The IceProd Framework: distributed data processing for the IceCube neutrino observatory

Research output: Contribution to journalJournal articleResearchpeer-review

  • M.G. Aartsen
  • R. Abbasi
  • M. Ackermann
  • J. Adams
  • J.A. Aguilar
  • M. Ahlers
  • D. Altmann
  • C. Arguelles
  • J. Auffenberg
  • X. Bai
  • M. Baker
  • S.W. Barwick
  • V. Baum
  • R. Bay
  • Koskinen, D. Jason
  • Subir Sarkar
IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, iden- tify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and processing of data require a significant amount of computational resources. IceProd is a distributed management system based on Python, XML-RPC and GridFTP. It is driven by a central database in order to coordinate and admin- ister production of simulations and processing of data produced by the IceCube detector. IceProd runs as a separate layer on top of other middleware and can take advantage of a variety of computing resources, including grids and batch systems such as CREAM, Condor, and PBS. This is accomplished by a set of dedicated daemons that process job submission in a coordinated fashion through the use of middleware plugins that serve to abstract the details of job submission and job management from the framework.
Original languageEnglish
JournalJournal of Parallel and Distributed Computing
Volume75
Pages (from-to)198-211
Number of pages14
ISSN0743-7315
DOIs
Publication statusPublished - 2015

ID: 129935186