IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v2y1990i2p112-125.html
   My bibliography  Save this article

Matrix Balancing on a Massively Parallel Connection Machine

Author

Listed:
  • Stavros A. Zenios

    (Decision Sciences Department, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104)

Abstract

Matrix balancing models find applications in economics, transportation, regional sciences, statistics, stochastic modeling and other areas. The iterative scaling algorithm RAS that is used for the solution of these problems is shown here to be suitable for data level parallelism on the Connection Machine (CM). We develop synchronous and asynchronous parallel versions of RAS and discuss designs for implementation of both dense and sparse problems on the CM. We report numerical experiences with matrices of dimension up to 1000 × 1000 and 990000 nonzero entries. Problems of this size are solved within seconds on a Connection Machine model CM-2 with 32K processing elements, and the algorithm achieves peak rate of computing in excess of 300μFLOPS. INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

Suggested Citation

  • Stavros A. Zenios, 1990. "Matrix Balancing on a Massively Parallel Connection Machine," INFORMS Journal on Computing, INFORMS, vol. 2(2), pages 112-125, May.
  • Handle: RePEc:inm:orijoc:v:2:y:1990:i:2:p:112-125
    DOI: 10.1287/ijoc.2.2.112
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijoc.2.2.112
    Download Restriction: no

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orijoc:v:2:y:1990:i:2:p:112-125. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Matthew Walls). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.