The ALICE analysis train system

Markus Zimmermann

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

Abstract

In the ALICE experiment hundreds of users are analyzing big datasets on a Grid system. High throughput and short turn-around times are achieved by a centralized system called the LEGO trains. This system combines analysis from different users in so-called analysis trains which are then executed within the same Grid jobs thereby reducing the number of times the data needs to be read from the storage systems. The centralized trains improve the performance, the usability for users and the bookkeeping in comparison to single user analysis. The train system builds upon the already existing ALICE tools, i.e. the analysis framework as well as the Grid submission and monitoring infrastructure. The entry point to the train system is a web interface which is used to configure the analysis and the desired datasets as well as to test and submit the train. Several measures have been implemented to reduce the time a train needs to finish and to increase the CPU efficiency.

Original languageEnglish
Article number012019
JournalJournal of Physics: Conference Series
Volume608
Issue number1
DOIs
StatePublished - 22 May 2015
Externally publishedYes
Event16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: Bridging Disciplines, ACAT 2014 - Prague, Czech Republic
Duration: 1 Sep 20145 Sep 2014

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