DOI

  • D Theodoropoulos
  • Grigorios Chrysos
  • Iosif Koides
  • George Charitopoulos
  • Emmanouil Pissadakis
  • Antonis Varikos
  • Dionisios Pnevmatikatos
  • Georgios Smaragdos
  • Christos Strydis
  • Nikos Zervos
Recent market forecasts predict that the portable computing trend will vastly spread, as by 2020 there will bemore than 3 billion LTE device users worldwide. Motivated by this fact, many companies and research institutes have already launched research projects that utilize portable devices, voluntarily provided by users, to perform the required computations. Many such projects employ Berkeley's BOINC middleware, since it can support a large variety of stationary and mobile devices. However, currently available BOINC high-level APIs, either do not support portable devices or lack advanced processing capabilities (such as inter-node task dependencies) and/or easiness of use. To resolve these issues, we propose the mCluster software framework for application execution powered by the BOINC middleware on portable devices. mCluster adopts a task-based programming model that requires simple, pragma-based annotations of the application software, in order to dynamically resolve task dependencies. To evaluate our framework, we have have mapped a scientific application from the neuroscience domain on an small-scaled network of portable devices. mCluster significantly reduces the required programming effort and complexity to efficiently map BOINC-powered applications with task dependencies on portable devices compared to previous approaches.
Original languageEnglish
Title of host publicationProceedings 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2016
Place of PublicationDanvers
PublisherIEEE
Pages336-341
Number of pages6
ISBN (Electronic)978-1-5090-2453-7
ISBN (Print)978-1-5090-2452-0
DOIs
Publication statusPublished - 2016
Externally publishedYes

ID: 11144973