Abstract
Large scale multidisciplinary design optimization (MDO) problems often involve massive computation over vast data sets. Regardless of the MDO problem solving methodology, advanced computing technologies and architectures are indispensable. The data parallelism inherent in some engineering problems makes massively parallel architectures a natural choice, but efficiently harnessing the power of massive parallelism requires sophisticated algorithms and techniques. This paper presents an effort to apply massively scalable distributed control and dynamic load balancing techniques to the reasonable design space identification phase of a variable complexity approach to the multidisciplinary design optimization of a high speed civil transport (HSCT). The scalability and performance of two dynamic load balancing techniques, random polling and global round robin with message combining, and two termination detection schemes, token passing and global task count, are studied. The extent to which such techniques are applicable to other MDO paradigms, and to the potential for parallel multidisciplinary design with current large-scale disciplinary codes, is of particular interest.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Balabanov, V., Kaufman, M., Giunta, A., A., Grossman, B., Mason, W. H., Watson, L. T., and Haftka, R. T. (1996). Developing customized weight function by structural optimization on parallel computers. In 37th AIAAIASMEIASCE/AHSIASC,Structures, Structural Dynamics and Materials Conference, pages 113–125, Salt Lake City, UT, AIAA Paper 96–1336 (A96–26815).
Becker, J. and Bloebaum, C. (1996). Distributed computing for multidisciplinary design optimization using java. In Sixth AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pages 1583–1593, Bellevue, Washington. AIAA.
Bischof, C., Green, L., Haigler, K., and Jr., T. K. (1994). Parallel calculation of sensitivity derivatives for aircraft design using automatic differentiation. In Fifth AIAA/USAF/NASA/OAI Symposium on Multidisciplinary Analysis and Optimization, pages 73–86, Panama City, Florida. AIAA.
Box, G. E. P. and Behnken, D. W. (1960). Some New Three Level Designs for the Study of Quantitative Variables, volume 2. Technometrics.
Braun, R. and Kroo, I. (1995). Development and application of the collaborative optimization architecture in a multidisciplinary design environment, pages 98–116. In Multidisciplinary Design Optimization: State of the Art, N. Alexandrov, M.Y. Hussaini (Eds.). SIAM, Philadelphia.
Brzezinski, J., Hélary, J.-M., and Raynal, M. (1993). Distributed termination detection: General model and algorithms. Technical Report BROADCAST#TR9305, ESPRIT Basic Research Project BROADCAST.
Burgee, S., Giunta, A. A., Balabanov, V., Grossman, B., Mason, W. H., Narducci, R., Haftka, R. T., and Watson, L. T. (1996). A coarse-grained parallel variable-complexity multidisciplinary optimization paradigm. The International Journal of Supercomputer Applications and High Performance Computing, 10(4):269–299.
Dennis Jr., J., Lewis, R. M. (1994). Problem formulations and other issues in multidisciplinary optimization. Tech. Rep. CRPC–TR94469, CRPC, Rice University.
Dennis Jr., J., V. T. (1991). Direct search methods on parallel machines. SIAM Journal of Optimization, 1(4):448–474.
Doorly, D., Peiró, J., and Oesterle, J. (1996). Optimisation of aerodynamic and coupled aerodynamic-structural design using parallel genetic algorithms. In Sixth AIAA/NASAIISSMO Symposium on Multidisciplinary Analysis and Optimization, pages 401–409, Bellevue, Washington. AIAA.
Eldred, M., Hart, W., Bohnhoff, W., Romero, V., Hutchison, S., and Salinger, A. (1996). Utilizing object-oriented design to build advanced optimization strategies with generic implementation. In Sixth AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization,pages 1568–1582, Bellevue, Washington. AIAA.
Ghattas, O. and Orozco, C. (1995). A parallel reduced Hessian SQP method for shape optimization, pages 133–152. In Multidisciplinary Design Optimization: State of the Art, N. Alexandrov, M.Y. Hussaini (Eds.). SIAM, Philadelphia.
Giunta, A. A. (1997). Aircraft multidisciplinary design optimization using design of experiments theory and response surface modeling methods. PhD thesis, Virginia Polytechnic Institute and State University.
Guruswamy, G. (1998). Impact of parallel computing on high fidelity based multidisciplinary analysis. In Seventh AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pages 67–80, St. Louis, Missouri. AIAA.
Hale, M. and Craig, J. (1995). Use of agents to implement an integrated computing environment. In Computing in Aerospace 10, pages 403–413, San Antonio, Texas. AIAA.
