Skip to main content
SpringerLink
Log in

Geometry-defining processors for engineering design and analysis

  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

Critical issues of interactive three-dimensional geometry definition and high-speed parallel computation are addressed in a unified fashion by Geometry-Defining Processors (GDPs). GDPs are microprocessors housed in three-dimensional physical polyhedral packages which can be easily manually assembled or reconfigured to construct approximate scale models of physical objects or domains. An individual GDP communicates with neighboring GDPs in an assembly through optical ports associated with the faces of its package. An assembly of communicating GDPs is able to bothdefine a system geometry and, operating as an optimally connected parallel processor,solve the associated continuum partial differential equations required for design evaluation. Combining simplicity-of-use with efficient computational capabilities, the GDP design system should prove useful in numberous engineering applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Anagnostou G, Fischer PF, Dewey D, Patera AT (1989) Finite/spectral element Navier-Stokes methods on vector hypercubes and geometry-defining processor reconfigurable lattices. In: Chao CC, Orszag S, Shyy W (eds) Proc US/ROC (Taiwan) Joint Workshop on Recent Advandaces in Comp Fluid Dynamics, pp 1–60

  2. Athas WC, Seitz CL (1988) Multicomputers: message-passing concurrent computers. IEEE Comput 21:8:9–24

    Google Scholar 

  3. Bennett JA, Botkin ME (eds) (1986) The optimum shape. Plenum Press, New York

    Google Scholar 

  4. Blech RA (1987) The hypercluster: a parallel-processing testbed architecture for computational mechanics applications. NASA Tech Memo 89823, NASA Lewis Res Center, Cleveland, Ohio

    Google Scholar 

  5. Bokhari SH (1979) On the mapping problem. In: Proc 1979 Int Conf Parallel Processing, pp 239–248

  6. Boyce JW, Gilchrist JE (1982) GMSolid: interactive modeling for design and analysis of solids. IEEE Comput Graph Appl 2:27–40

    Google Scholar 

  7. Dally WJ, Song P (1987) Design of a self-timed VLSI multi-computer communication controller. Proc IEEE Int Conf Comput Design: VLSI in Computers and Processors, pp 230–234

  8. Dewey D, Patera AT (1988) Geometry-defining processors for partial differential equations. In: Alder BJ (ed) Special Purpose Computers. Academic Press, pp 67–96

  9. Erlebacher G, Eiseman PR (1987) Adaptive triangular mesh generation. AIAA J 25 (10):1356–1364

    Google Scholar 

  10. Fay DQM, Das PK (1987) Hardware reconfiguration of transputer networks for distributed object-oriented programming. Microprocessing and Microprogramming 21:1965–1990

    Google Scholar 

  11. Fischer PF, Patera AT (1988) Parallel spectral element solution of the Stokes problem. J Comput Phys (to appear)

  12. Fischer PF, Ho LW, Karniadakis GE, Rønquist EM, Patera AT (1988) Recent advances in parallel spectral element simulation of unsteady incompressible flows. Comput Struct 30:217–231

    Google Scholar 

  13. Fox G, Johnson M, Lyzenga G, Otto S, Salmon J, Walker D (1988) Solving problems on concurrent processors, vol 1. General techniques and regular problems. Prentice-Hall, Englewood Cliffs, New Jersey

    Google Scholar 

  14. Glowinski R, Golub GH, Meurant GA, Periaux J (eds) (1988) Proc First Int Conf on Domain Decomposition Methods for Partial Differential Equations. SIAM, Philadelphia

    Google Scholar 

  15. Gropp WD, Keyes DE (1988) Complexity of parallel implementation of domain decomposition techniques for elliptic partial differential equations. SIAM J Sci Stat Comput 9:312–326

    Google Scholar 

  16. Hoffman C, Hopcroft J (1985) Automatic surface generation in computer-aided design. The Visual Computer 1:92–100

    Google Scholar 

  17. Jain A (1986) Modern methods for automatic FE mesh generation. In: Baldwin K (ed) Proc Modern Methods for Automatic Finite Element Mesh Generation. ASCE National Convention, Boston, MA

    Google Scholar 

  18. Jordan HF (1978) A special purpose architecture for finite element analysis. In: Proc 1978 Int Conf on Parallel Processing, pp 263–266

  19. Li H, Maresca M (1987) Polymorphic-torus network. In: Proc 1987 Int Conf on Parallel Processing, pp 411–414

  20. Lin HX, Sips HJ (1986) A parallel vector reduction architecture. In: Proc 1986 Int Conf on Parallel Processing, pp 503–510

  21. Maday Y, Patera AT (1989) Spectral element methods for the incompressible Navier-Stokes equations. In: Noor A, Oden JT (eds) State-of-the-Art Surveys in Computational Mechanics ASME, pp 71–143

  22. May D (1987) The transpurer. In: Jesshope C (ed) Major Advances in Parallel Processing. Tech Press, Hampshire

    Google Scholar 

  23. McByron OA, Van de Velde EF (1987) Hypercube algorithms and implementations. In: Gear CW, Voigt RG (eds) Selected Papers from the Second Conference on Parallel Processing for Scientific Computing. SIAM, Philadelphia

    Google Scholar 

  24. Meagher DJ (1982) Geometric modelling using octree encoding. Comput Graph Image Proc 19:129–147

    Google Scholar 

  25. NEKTON User's Manual. Nektonics, 875 Main St, Cambridge, MA 02139

  26. Patera AT (1984) A spectral element method for fluid dynamics: laminar flow in a channel expansion. J Comput Phys 54:468–488

    Google Scholar 

  27. Przemienecki JS (1979) Matrix structural analysis of substructures. AIAA J 1:239–248

    Google Scholar 

  28. Rayfield JT, Silverman HF (1988) System and application software for the Armstrong Multiprocessor. IEEE Computer 21(6):38–52

    Google Scholar 

  29. Requicha AAG, Voclcker HB (1982) Solid modeling: a historical summary and contemporary assessment. IEEE Comput Graph Appl, pp 9–24

  30. Saad Y, Schultz MH (1985) Topological properties of hypercubes. Res Rep YALEU/DCS/RR-389, Yale Univ, New Haven

    Google Scholar 

  31. Scherr S (ed) (1988) Input Devices. Academic Press

  32. Strang G, Fix GJ (1973) An Analysis of the Finite Element method. Prentice-Hall, Englewood Cliffs, New Jersey

    Google Scholar 

  33. Thompson JF (1988) Composite grid generation code for general 3-D regions — the EAGLE code. AIAA J 26(3):271–272

    Google Scholar 

  34. Yerry MA, Shephard MS (1984) Automatic three-dimensional mesh generation by the modified octree technique. Int J Numer Methods Eng 20:1965–1990

    Google Scholar 

  35. Zienkiewicz OC, Phillips DV (1971) An automatic mesh generation scheme for plane and curved surfaces by ‘isoparametric’ coordinates. Int J Numer Methods Eng 3:519–528

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Massachusetts Institute of Technology, 02139, Cambridge, MA, USA

    G. Anagnostou, D. Dewey & A. T. Patera

Authors
  1. G. Anagnostou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D. Dewey
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. T. Patera
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Anagnostou, G., Dewey, D. & Patera, A.T. Geometry-defining processors for engineering design and analysis. The Visual Computer 5, 304–315 (1989). https://doi.org/10.1007/BF01914788

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01914788

Key words

Search

Navigation