IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v36y2024i3p820-835.html
   My bibliography  Save this article

Sparsity-Exploiting Distributed Projections onto a Simplex

Author

Listed:
  • Yongzheng Dai

    (Integrated Systems Engineering, The Ohio State University, Columbus, Ohio 43210)

  • Chen Chen

    (Integrated Systems Engineering, The Ohio State University, Columbus, Ohio 43210)

Abstract

Projecting a vector onto a simplex is a well-studied problem that arises in a wide range of optimization problems. Numerous algorithms have been proposed for determining the projection; however, the primary focus of the literature is on serial algorithms. We present a parallel method that decomposes the input vector and distributes it across multiple processors for local projection. Our method is especially effective when the resulting projection is highly sparse, which is the case, for instance, in large-scale problems with independent and identically distributed (i.i.d.) entries. Moreover, the method can be adapted to parallelize a broad range of serial algorithms from the literature. We fill in theoretical gaps in serial algorithm analysis and develop similar results for our parallel analogues. Numerical experiments conducted on a wide range of large-scale instances, both real world and simulated, demonstrate the practical effectiveness of the method.

Suggested Citation

  • Yongzheng Dai & Chen Chen, 2024. "Sparsity-Exploiting Distributed Projections onto a Simplex," INFORMS Journal on Computing, INFORMS, vol. 36(3), pages 820-835, May.
    • Handle: RePEc:inm:orijoc:v:36:y:2024:i:3:p:820-835
    DOI: 10.1287/ijoc.2022.0328
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijoc.2022.0328
    Download Restriction: no
    File URL: https://libkey.io/10.1287/ijoc.2022.0328?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:36:y:2024:i:3:p:820-835. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.