massively parallel computers. The resulting diagonal data- parallel lower-upper relaxation method (DP-LUR) is shown to have good convergence properties on many problems. However, the convergence rate decreases on the high cell aspect ratio grids required to simulate high Reynolds number flows. Therefore, the diagonal approximation is relaxed and a full matrix DP-LUR method is derived. It retains the data-parallel properties of the original method and reduces the sensitivity of the convergence rate to the grid aspect ratio. Both methods are implemented on the Thinking Machines CM-5, and a large fraction of the peak theoretical performance of the machine is obtained. The low memory use and high parallel efficiency of the methods make them attractive for large-scale simulation of viscous flows.
|Original language||English (US)|
|Number of pages||10|
|State||Published - Jan 1 1995|
|Event||12th Computational Fluid Dynamics Conference, 1995 - San Diego, United States|
Duration: Jun 19 1995 → Jun 22 1995
|Other||12th Computational Fluid Dynamics Conference, 1995|
|Period||6/19/95 → 6/22/95|