Hostname: page-component-77c89778f8-gq7q9 Total loading time: 0 Render date: 2024-07-19T21:51:18.405Z Has data issue: false hasContentIssue false

Demonstration of cluster computing for three-dimensional CFD simulations

Published online by Cambridge University Press:  04 July 2016

W. McMillan
Affiliation:
Aerospace Engineering DepartmentUniversity of Glasgow, Glasgow, UK
M. Woodgate
Affiliation:
Aerospace Engineering DepartmentUniversity of Glasgow, Glasgow, UK
B. E. Richards
Affiliation:
Aerospace Engineering DepartmentUniversity of Glasgow, Glasgow, UK
B. J. Gribben
Affiliation:
Aerospace Engineering DepartmentUniversity of Glasgow, Glasgow, UK
K. J. Badcock
Affiliation:
Aerospace Engineering DepartmentUniversity of Glasgow, Glasgow, UK
C. A. Masson
Affiliation:
Aerospace Engineering DepartmentUniversity of Glasgow, Glasgow, UK
F. Cantariti
Affiliation:
Aerospace Engineering DepartmentUniversity of Glasgow, Glasgow, UK

Abstract

Motivated by a lack of sufficient local and national computing facilities for computational fluid dynamics simulations, the Affordable Systems Computing Unit (ASCU) was established to investigate low cost alternatives. The options considered have all involved cluster computing, a term which refers to the grouping of a number of components into a managed system capable of running both serial and parallel applications. The present work aims to demonstrate the utility of commodity processors for dedicated batch processing. The performance of the cluster has proved to be extremely cost effective, enabling large three dimensional flow simulations on a computer costing less than £25k sterling at current market prices. The experience gained on this system in terms of single node performance, message passing and parallel performance will be discussed. In particular, comparisons with the performance of other systems will be made. Several medium-large scale CFD simulations performed using the new cluster will be presented to demonstrate the potential of commodity processor based parallel computers for aerodynamic simulation.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 1999 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Sunderam, V., Giest, G., , Donoarra, J., and Manchek, R., PVM: A framework for parallel distributed computing, J Concurrency: Practice and Experience, 1990, 2, pp 315339.Google Scholar
2. MPI Forum, MPI: A message-passing interface standard, J Supercomp App, 1994, 8.Google Scholar
3. Mucci, P.J. and London, K. The MPBench report, University of Tennessee, Knoxville, Tech Report ut-cs-98-394, 1998.Google Scholar
4. Dubuc, L., Cantariti, F., Woodoate, M., Gribben, B, Badcock, K.J. and Richards, B.E. Solution of the unsteady Euler equations using an implicit dual-time method, AlAA J, 1998, 36, pp 14171424.Google Scholar
5. Badcock, K.J., Mcmillan, W., Woodoate|M.A., Gribben, B.J., Porter, S. and Richards, B.E. Integration of an implicit multiblock code into a workstation cluster environment, In: Parellel Computational Fluid Dynamics: Algorithms and Results using Advanced Computers, Schiano, P. et al (Eds), Elsevier Science, Amsterdam, 1996, pp 408415.Google Scholar
6. Zwaan, R.L. Lann wing, pitching oscillation, In: Compendium of unsteady aerodynamic measurements — Addendum I, AGARD Tech Report 702, 1985.Google Scholar
7. Badcock, K., Woodgate, M., Cantariti, F. and Richards, B. Solution of the unsteady Euler equations in three dimensions using a fully unfactored method. University of Glasgow Aerospace Engineering Report 9909, 1999.Google Scholar