Computational & Technology Resources
an online resource for computational,
engineering & technology publications 

CivilComp Proceedings
ISSN 17593433 CCP: 80
PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by: B.H.V. Topping and C.A. Mota Soares
Paper 88
Parallel Implementation for Direct Numerical Simulation of Turbulent Flow using OpenMP H.V. Truong and J.C. Wells
Department of Civil and Enviromental Systems Engineering, Graduate School of Science and Engineering, Ritsumeikan University, Shiga, Japan H.V. Truong, J.C. Wells, "Parallel Implementation for Direct Numerical Simulation of Turbulent Flow using OpenMP", in B.H.V. Topping, C.A. Mota Soares, (Editors), "Proceedings of the Fourth International Conference on Engineering Computational Technology", CivilComp Press, Stirlingshire, UK, Paper 88, 2004. doi:10.4203/ccp.80.88
Keywords: numerical method, OpenMP, parallelization.
Summary
In this paper, we present parallelization methods for a direct numerical simulation
of a turbulent open channel flow using OpenMP which is a relatively new set of
compiler directives for sharedmemory computers [1,2]. OpenMP can create high
performance parallelized codes with significantly less coding time than the older
compiler directives MPI or PVM, which are based on a distributed memory model
and require explicit send/receive directives. From the sequential Direct Numerical
Simulation (DNS) program, we analyse the data relationship in order to propose
three parallelization models for the Poisson Solver and two parallelization models
for the remaining calculation parts. Results obtained on our 16 node PCCluster
illustrate the advantages and the drawbacks of each approach.
We perform DNS of turbulent flow in an open channel. The noslip boundary condition is applied at the wall and the zerostress condition is applied at the free surface. To keep the problem tractable, we follow the standard practice of applying periodic boundary conditions in the streamwise and spanwise directions. The temporal discretization of the incompressible NavierStokes equations is based on the fractional step method. Such "projection schemes" require solving a Poisson equation for pressure, which typically accounts for most of the computational time. Time discretization is a second order AdamsBashforth scheme for the convective terms. For the spatial discretization, a fourthorder central differencing scheme is adopted. Details of the numerical method can be found in [3]. We run OpenMP code compiled by Omni OpenMP on SCASH environment which then runs on a "PCcluster enabled OpenMP" [4]. To parallelize efficiently, it is crucial to distribute data among nodes in such a manner that minimizes remote data access during the calculation process. For nonPoisson solver parts, we propose two parallelization models. The first model was produced by distributing data and parallelizing intuitively, while for the second model, data distribution and parallelism are guided by solving the optimization problem associated with Data Mapping Parallelism Graph using 01 integer programming [5]. Experimental results show that the speedup of the second model is better than those of the first model and continuously improved when increasing the number of processor. For the Poisson solver part, we propose three parallelization models: static, dynamic and pipelined model. The Static Data Distribution model requires neither data redistribution nor data transposition while Dynamic Data Distribution requires data transposition in order to keep use of the sequential code on its subset data. In the Pipelined model, we implement a real parallel solver for septadiagonal linear systems to avoid explicit data transposition and redistribution. Comparing the speed up of these parallelization models, it appears that the Pipeline parallelization model behaves better than the Static parallelization model. The Dynamic parallelization model performs worst because it requires a lot of time for data transposition. References
purchase the fulltext of this paper (price £20)
go to the previous paper 
