IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0205568.html
   My bibliography  Save this article

DENIS: Solving cardiac electrophysiological simulations with volunteer computing

Author

Listed:
  • Violeta Monasterio
  • Joel Castro-Mur
  • Jesús Carro

Abstract

Cardiac electrophysiological simulations are computationally intensive tasks. The growing complexity of cardiac models, together with the increasing use of large ensembles of models (known as populations of models), make extensive simulation studies unfeasible for regular stand-alone computers. To address this problem, we developed DENIS, a cardiac electrophysiology simulator based on the volunteer computing paradigm. We evaluated the performance of DENIS by testing the effect of simulation length, task deadline, and batch size, on the time to complete a batch of simulations. In the experiments, the time to complete a batch of simulations did not increase with simulation length, and had little dependence on batch size. In a test case involving the generation of a population of models, DENIS was able to reduce the simulation time from years to a few days when compared to a stand-alone computer. Such capacity makes it possible to undertake large cardiac simulation projects without the need for high performance computing infrastructure.

Suggested Citation

  • Violeta Monasterio & Joel Castro-Mur & Jesús Carro, 2018. "DENIS: Solving cardiac electrophysiological simulations with volunteer computing," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-12, October.
  • Handle: RePEc:plo:pone00:0205568
    DOI: 10.1371/journal.pone.0205568
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0205568
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0205568&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0205568?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
    ---><---

    References listed on IDEAS

    as
    1. Willemijn Groenendaal & Francis A Ortega & Armen R Kherlopian & Andrew C Zygmunt & Trine Krogh-Madsen & David J Christini, 2015. "Cell-Specific Cardiac Electrophysiology Models," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-22, April.
    2. Carlos Sánchez & Alfonso Bueno-Orovio & Erich Wettwer & Simone Loose & Jana Simon & Ursula Ravens & Esther Pueyo & Blanca Rodriguez, 2014. "Inter-Subject Variability in Human Atrial Action Potential in Sinus Rhythm versus Chronic Atrial Fibrillation," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-14, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tanmay A Gokhale & Jong M Kim & Robert D Kirkton & Nenad Bursac & Craig S Henriquez, 2017. "Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-26, January.
    2. Jordan Elliott & Maria Kristina Belen & Luca Mainardi & Josè Felix Rodriguez Matas, 2021. "A Comparison of Regional Classification Strategies Implemented for the Population Based Approach to Modelling Atrial Fibrillation," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    3. Dmitrii Smirnov & Andrey Pikunov & Roman Syunyaev & Ruslan Deviatiiarov & Oleg Gusev & Kedar Aras & Anna Gams & Aaron Koppel & Igor R Efimov, 2020. "Genetic algorithm-based personalized models of human cardiac action potential," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-31, May.
    4. Gustavo Montes Novaes & Enrique Alvarez-Lacalle & Sergio Alonso Muñoz & Rodrigo Weber dos Santos, 2022. "An ensemble of parameters from a robust Markov-based model reproduces L-type calcium currents from different human cardiac myocytes," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-26, April.
    5. Sucheta Sehgal & Nitish D Patel & Avinash Malik & Partha S Roop & Mark L Trew, 2019. "Resonant model—A new paradigm for modeling an action potential of biological cells," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-25, May.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0205568. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.