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

• Published in: Journal of Parallel and Distributed Computing
• Main Authors: Aartsen, MG, Sarkar, S
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Elsevier 2016
• Subjects: South Pole; South pole
• Online Access: https://doi.org/10.1016/j.jpdc.2014.08.001; https://ora.ox.ac.uk/objects/uuid:3ffcaa9a-9c37-4665-a774-a7f5634dc155

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.