Discover
/
Article

Exploiting Highly Concurrent Computers for Physics

OCT 01, 1987
Architectures as varied as rigid arrays of many simple processors and reconfigurable networks of transputers are being used to solve problems as diverse as lattice gauge theories and neural networks.
Ken C. Bowler
Alastair D. Bruce
Richard D. Kenway
G. Stuart Pawley
David J. Wallace

Computational physics—that is, the use of computers to solve problems by simulating theoretical models—is part of a new methodology that has taken its place alongside theory and experiment during the last 50 years or so. Computer simulations permit one to study microscopic properties and their macroscopic consequences in a host of problems that may be inaccessible to direct experimental study or too complex for theoretical analysis. Thus computers have become laboratories for experimenting with theories. The growth of computational physics has been fueled by the explosion in the availability of relatively cheap and powerful computers—and, for just that reason, the field is utterly dependent for its good health on continued advances in computer technology.

This article is only available in PDF format

References

  1. 1. C. L. Seitz, J. Matisoo, PHYSICS TODAY, May 1984, page 38.

  2. 2. C. A. R. Hoare, Communicating Sequential Processes, Prentice‐Hall, Englewood Cliffs, N.J. (1984).

  3. 3. R. P. Feynman, A. R. Hibbs, Quantum Mechanics and Path Integrals, McGraw‐Hill, New York (1965).

  4. 4. K. G. Wilson, Phys. Rev. D 10, 2445 (1974). https://doi.org/PRVDAQ
    K. G. Wilson, in New Phenomena in Subnuclear Physics, A. Zichichi, ed., Plenum, New York (1977).

  5. 5. K. C. Bowler, C. B. Chalmers, R. D. Kenway, D. Roweth, D. Stephenson, Nucl. Phys. B, to be published; available as Edinburgh Univ. preprint 87/403.

  6. 6. See the review by R. H. Swendsen in Statistical and Particle Physics: Common Problems and Techniques, K. C. Bowler, A. J. McKane, eds., SUSSP Publications, Edinburgh (1984), p. 155.

  7. 7. G. S. Pawley, R. H. Swendsen, D. J. Wallace, K. G. Wilson, Phys. Rev. B 29, 4030 (1984).https://doi.org/PRBMDO

  8. 8. K. G. Wilson, J. B. Kogut, Phys. Rep. 12C, 75 (1974).

  9. 9. G. S. Pawley, G. W. Thomas, Phys. Rev. Lett. 48, 410 (1982).https://doi.org/PRLTAO

  10. 10. M. T. Dove, B. M. Powell, G. S. Pawley, L. S. Bartell, in preparation;
    nmr result sare reported by S. K. Garg, J. Chem. Phys. 66, 2517 (1977).https://doi.org/JCPSA6

  11. 11. S. Wolfram, J. Stat. Phys. 45, 471 (1986). https://doi.org/JSTPBS
    U. Frisch, D. d’Humieres, B. Hasslacher, P. Lallemand, Y. Pomeau, J.‐P. Rivet, in Proc. Wksp. Modern Approaches to Large Nonlinear Systems, Santa Fe 1986, to appear in J. Stat. Phys.

  12. 12. U. Frisch, B. Hasslacher, Y. Pomeau, Phys. Rev. Lett. 56, 1505 (1986).https://doi.org/PRLTAO

  13. 13. J. J. Hopfield, Proc. Natl. Acad. Sci. USA 79, 2554 (1982).https://doi.org/PNASA6

  14. 14. See, for example, articles in G. E. Hinton, J. A. Anderson, eds., Parallel Models of Associated Memory, Lawrence Erlbaum, Hillsdale, N.J. (1981);
    D. E. Rumelhart, J. L. McClelland, eds., Parallel Distributed Processing, vols. 1 and 2, MIT P., Cambridge, Mass. (1986);
    J. S. Denker, ed., Neural Networks for Computing, AIP Conf. Proc. 151, AIP, New York (1986).

  15. 15. B. M. Forrest, D. Roweth, N. Stroud, D. J. Wallace, G. V. Wilson, to be published in The Computer Journal, available as Edinburgh Univ. preprint 87/ 414, and references therein.

  16. 16. S. Geman, D. Geman, IEEE Trans. Pattern Anal. Machine Intelligence PAMI‐5, 721 (1984).https://doi.org/ITPIDJ

  17. 17. J. J. Hopfield, D. W. Tank, Biol. Cybern. 52, 141 (1985).https://doi.org/BICYAF

More about the Authors

Ken C. Bowler. University of Edinburgh.

Alastair D. Bruce. University of Edinburgh.

Richard D. Kenway. University of Edinburgh.

G. Stuart Pawley. University of Edinburgh.

David J. Wallace. University of Edinburgh.

Related content
/
Article
Figuring out how to communicate with the public can be overwhelming. Here’s some advice for getting started.
/
Article
Amid growing investment in planetary-scale climate intervention strategies that alter sunlight reflection, global communities deserve inclusive and accountable oversight of research.
/
Article
Although motivated by the fundamental exploration of the weirdness of the quantum world, the prizewinning experiments have led to a promising branch of quantum computing technology.
/
Article
As conventional lithium-ion battery technology approaches its theoretical limits, researchers are studying alternative architectures with solid electrolytes.
This Content Appeared In
pt-cover_1987_10.jpeg

Volume 40, Number 10

Get PT in your inbox

pt_newsletter_card_blue.png
PT The Week in Physics

A collection of PT's content from the previous week delivered every Monday.

pt_newsletter_card_darkblue.png
PT New Issue Alert

Be notified about the new issue with links to highlights and the full TOC.

pt_newsletter_card_pink.png
PT Webinars & White Papers

The latest webinars, white papers and other informational resources.

By signing up you agree to allow AIP to send you email newsletters. You further agree to our privacy policy and terms of service.