Harris Jr., R. V. (1964). An analysis and correlation of aircraft wave drag. Technical Report TM X-947, NASA.
Hinkelman, K. (1994). Design and analysis of experiments. John Wiley & Sons, Inc.
Hopkins, D., Patnaik, S., and Berke, L. (1996). General-purpose optimization engine for multi-disciplinary design applications. In Sixth AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pages 1558–1565, Bellevue, Washington. AIAA.
Hulme, K. F. and Bloebaum, C. (1996). Development of CASCADE: a multidisciplinary design test simulator. In Sixth AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pages 438–447, Bellevue, Washington. AIAA.
Kameda, H., Li, J., Kim, C., and Zhang, Y. (1997). Optimal Load Balancing in Distributed Computer Systems. Springer-Verlag.
Kaufman, M. D. (1996). Variable-complexity response surface approximations for wing structural weight in hsct design. Master’s thesis, Virginia Polytechnic Institute and State University.
Knill, D., Giunta, A., Baker, C., Grossman, B., Mason, W., Haftka, R., and Watson, L. Response surface models combining linear and euler aerodynamics for hsct design. Journal of Aircraft (to appear).
Kroo, I., Altus, S., Braun, R., Gage, P., and Sobieski, I. (1994). Mul-tidisciplinary optimization methods for aircraft preliminary design. In Fifth AIAA/USAF/NASA/OAI Symposium on Multidisciplinary Analysis and Optimization, pages 697–707, Panama City, Florida. AIAA.
Kumar, V., Grama, A. Y., and Vempaty, N. R. (1994). Scalable load balancing techniques for parallel computers. Journal of Parallel and Distributed Computing, 22(1):60–79.
Ridlon, S. (1996). A software framework for enabling multidisciplinary analysis and optimization. In Fifth AIAA/USAF/NASAIOAI Symposium on Multidisciplinary Analysis and Optimization, pages 1280–1285, Panama City, Florida. AIAA.
Sanders, P. (1994). A detailed analysis of random polling dynamic load balancing. In International Symposium on Parallel Architectures, Algorithms,and Networks, pages 382–389, Kanazawa, Japan.
Sanders, P. (1995). Some implementations results on random polling dynamic load balancing. Technical Report iratr-1995–40, Universität Karlsruhe, Informatik für Ingenieure und Naturwissenschaftler.
Singhal, M. and Shivaratri, N. G. (1994). Advanced Concepts in Operating Systems. McGraw-Hill.
Snir, Marc O., W., S., Huss-Lederman, S., Walker, D. W., and Dongarra, J. (1996). MPI The Complete Reference. The MIT Press.
Tel, G. (1991). Topics in Distributed Algorithms. Number 1 in Cambridge International Series in Parallel Computation. Cambridge University Press.
Tel, G. (1994). Introduction to Distributed Algorithms. Cambridge University Press.
Weston, R., Townsend, J., Edison, T., Gates, R. (1994). A distributed computing environment for multidisciplinary design. In Fifth AIAA/USAF/NASA/OAI Symposium on Multidisciplinary Analysis and Optimization, pages 1091–1095, Panama City, Florida. AIAA.
Wujek, B., Renaud, J., and Batill, S. M. (1995). A concurrent engineering approach for multidisciplinary design in a distributed computing environment, pages 189–208. In MultidisciplinaryDesign Optimization: State of the Art, N. Alexandrov, M.Y. Hussaini (Eds.). SIAM, Philadelphia.
Yoder, S. and Brockman, J. (1996). A software architecture for collaborative development and solution of mdo problems. In Sixth AIAAINASAIISSMO Symposium on Multidisciplinary Analysis and Optimization, pages 1060–1062, Bellevue, Washington. AIAA.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1999 Springer Science+Business Media New York
About this chapter
Cite this chapter
Krasteva, D.T., Watson, L.T., Baker, C.A., Grossman, B., Mason, W.H., Haftka, R.T. (1999). Distributed Control Parallelism for Multidisciplinary Design of a High Speed Civil Transport. In: Yang, T. (eds) Parallel Numerical Computation with Applications. The Springer International Series in Engineering and Computer Science, vol 515. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5205-5_9
Download citation
DOI: https://doi.org/10.1007/978-1-4615-5205-5_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7371-1
Online ISBN: 978-1-4615-5205-5
eBook Packages: Springer Book Archive